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I Tried 12 System Design Courses. Here Are My Top 5 Recommendations for 2026

Dev Design Daily — Mon, 24 Aug 2026 08:06:25 +0000

I have a slightly embarrassing habit when I want to learn something properly: I try far more resources than I actually need. System design was no exception, and over time I worked through or sampled courses from Educative, ByteByteGo, DesignGurus, Udemy, Coursera, YouTube, and several smaller platforms that promised to make distributed systems finally "click."

Some were genuinely excellent. Others had beautiful diagrams but didn't give me enough practice, while a few somehow turned caching and load balancing into something considerably more complicated than they needed to be.

After trying 12 different options, I eventually narrowed my list down to the five best system design courses I would actually recommend in 2026.

This isn't a ranking based on which course has the most hours of content. I focused on something much more useful: which courses actually helped me become better at reasoning through a system design problem from scratch?

Personal note: I made the classic mistake of thinking that consuming more system design content would automatically make me better at system design. It didn't. The biggest improvement happened when I stopped memorizing architectures and started forcing myself to explain requirements, capacity, bottlenecks, failure modes, and trade-offs before looking at someone else's solution.

The short version: My 5 best system design courses for 2026

If you don't want to read the entire comparison, these are the five resources that made my final list.

Rank	Course	Best for	My take
1	Grokking Modern System Design Interview — Educative	Best overall	My first choice for structured interview preparation
2	ByteByteGo System Design	Visual learners	Excellent diagrams and real-world architecture explanations
3	Grokking the System Design Interview — DesignGurus	Interview case studies	Strong alternative for interview-focused preparation
4	Hello Interview System Design	Guided interview practice	Useful for understanding how strong interview answers develop
5	System Design courses on Udemy	Budget-conscious video learners	Good value if you choose the instructor carefully

There isn't one universally perfect course here because people learn differently. Someone preparing for an interview in four weeks has very different requirements from an engineer who simply wants to understand distributed systems over the next year.

If I could choose only one, however, I would start with Educative's Grokking Modern System Design Interview. The current course contains more than 200 lessons, eight mock interviews, roughly 26 hours of material, and a framework specifically designed to help you structure a 45-minute system design answer.

1. Grokking Modern System Design Interview on Educative — Best overall

My rating: 9.5/10

If someone asked me for one of the best system design courses to take before a serious technical interview, this is where I would send them first:

[Grokking Modern System Design Interview]https://www.educative.io/courses/grokking-the-system-design-interview?aff=xDPD)

There is also some history behind why Educative is so closely associated with system design preparation. Its Grokking interview-prep catalog dates back to 2015, and Educative itself describes Grokking as its long-running interview-preparation standard. The current system design course has been substantially expanded for today's interview landscape rather than remaining a static collection of old architecture questions.

What immediately stood out to me was the structure.

A lot of system design resources show you the final architecture. Educative spends considerably more time teaching you how to get there.

The course currently covers preliminary distributed-systems concepts, non-functional requirements, core building blocks, capacity and reliability considerations, and end-to-end design problems. Educative says the curriculum contains more than 40 chapters and sixteen end-to-end design problems, which makes it much closer to a complete preparation path than a collection of isolated case studies.

That distinction is why it ended up at number one for me.

What I liked most about Educative's approach

The hardest part of a system design interview usually isn't remembering what a load balancer does.

It's figuring out what to do after the interviewer says:

"Design YouTube."

You suddenly need to clarify requirements, identify scale, estimate capacity, choose APIs and storage, sketch the high-level architecture, decide where caching belongs, think about reliability, and explain trade-offs without disappearing down a technical rabbit hole.

Educative's current course teaches a structured framework called RESHADED for approaching that process. It emphasizes turning vague prompts into requirements and constraints before working through estimates, architecture, detailed design, and evaluation.

I found that much more useful than memorizing twenty finished diagrams.

Once you understand the process, unfamiliar interview questions become considerably less intimidating because you have somewhere to start.

Why this matters: Your interviewer probably doesn't care whether your architecture looks exactly like the solution from a course. They care whether you can explain why you made each decision and adapt when they change the requirements.

Educative also forces you to stay more active

This is another reason I put Educative first.

I like video courses, but system design is one subject where passive learning can create a dangerous amount of confidence. You watch someone design a notification service, understand everything they're saying, and convince yourself you could reproduce the architecture tomorrow.

Then tomorrow arrives.

You open an empty whiteboard.

Nothing happens.

Educative's browser-based learning style makes the experience more interactive, and the current Grokking course includes quizzes, design exercises, AI evaluation, and mock interviews alongside the core lessons. The course page currently lists eight mock interviews and specifically focuses on communication, trade-offs, capacity calculations, reliability, and structured diagramming.

That makes it my top recommendation for candidates who don't just want to learn about system design but need to actually demonstrate it.

My recommendation: If your interview is within the next one to three months, start here and complete the course problems actively. Before revealing each solution, spend 20–30 minutes designing your own version first.

2. ByteByteGo — Best for visual learners

My rating: 8/10

ByteByteGo was probably the easiest system design resource for me to consume.

Alex Xu and the ByteByteGo team are exceptionally good at taking intimidating distributed-systems concepts and turning them into diagrams that make you think, "Okay, that actually makes sense."

That ability shouldn't be underestimated.

Topics such as database sharding, caching, consistent hashing, message queues, rate limiting, replication, CDNs, and distributed storage can become extremely abstract when you're learning them entirely through text. ByteByteGo's visual approach makes the relationships between those components much easier to understand.

Current comparisons of the best system design courses consistently highlight ByteByteGo for its polished diagrams and worked examples, particularly for learners who prefer seeing complete architectures broken down visually.

For building intuition, I think it's excellent.

Why ByteByteGo isn't my number one

My only hesitation is that I find ByteByteGo more useful for understanding and reviewing architectures than for building a complete interview process from scratch.

That's an important distinction.

Seeing a beautifully illustrated Twitter architecture can help you understand fan-out, caching, feeds, databases, and asynchronous processing. But during an interview, nobody gives you the finished picture.

You have to create it.

That's why my preferred combination is actually Educative + ByteByteGo.

I use Educative for the structured interview framework and active problem-solving, then ByteByteGo when I want another visual explanation of a concept or architecture that hasn't completely clicked yet.

Personal note: ByteByteGo is the resource I would happily browse for an hour. Educative is the resource I would force myself to work through before an interview. Those sound similar, but they're two very different learning experiences.

If you're highly visual and don't currently have an interview deadline, ByteByteGo could easily be your favorite resource on this list.

3. Grokking the System Design Interview on DesignGurus — Best alternative for interview case studies

My rating: 8/10

DesignGurus is another platform that inevitably appears when you start researching the best system design courses, and there is a good reason for that.

Its Grokking-style system design material is heavily focused on interview problems and case studies. Rather than spending all of your time studying distributed-systems theory in isolation, you see those concepts applied to the types of open-ended architecture questions that appear during technical interviews.

I like that practical orientation.

System design can become an endless subject if you let it. You could spend months studying consensus algorithms, databases, distributed storage, networking, observability, and cloud architecture before ever attempting a mock interview.

A case-study-driven course prevents that.

It gives the concepts somewhere to live.

DesignGurus also remains one of the strongest alternatives to Educative if you specifically want interview-focused system design material, and current 2026 comparisons frequently put both platforms alongside ByteByteGo when discussing structured preparation.

Why I still prefer Educative

For my learning style, Educative feels more like a complete preparation environment.

I particularly like having foundational concepts, structured frameworks, end-to-end design problems, quizzes, AI-assisted evaluation, and mock interviews connected inside one learning path. Educative's current course also explicitly teaches capacity calculations, SLIs and SLOs, failure handling, trade-off narratives, and interview communication rather than focusing only on finished architectures.

DesignGurus remains a strong choice, especially if its presentation style works better for you.

4. Hello Interview — Best for understanding the actual interview conversation

My rating: 7.8/10

Hello Interview earned a place on my list for a slightly different reason.

A lot of courses teach architecture.

Hello Interview helped me think more about the interview itself.

That distinction matters because a system design interview isn't simply a technical exercise. It's a conversation where you're expected to clarify ambiguity, establish requirements, make assumptions, communicate trade-offs, respond to hints, and decide which parts of the architecture deserve deeper discussion.

You can know distributed systems extremely well and still perform poorly if your answer is chaotic.

That's why I like resources that expose you to the structure of strong interview answers rather than only teaching components.

Hello Interview's system design material is particularly useful as a complementary resource after you've already developed the fundamentals.

How I would use Hello Interview

I wouldn't necessarily make this my first system design course.

Instead, I would use it after completing a structured foundation such as Educative's Grokking course.

At that point, you already understand concepts such as replication, partitioning, caching, load balancing, queues, consistency, and storage. What you need next is practice turning that knowledge into a coherent 45–60 minute conversation.

That's where interview-oriented examples become much more useful.

Quick tip: When studying a completed system design answer, don't just ask, "Do I understand this architecture?" Ask, "Could I have arrived at this architecture myself?" Those are completely different standards.

If the answer is no, close the solution and try again.

5. Udemy system design courses — Best for budget-conscious video learners

My rating: 7.5/10

Udemy is difficult to rank because you're not really evaluating one system design course.

You're evaluating a marketplace.

There are excellent instructors teaching distributed systems, software architecture, microservices, databases, and system design. There are also courses that spend hours walking through architecture diagrams without giving you enough opportunity to reason through the problem yourself.

That variability is why Udemy comes fifth on my list.

The advantage is flexibility.

If you strongly prefer video learning, want to buy one course rather than subscribe to an entire learning platform, or find an instructor whose teaching style works exceptionally well for you, Udemy can provide great value.

The key is choosing carefully.

What I look for in a Udemy system design course

I pay much less attention to the total number of hours than I used to.

A 40-hour course isn't automatically better than a 15-hour course.

Instead, I look for a curriculum that covers the core building blocks and then forces those concepts into realistic design problems. I want discussions of trade-offs rather than statements such as "we'll use Kafka here," and I want the instructor to explain why a particular database, cache, queue, or consistency model makes sense.

Most importantly, I want exercises where I can stop the course and design the system myself.

If every problem immediately shows you the architecture, you're learning recognition rather than recall.

My rule for video courses: Pause before the solution. Give yourself 20 minutes with a blank page. Your ugly first attempt will teach you more than another twenty minutes of watching someone else's perfect diagram.

The seven courses that didn't make my top five

Trying twelve courses taught me something I didn't expect.

Most system design courses aren't necessarily bad.

They're just useful for different purposes.

Some resources I tried were extremely theoretical and would probably be excellent for an engineer who wanted a deeper distributed-systems education, but they weren't what I'd recommend to someone with a Meta interview next month. Others were wonderfully concise but felt more like revision material than complete learning paths.

A few relied heavily on video, which I personally find less effective for system design unless I'm constantly pausing to draw the architecture myself.

That is why I wouldn't obsess over finding a universally agreed-upon ranking of the best system design courses.

Start with your goal.

If you're preparing for interviews, choose a course designed around interview reasoning.

If you're trying to become a stronger distributed-systems engineer over the next year, you can afford to go considerably deeper.

What actually makes a system design course good?

After working through so many resources, I've become much pickier about what I consider a good system design course.

Pretty diagrams aren't enough.

A useful course should teach you how to move from an ambiguous problem to a defensible architecture.

That means learning how to clarify requirements, estimate scale, identify the most important non-functional requirements, choose storage models, introduce caches and queues where appropriate, reason about consistency and availability, identify bottlenecks, handle failures, and explain your trade-offs.

Most importantly, it should prepare you for unfamiliar questions.

Educative makes this point explicitly in its current Grokking curriculum: rather than treating system design as a set of formulaic answers to memorize, the course emphasizes first-principles reasoning and reusable building blocks that can be applied to new problems.

That is exactly what I want from a system design course.

I don't want to memorize how somebody else designed Dropbox.

I want to understand enough that I can design something I've never seen before.

Why Educative remains my trusted starting point for system design

There are more system design resources available in 2026 than ever before, but I still think Educative deserves special consideration because of how long the platform has been associated with structured Grokking-style interview preparation.

Educative currently describes its Grokking interview-prep curriculum as a standard it has been developing since 2015, while its flagship system design course continues to receive updates for the current interview environment. As of August 2026, Educative lists the course at roughly 26 hours and shows it as recently updated.

That history matters to me.

System design content ages.

Architectural principles such as caching, replication, partitioning, queues, and consistency remain important, but interview expectations and the systems engineers work with continue evolving.

I would rather use a course that continues being developed than rely entirely on an architecture guide written years ago and never revisited.

Recommended starting point: Grokking Modern System Design Interview on Educative is the course I'd choose first if I were beginning my system design preparation again in 2026.

How I would learn system design from scratch in 2026

If I had to start again, I wouldn't take twelve courses.

I learned that lesson the expensive way.

I'd start with Educative's Grokking Modern System Design Interview and use it to build my fundamentals and interview framework. I would work through every major design problem without looking at the solution first, even if my initial architecture was terrible.

Then I'd use ByteByteGo as a visual companion.

Whenever something such as consistent hashing, database replication, message queues, or distributed caching felt abstract, I'd find another visual explanation until the concept clicked.

After that, I'd move toward mock interviews and interview-style practice using Educative's mocks, Hello Interview, or another practice environment.

Finally, I'd read real engineering blogs and resources such as Designing Data-Intensive Applications to deepen the theory behind the decisions I was already making.

That is more than enough.

You do not need twelve courses.

Trust me.

My 4-week system design study plan

If I had an interview roughly one month away, I would keep the plan deliberately simple.

Week	Focus	What I'd use
Week 1	Fundamentals and building blocks	Educative Grokking
Week 2	End-to-end design problems	Educative + ByteByteGo
Week 3	Timed designs and weak areas	Educative mocks + Hello Interview
Week 4	Mock interviews and review	All three selectively

During the first week, I would focus heavily on understanding scalability, availability, reliability, databases, caching, queues, load balancing, partitioning, replication, and consistency. Educative's current course dedicates substantial sections to preliminary concepts, non-functional requirements, and sixteen essential building blocks before moving fully into end-to-end design problems.

During weeks two and three, I would progressively stop reading first.

Instead, I'd choose a prompt, start a timer, and design.

That transition from consumption to production is where most of the improvement happens.

One mistake I'd avoid with every system design course

Don't memorize the final diagrams.

I understand why people do it.

When you have an interview approaching, memorizing "Design Twitter," "Design YouTube," "Design Uber," and "Design WhatsApp" feels efficient because there's a decent chance you'll encounter something similar.

The problem appears when the interviewer changes one requirement.

Suddenly the memorized architecture doesn't fit anymore.

A much stronger approach is to understand the reusable building blocks behind those designs.

Why does this system need a queue?
Why are we partitioning this database?
What happens when one region becomes unavailable?
Where could eventual consistency be acceptable?
What is our read-to-write ratio?
What becomes the bottleneck at ten times the traffic?

Those questions transfer between systems.

The diagram doesn't.

Personal note: The moment system design became easier for me was when I stopped thinking, "What architecture am I supposed to draw?" and started thinking, "What problem does the next component need to solve?"

Which of the best system design courses should you choose?

My recommendation depends primarily on how you learn and what you're preparing for.

If you're preparing seriously for a system design interview and want one structured course, I would choose Grokking Modern System Design Interview on Educative.

If you're a visual learner who wants exceptionally clear diagrams and architecture breakdowns, ByteByteGo is difficult to beat.

If you want another interview-focused case-study resource, DesignGurus is a strong option.

If you already know the fundamentals and want to improve how you structure interview conversations, add Hello Interview.

And if you strongly prefer video learning or have a smaller budget, a carefully selected Udemy course can still be an excellent investment.

The important thing is not to confuse having more resources with being more prepared.

Final verdict: The best system design courses I would actually recommend in 2026

After trying twelve different resources, these are the five best system design courses I'd keep:

Grokking Modern System Design Interview — Educative — Best overall
ByteByteGo System Design — Best for visual learning
Grokking the System Design Interview — DesignGurus — Best alternative for interview case studies
Hello Interview System Design — Best for interview-oriented practice
Udemy system design courses — Best for video learners on a budget

If I were starting over, however, I wouldn't take all five.

I'd choose one primary course and use everything else selectively.

For me, that primary course would be Educative's Grokking Modern System Design Interview. Its combination of fundamentals, reusable building blocks, structured interview methodology, end-to-end problems, and mock interviews makes it the most complete starting point among the courses I tried. The current curriculum is explicitly designed to move from foundational concepts through distributed-system building blocks and into complete design problems rather than asking learners to memorize isolated solutions.

Then I'd practice.

And practice again.

Because after trying twelve courses, the most useful lesson I learned had very little to do with finding another course:

You don't get good at system design by watching people design systems. You get good by designing them yourself.

Reading and writing files in Java: Comprehensive 2026 guide

Dev Design Daily — Thu, 20 Aug 2026 07:37:06 +0000

Reading and writing files in Java is one of those topics that looks simple at first and then becomes surprisingly important once you start building real applications. You may begin by reading a few lines from a text file, but before long you are dealing with CSV exports, configuration files, logs, binary files, character encodings, large datasets, and error handling.

That is why learning reading and writing files in Java properly matters. Java gives you several APIs for file I/O, including the traditional java.io package and the newer java.nio.file package, and knowing when to use each approach can help you write cleaner, safer, and more efficient code.

In this guide, we will walk through the most useful ways to read and write files in Java, compare the major APIs, look at practical examples, and discuss the mistakes developers commonly make.

Personal note: File I/O was one of those Java topics I initially treated as "just syntax." It became much more important once I started working with applications that needed configuration loading, log processing, data exports, and backend integrations. The APIs themselves are not difficult, but choosing the right one for the size and structure of your data is the skill that matters.

What does reading and writing files in Java mean?

At the simplest level, file I/O means moving information between your Java application and files stored on a filesystem. When your program reads a file, it loads data from disk so that your application can process it, and when it writes a file, it takes data from memory and saves it to disk.

Java provides two major families of APIs for this work. The older java.io package gives you readers, writers, streams, and file abstractions, while the newer java.nio.file package provides the Path and Files APIs that make many common operations easier to express.

Java API	Package	Best suited for
Traditional I/O	`java.io`	Readers, writers, byte streams, legacy applications
New I/O	`java.nio.file`	Paths, modern file operations, concise utility methods

For new applications, I generally recommend starting with Path and Files because the APIs are readable and convenient. The older java.io classes still matter, especially when you need stream-based processing or are maintaining an existing codebase.

Understanding `Path` before working with files

Modern Java file handling usually starts with a Path. A Path represents the location of a file or directory, which is cleaner and safer than passing raw path strings throughout your code.

Here is a simple example:

import java.nio.file.Path;

public class FileExample {
    public static void main(String[] args) {
        Path path = Path.of("data.txt");

        System.out.println(path);
    }
}


You can also create a nested path without manually inserting operating-system-specific separators:

Path path = Path.of("data", "users", "users.txt");


If you are working with older Java code, you may see `Paths.get()` instead:

import java.nio.file.Path;


import java.nio.file.Paths;

Path path = Paths.get("data.txt");

For modern Java versions, `Path.of()` is usually the cleaner option.

> **Tip:** Avoid hardcoding separators such as `data\\users\\users.txt`. Building paths with `Path.of()` makes your code more portable across Windows, Linux, and macOS.


## Reading an entire text file with `Files.readString()`

If you are working with a small or moderately sized text file, `Files.readString()` is one of the simplest ways to read it. The method reads the complete file into a `String`, which makes it useful for configuration files, short templates, JSON documents, or other text content that comfortably fits in memory.

Suppose `message.txt` contains:

Java file handling is easier than it looks.


You can read it like this:

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

public class ReadFileExample {

public static void main(String[] args) {

Path path = Path.of("message.txt");

try {

String content = Files.readString(path);

System.out.println(content);

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

The output will be:

Java file handling is easier than it looks.


This is usually my first choice when the file is small and I simply need its complete contents as text.

> **Personal note:** Convenience methods are great until the data gets large. I have seen developers use methods such as `readString()` for files that should have been streamed line by line, so always think about file size before deciding that the shortest code is automatically the best code.


## Reading a file line by line with `Files.readAllLines()`

Sometimes you want each line as a separate element instead of receiving one large string. In that case, `Files.readAllLines()` returns the file contents as a `List<String>`.

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

import java.util.List;

public class ReadLinesExample {

public static void main(String[] args) {

Path path = Path.of("languages.txt");

try {

List\<String> lines = Files.readAllLines(path);

for (String line : lines) {

System.out.println(line);

            }

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

If `languages.txt` contains:

Java


Python

Go

Rust

The program prints each line individually.

This approach is especially convenient when you need to inspect, transform, or filter a small set of lines. However, it still loads the entire file into memory, so it is not ideal for very large files.


## Reading large files with `Files.lines()`

When a file becomes large, loading the entire thing into memory may be inefficient. Java's `Files.lines()` method lets you process the file as a `Stream<String>`, which is often a better fit for logs, datasets, or large text exports.

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

import java.util.stream.Stream;

public class StreamFileExample {

public static void main(String[] args) {

Path path = Path.of("large-file.txt");

try (Stream\<String> lines = Files.lines(path)) {

lines.forEach(System.out::println);

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

The important part is the `try-with-resources` statement. The stream is associated with an open file resource, so you want Java to close it automatically after processing is complete.

You can also combine `Files.lines()` with the Streams API:

try (Stream lines = Files.lines(Path.of("users.txt"))) {


long activeUsers = lines

.filter(line -> line.contains("ACTIVE"))

.count();

System.out.println(activeUsers);

}

This approach is useful because you can process the data while it is being read rather than loading everything first and then performing a second pass.


## Reading files with `BufferedReader`

`BufferedReader` has been one of the standard ways to read text files in Java for years. It remains useful today, particularly when you want direct control over line-by-line processing.

import java.io.BufferedReader;


import java.io.FileReader;

import java.io.IOException;

public class BufferedReaderExample {

public static void main(String[] args) {

try (BufferedReader reader =

new BufferedReader(new FileReader("data.txt"))) {

String line;

while ((line = reader.readLine()) != null) {

System.out.println(line);

            }

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

The call to `reader.readLine()` returns one line at a time. When there are no more lines, it returns `null`, which makes a `while` loop a natural way to process the file.

`BufferedReader` is a strong choice when your processing logic contains state, multiple conditions, counters, or other logic that feels awkward inside a stream pipeline.


## `Files.lines()` vs `BufferedReader`

Both approaches are useful for reading files without loading everything into memory, but they support slightly different coding styles.

| ApproachBest when      |                                                                     |
| ---------------------- | ------------------------------------------------------------------- |
| `Files.lines()`        | You want to use Java Streams for filtering, mapping, or aggregation |
| `BufferedReader`       | You want explicit control over each line                            |
| `Files.readString()`   | You need the complete contents of a small text file                 |
| `Files.readAllLines()` | You need all lines as a `List<String>`                              |

I tend to use `Files.lines()` when the problem naturally fits a stream pipeline and `BufferedReader` when the logic is easier to understand as a traditional loop. Neither is universally better, so the best choice depends on the work your program needs to perform.


## Writing text files with `Files.writeString()`

Reading files is only half of **reading and writing files in Java**. Writing is just as important, and modern Java makes simple text output very straightforward with `Files.writeString()`.

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

public class WriteFileExample {

public static void main(String[] args) {

Path path = Path.of("output.txt");

try {

Files.writeString(path, "Hello from Java!");

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

If the file does not exist, Java creates it under the default options. If it already exists, the existing content is normally replaced.

This method works well for small reports, generated text, configuration output, and simple files where you already have the content available as a `String`.


## Writing multiple lines with `Files.write()`

When your application already stores content as a collection of strings, `Files.write()` can be more convenient than manually joining everything together.

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

import java.util.List;

public class WriteLinesExample {

public static void main(String[] args) {

List\<String> languages = List.of(

"Java",

"Python",

"Go",

"Rust"

        );

try {

Files.write(Path.of("languages.txt"), languages);

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

The resulting file contains:

Java


Python

Go

Rust

This is especially useful for exports, reports, generated configuration files, or any other situation where your program naturally produces a list of lines.


## Appending data instead of overwriting a file

One common beginner mistake is accidentally replacing a file when the intention was to add new content to it. Java allows you to control this behavior through `StandardOpenOption`.

For example, suppose you are creating a simple application log:

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

import java.nio.file.StandardOpenOption;

public class AppendFileExample {

public static void main(String[] args) {

Path path = Path.of("app.log");

try {

Files.writeString(

path,

"Application started" + System.lineSeparator(),

StandardOpenOption.CREATE,

StandardOpenOption.APPEND

            );

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

`CREATE` tells Java to create the file if it does not already exist, while `APPEND` tells it to add content to the end rather than replacing what is already there.

> **Tip:** Before writing any file, decide whether the correct behavior is to replace the file, append to it, or fail if it already exists. Making that decision explicitly helps prevent accidental data loss.


## Writing files with `BufferedWriter`

`BufferedWriter` is useful when you need to perform repeated text writes. Rather than sending every small write operation directly to the underlying destination, buffering lets Java collect content before writing larger chunks.

import java.io.BufferedWriter;


import java.io.FileWriter;

import java.io.IOException;

public class BufferedWriterExample {

public static void main(String[] args) {

try (BufferedWriter writer =

new BufferedWriter(new FileWriter("output.txt"))) {

writer.write("First line");

writer.newLine();

writer.write("Second line");

writer.newLine();

writer.write("Third line");

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

The `newLine()` method is useful because it uses the appropriate line separator for the current platform. That makes it a better choice than manually assuming a particular newline character when portability matters.


## Why buffering matters

Buffering is primarily about efficiency. If your program performs many tiny read or write operations, repeatedly communicating with the underlying filesystem can create unnecessary overhead.

Without buffering, the flow conceptually looks like this:

Java program


    ↓

small write

    ↓

disk

Java program

    ↓

small write

    ↓

disk

With buffering, multiple small operations can be collected before a larger write takes place:

Java program


    ↓

buffer

    ↓

buffer fills

    ↓

larger disk write

For a tiny text file, you probably will not notice much difference. For repeated operations, larger workloads, and long-running applications, buffering can become much more important.


## Understanding try-with-resources

One of the most important habits when **reading and writing files in Java** is properly closing resources. Older Java code often contains verbose cleanup logic, but modern Java gives you a much cleaner approach through try-with-resources.

Instead of writing manual cleanup code, you can do this:

try (BufferedReader reader =


new BufferedReader(new FileReader("data.txt"))) {

String line;

while ((line = reader.readLine()) != null) {

System.out.println(line);

    }

}

Java automatically closes the resource when execution leaves the `try` block.

This works with resources that implement `AutoCloseable`, including many Java I/O classes.

> **Personal note:** Resource cleanup feels unimportant when you are experimenting with five-line examples because the program exits almost immediately. In long-running applications, leaking file handles can become a real operational problem, so try-with-resources is a habit worth building from the beginning.


## Reading files with a specific character encoding

Character encoding is easy to ignore until you encounter corrupted text. Modern Java methods often use UTF-8 by default, but you can also specify the charset explicitly when you need predictable behavior.

import java.nio.charset.StandardCharsets;


import java.nio.file.Files;

import java.nio.file.Path;

String content = Files.readString(

Path.of("data.txt"),

StandardCharsets.UTF\_8

);

You can use the same approach when writing:

Files.writeString(


Path.of("output.txt"),

"Hello, Java!",

StandardCharsets.UTF\_8

);

This becomes particularly important when your application processes international text, communicates with external systems, or reads files created by applications using a different encoding.

When encoding assumptions do not match, characters may be displayed incorrectly or corrupted entirely.


## Reading binary files in Java

Not every file contains text. Images, PDFs, ZIP archives, audio files, and many custom formats contain binary data, which means you should work with bytes rather than characters.

For a small binary file, you can use `Files.readAllBytes()`:

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

public class BinaryReadExample {

public static void main(String[] args) {

try {

byte[] data = Files.readAllBytes(Path.of("image.png"));

System.out.println("Bytes read: " + data.length);

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

You can write binary data similarly:

byte[] data = {10, 20, 30, 40};


Files.write(Path.of("data.bin"), data);

This is convenient for small files, but larger binary files are usually better handled with streams so that you do not need to load the entire file into memory.


## Reading binary files with `InputStream`

For larger binary files, `InputStream` allows you to process data in chunks.

import java.io.FileInputStream;


import java.io.IOException;

import java.io.InputStream;

public class InputStreamExample {

public static void main(String[] args) {

try (InputStream input =

new FileInputStream("image.png")) {

byte[] buffer = new byte[4096];

int bytesRead;

while ((bytesRead = input.read(buffer)) != -1) {

System.out.println("Read " + bytesRead + " bytes");

            }

        } catch (IOException e) {

e.printStackTrace();

        }

    }

}

Instead of holding the complete file in memory, this program reads chunks of up to 4,096 bytes at a time.

This pattern is common when handling large uploads, downloads, media files, archives, and network-based data transfer.


## Text streams vs byte streams

A useful distinction in Java file handling is the difference between character-based and byte-based APIs.

| Data typeCommon Java classesTypical use |                                                                              |                                     |
| --------------------------------------- | ---------------------------------------------------------------------------- | ----------------------------------- |
| Characters                              | `Reader`, `Writer`, `BufferedReader`, `BufferedWriter`                       | Text files                          |
| Bytes                                   | `InputStream`, `OutputStream`, `BufferedInputStream`, `BufferedOutputStream` | Images, PDFs, archives, binary data |

If the data represents readable text, character-based APIs are usually easier to work with. If the file contains arbitrary binary data, byte streams are the appropriate choice.

> **Tip:** Do not choose an API based only on the file extension. Think about the actual data representation inside the file and whether your program should interpret it as characters or raw bytes.


## Checking whether a file exists

Before reading or modifying a file, you may want to check whether it exists.

import java.nio.file.Files;


import java.nio.file.Path;

Path path = Path.of("config.txt");

if (Files.exists(path)) {

System.out.println("File exists");

} else {

System.out.println("File not found");

}

You can also determine whether the path points to a regular file:

if (Files.isRegularFile(path)) {


System.out.println("This is a regular file");

}

Or whether it represents a directory:

if (Files.isDirectory(path)) {


System.out.println("This is a directory");

}

These checks become useful when your program accepts paths from users or interacts with files that may be created and removed outside your application's control.


## Creating directories before writing files

Suppose your application needs to write a report here:

reports/2026/summary.txt


If the parent directories do not exist, the write operation may fail. You can create the entire directory hierarchy with `Files.createDirectories()`.

Path directory = Path.of("reports", "2026");


Files.createDirectories(directory);

You can then build the file path using `resolve()`:

Path file = directory.resolve("summary.txt");


Files.writeString(file, "Annual report");

Using `resolve()` keeps path construction readable and avoids manually concatenating strings.


## Handling `IOException` properly

Many file operations can throw `IOException`, and that is not just a compiler inconvenience. File operations genuinely fail for many reasons, so your application should decide what to do when that happens.

For small learning examples, you often see:

catch (IOException e) {


e.printStackTrace();

}

In a real application, you may want something more intentional:

try {


String content = Files.readString(Path.of("config.txt"));

} catch (IOException e) {

System.err.println("Unable to read configuration file.");

}

Some common reasons file operations fail include:

-  The file does not exist. 
-  Your application does not have permission to access it. 
-  The filesystem is unavailable. 
-  The disk is full. 
-  The path points to a directory rather than a file. 
-  Another process is interfering with access. 
-  The file uses an unexpected encoding. 
-  A parent directory does not exist. 

Good file-handling code should treat these situations as part of normal error handling rather than as impossible edge cases.


## A practical example: Reading and updating a simple task file

Let's combine several of the ideas from this guide into a small task manager.

Suppose `tasks.txt` contains:

Learn Java streams


Practice file handling

Build a small project

We want to read the existing tasks and then append another one.

import java.io.IOException;


import java.nio.file.Files;

import java.nio.file.Path;

import java.nio.file.StandardOpenOption;

import java.util.List;

public class TaskManager {

public static void main(String[] args) {

Path taskFile = Path.of("tasks.txt");

try {

if (Files.exists(taskFile)) {

List\<String> tasks = Files.readAllLines(taskFile);

System.out.println("Current tasks:");

for (String task : tasks) {

System.out.println("- " + task);

                }

            }

Files.writeString(

taskFile,

System.lineSeparator() + "Review Java NIO",

StandardOpenOption.CREATE,

StandardOpenOption.APPEND

            );

        } catch (IOException e) {

System.err.println("Unable to process task file.");

e.printStackTrace();

        }

    }

}

This small example checks whether a file exists, reads the current content, displays each line, and then appends another task. The same concepts appear in larger systems, even if the surrounding architecture becomes significantly more complex.

---

## Common mistakes when reading and writing files in Java

File I/O is straightforward once you understand the APIs, but a few mistakes appear repeatedly in beginner and production code.

One common issue is loading huge files entirely into memory because a convenience method was easier to write. Methods such as `Files.readString()` and `Files.readAllLines()` are excellent when the file is small, but large datasets and logs should usually be processed incrementally.

Another common mistake is forgetting to close resources. Try-with-resources solves most of this problem cleanly, so you should use it whenever you are working directly with closable streams, readers, or writers.

Encoding assumptions also cause bugs that can be difficult to notice at first. If your application writes text using one encoding and another program reads it using a different one, characters may become corrupted.

Finally, developers sometimes catch every `IOException` and ignore it. If your application fails to read an important configuration file or cannot write critical output, continuing silently can create much harder problems later.

> **Tip:** Treat reading and writing as operations that can fail, and decide what the correct recovery behavior should be before you simply add a `catch` block.


## Which Java file API should you use?

If the number of options feels confusing, this practical decision table is a useful place to start.

| SituationRecommended approach    |                                        |
| -------------------------------- | -------------------------------------- |
| Read a small text file           | `Files.readString()`                   |
| Read all lines from a small file | `Files.readAllLines()`                 |
| Process a large text file        | `Files.lines()` or `BufferedReader`    |
| Write a small string             | `Files.writeString()`                  |
| Write a collection of lines      | `Files.write()`                        |
| Perform many text writes         | `BufferedWriter`                       |
| Read a small binary file         | `Files.readAllBytes()`                 |
| Process large binary data        | `InputStream` or buffered byte streams |
| Append to an existing file       | `StandardOpenOption.APPEND`            |

For most modern Java applications, I recommend starting with `Path` and `Files`. When your problem becomes more stream-oriented, memory-sensitive, or specialized, move toward readers, writers, input streams, and output streams.


## A good way to practice reading and writing files in Java

The fastest way to get comfortable with **reading and writing files in Java** is to build something small rather than trying to memorize every method in the standard library.

A command-line notes application is a good starting point because it forces you to create files, append entries, read previous notes, and handle missing files. A CSV analyzer is another useful project because it introduces line-by-line processing, parsing, validation, and data transformation.

A log analyzer is also a great practice exercise. You can read a log file, find lines containing `"ERROR"`, count them, and then write the result to a summary file.

try (var lines = Files.lines(Path.of("application.log"))) {




long errors = lines

.filter(line -> line.contains("ERROR"))

.count();

Files.writeString(

Path.of("summary.txt"),

"Total errors: " + errors

    );

}

This example is small, but it combines file reading, streams, filtering, aggregation, and file writing in one practical workflow.

> **Personal note:** I learn Java concepts much faster when I connect them together. File I/O becomes far more memorable when you combine it with streams, collections, exceptions, and small projects instead of treating each topic as a separate chapter.


## How file I/O connects to real Java applications

It is easy to think of file handling as a beginner topic, but the underlying concepts appear throughout professional Java development.

Backend services may read configuration files at startup. Data pipelines may process exported CSV or JSON files. Build tools read and generate files continuously. Logging systems write application events to files or forward them to other systems. Command-line applications frequently store local state, while migration utilities often read data from one format and write transformed output somewhere else.

The exact API may change depending on the application, but the fundamentals remain the same. You still need to understand paths, character encoding, resource cleanup, streaming, buffering, error handling, and the difference between text and binary data.

That is why **reading and writing files in Java** is worth learning properly even if you expect to spend most of your career building APIs or cloud services.


## Final thoughts

Learning **reading and writing files in Java** is less about memorizing every class in `java.io` and `java.nio` and more about understanding what kind of data you have and how your application should process it.

For small text files, methods such as `Files.readString()` and `Files.writeString()` keep your code concise and readable. For larger text files, `Files.lines()` and `BufferedReader` let you process data incrementally, while byte streams remain essential when you are working with images, archives, PDFs, and other binary formats.

The most important habits are fairly simple. Use try-with-resources when working with closable resources, think deliberately about encoding, avoid loading huge files into memory unnecessarily, choose append versus overwrite behavior carefully, and treat I/O failures as something your program needs to handle intentionally.

Once those habits become natural, file handling stops feeling like a standalone Java topic. It becomes another practical tool you can use when building configuration systems, log processors, command-line applications, backend services, data pipelines, and larger Java projects.

If you want to keep building your skills beyond this guide, Educative's Java courses are a useful next step because they let you practice concepts such as file I/O alongside the broader Java skills that real applications require.

Is a Udemy course really worth it? An honest Udemy review before you buy another course

Dev Design Daily — Wed, 19 Aug 2026 06:47:30 +0000

If you've ever searched Google for a programming language, certification, business skill, design tool, or almost anything else you can learn online, there's a good chance you've landed on Udemy.

The platform is enormous. Udemy currently advertises a catalog of more than 250,000 courses covering everything from web development and data science to marketing, leadership, photography, and personal finance. That enormous selection sounds fantastic until you're staring at twelve courses teaching exactly the same topic and wondering which instructor actually deserves your money.

That brings us to the question I hear surprisingly often:

Is a Udemy course really worth it?

My answer is yes, but with a fairly large asterisk attached.

I've used enough online learning platforms over the years to realize that the platform itself is only half of the equation. Udemy can offer extraordinary value when you find an excellent instructor teaching exactly what you need, but the marketplace model also means the experience can vary considerably from one course to another.

If you're trying to decide whether a Udemy course is really worth it, this review will help you understand what you're actually paying for, where Udemy shines, where I think it falls short, and why developers in particular should also consider a more structured, interactive alternative such as Educative.io.

Personal note: My biggest mistake with online courses was assuming that buying a course counted as making progress. At one point, my course library looked significantly more impressive than my actual skill set. These days, I judge a learning platform by how much it gets me to do, rather than how much content it gives me permission to watch.

The short answer: Is a Udemy course really worth it?

Yes, a good Udemy course can absolutely be worth it.

The important word there is good.

Udemy is a marketplace, which means instructors create and manage their own courses rather than every course following one centrally designed curriculum. Udemy itself explains that instructors own and manage their course content, which is one reason the learning experience can differ substantially depending on whose course you choose.

When you find an excellent instructor, this model works beautifully.

You can learn directly from someone who understands a technology deeply, follow a carefully structured curriculum, complete exercises, revisit difficult sections, and keep access to an individually purchased course for as long as Udemy retains the necessary license and your account remains in good standing.

When you choose poorly, however, the experience can feel very different.

You may encounter a course that looked comprehensive from the landing page but spends hours covering basics, hasn't kept pace with the technology, or relies so heavily on passive video that you finish the material without feeling confident enough to build anything independently.

That variability is the most important thing to understand before purchasing.

My rule: Don't ask whether Udemy is worth it. Ask whether this specific Udemy course, from this specific instructor, for this specific skill is worth your time. That's a much better question.

What makes Udemy attractive in the first place?

Udemy's biggest advantage is choice.

There are very few mainstream learning platforms where you can search for something extremely specific and have a reasonable chance of finding an entire course dedicated to it.

You might want to learn Python from scratch, prepare for an AWS certification, understand Kubernetes, improve your Excel skills, learn Blender, study digital marketing, or finally understand that JavaScript framework everyone on your team keeps talking about.

There's probably a Udemy course for it.

Actually, there are probably twenty.

Udemy says its overall catalog contains more than 250,000 courses, while its Personal Plan provides access to a curated subset of courses rather than the entire marketplace.

That breadth is extremely valuable if you're a curious learner who frequently jumps between different disciplines.

At the same time, abundance creates its own problem.

Finding a course is easy.

Finding the right course takes considerably more work.

The individual-course model is still one of Udemy's strongest advantages

One thing I genuinely like about Udemy is the ability to purchase individual courses instead of always needing another subscription.

If you buy an individual course, Udemy currently provides ongoing access to that course, subject to its lifetime-access conditions. Subscription content works differently because you retain access only while your subscription remains active.

I think this model makes a lot of sense for certain learners.

Imagine you want one comprehensive AWS certification course and expect to spend three months studying it. You don't necessarily need access to thousands of unrelated courses during those three months.

You need one excellent course.

Buying it individually means you can work through it at your own pace, return months later when you've forgotten something, and use it as a reference when necessary.

That's much more appealing than feeling pressured to finish because another subscription payment is approaching.

Quick tip: If you're buying an individual Udemy course, don't evaluate the purchase only by the number of hours included. A focused 12-hour course that gets you building can be considerably more useful than a 60-hour course filled with repetition.

Udemy works particularly well when you find the right instructor

The instructor matters enormously on Udemy.

In fact, I'd argue that choosing the instructor is more important than choosing the platform.

Some instructors are outstanding teachers who spend years refining their courses, answering questions, updating examples, and improving explanations. When you discover someone whose teaching style matches the way you learn, Udemy can offer remarkable value.

Before buying, I spend time examining the course rather than immediately clicking the purchase button.

I look at when it was updated, how the curriculum progresses, whether the instructor explains why things work rather than simply demonstrating steps, what recent students say, and whether the preview lectures are genuinely clear.

Udemy allows prospective learners to preview course material before purchasing, so there is little reason to buy completely blind.

A five-minute preview can tell you a surprising amount.

If you already find yourself checking another browser tab during the preview, twenty more hours of the same teaching style probably won't magically become exciting.

Where Udemy starts becoming difficult for developers

This is where my opinion becomes more nuanced.

Video is fantastic for demonstrating concepts.

It's not always fantastic for mastering them.

I've watched plenty of programming tutorials where everything made perfect sense while the instructor was writing the code. I understood every line, nodded along confidently, and genuinely felt like I had learned the topic.

Then I closed the video and opened an empty editor.

Suddenly, my brain behaved as if we'd never discussed programming before.

That experience taught me an important distinction between recognition and recall.

Watching someone solve a problem gives you recognition.

Solving it yourself requires recall.

Real software development requires considerably more of the second.

Udemy does support learning features beyond video, including quizzes, coding exercises, assignments, practice tests, and downloadable resources, although feature availability differs by platform and individual course.

The problem is that the quality and depth of those activities still depend heavily on the particular course.

Developer note: Whenever you're following a coding course, stop copying the instructor. Watch the explanation, close the solution, and rebuild the project yourself. The moment you become stuck is usually the moment the real learning begins.

The biggest Udemy problem isn't course quality, it's course collecting

I have a theory about Udemy.

A surprisingly large number of people aren't using it as a learning platform.

They're using it as a digital bookshelf.

You see an interesting course, convince yourself Future You will definitely complete it, buy it, watch three lectures, and then discover another course you apparently need first.

Soon your library contains React, Python, Kubernetes, machine learning, AWS, Docker, system design, and seven technologies you can't remember being interested in.

I've been there.

The problem isn't unique to Udemy, but inexpensive individual courses can make it especially easy to accumulate educational content faster than you can consume it.

That's why my answer to is a Udemy course really worth it depends partly on your learning discipline.

One completed course can be extremely valuable.

Twenty unfinished courses are mostly bookmarks you paid for.

What about Udemy certificates?

Udemy provides certificates of completion for approved paid courses, but it's important to understand what those certificates represent.

Udemy explicitly states that it isn't an accredited institution. The certificate documents that you completed a course, but it shouldn't be confused with an accredited academic qualification or an industry certification such as AWS Certified Solutions Architect.

Personally, I wouldn't choose a Udemy course because of the certificate.

I'd choose it because of the skill.

If you're learning software development, a working project you can explain confidently usually tells a much stronger story than another completion badge. If you're studying for an external certification, the real objective is passing that certification exam and understanding the underlying technology.

Treat the certificate as a nice record of completion.

Don't treat it as the primary return on your investment.

Can you get your money back if the course isn't right?

This is another useful advantage.

Udemy currently offers refunds for eligible individual course purchases within 30 days, subject to its refund-policy conditions and restrictions. That makes experimenting with an unfamiliar instructor somewhat less risky, although the policy shouldn't be treated as permission to consume most of a course and then request your money back.

Subscriptions have different rules, so don't assume that the same refund conditions apply to a Personal Plan subscription.

For individual purchases, though, I appreciate having that safety net.

Online courses are difficult to judge from landing pages alone.

Sometimes you simply need to start learning before you know whether the instructor's style works for you.

Is Udemy worth it for programming?

This is where I'd separate casual learning from serious technical development.

If you want to learn a specific framework, library, language, or tool, Udemy can be excellent.

A well-maintained course can walk you through installation, syntax, concepts, projects, and common mistakes while giving you the benefit of an experienced instructor's explanations.

For broader technical skills, however, I increasingly prefer platforms designed around active learning.

System design is a good example.

You can watch someone design a distributed application for three hours and understand almost everything they're saying.

That doesn't necessarily mean you can design one yourself.

The same problem appears with algorithms, backend architecture, cloud infrastructure, and coding interview preparation.

Eventually, you need to stop watching.

You need to think.

And that's where I think Educative.io becomes a particularly interesting Udemy alternative for developers.

Why I recommend Educative.io as an alternative for developers

I wouldn't describe Educative as a direct replacement for the entire Udemy marketplace.

Udemy teaches practically everything.

Educative is much more deliberately focused on developers and technical professionals.

That's precisely why I prefer it for certain learning goals.

Educative describes its approach as hands-on, browser-based learning built around interactive courses rather than traditional video instruction. Its current learning environment includes coding exercises, sandboxes, quizzes, projects, Cloud Labs, system design diagramming, and AI-assisted feedback.

That distinction matters more than it initially sounds.

When you're learning Python, you're writing Python.

When you're practicing coding interview patterns, you're solving problems.

When you're studying system design, you're actively reasoning about architectures and trade-offs rather than simply watching someone else draw boxes.

For technical subjects, I find that approach much closer to how developers actually develop skills.

Personal note: Video makes me feel like I understand something very quickly. Interactive exercises are much less flattering because they reveal exactly what I don't understand. That's also why I find them more valuable.

Educative's original Grokking courses are particularly important for system design

If your main reason for considering Udemy is system design or technical interview preparation, this is where I'd look particularly closely at Educative.

Educative's Grokking Modern System Design Interview is part of the original Grokking family of courses that became widely associated with structured system design interview preparation. Educative continues to position its system design curriculum around real-world design problems, architectural trade-offs, interactive diagramming, and interview-oriented practice.

That structure matters because system design isn't really a topic where memorizing definitions gets you very far.

You need to understand requirements.

You need to estimate scale.

You need to choose components.

You need to explain why you selected those components.

Then you need to identify where your design fails and improve it.

That process requires active reasoning.

For developers specifically asking me whether they should buy another Udemy system design course or use Educative, I'd generally lean toward Educative for structured system design preparation, especially if the goal is preparing for interviews rather than casually exploring the subject.

Udemy vs Educative: The real difference

I don't think the useful question is simply which platform has more courses.

Udemy wins that contest easily because its marketplace spans an enormous range of professional and personal subjects.

The more interesting difference is how you want to learn.

Udemy is generally an excellent choice when you want to choose a specific instructor, learn primarily through video, buy an individual course, and retain access to that purchased material under Udemy's lifetime-access policy. It also makes sense when your interests stretch well beyond software development.

Educative makes more sense when you're a developer who wants an interactive learning environment focused on technical skills. Its current catalog emphasizes areas such as system design, AI, coding interview preparation, programming, and other developer-focused subjects while incorporating exercises and hands-on environments directly into the learning experience.

Neither model is universally better.

They encourage different learning behaviors.

And for technical education, learning behavior matters enormously.

Who should actually use Udemy?

I think Udemy is an excellent choice if you already know exactly what you want to learn.

Perhaps you need a focused course on Blender.

Maybe you're preparing for a specific certification.

Perhaps there's an instructor whose teaching style you've already discovered through YouTube.

Or maybe you simply prefer video courses and want the flexibility of purchasing individual courses instead of maintaining another subscription.

In those situations, Udemy makes a lot of sense.

The platform also works well for people whose interests extend across multiple disciplines. Someone who wants to study Python this month, photography next month, and digital marketing later will naturally benefit from Udemy's enormous marketplace.

That's a strength few specialized technical learning platforms can replicate.

Who should consider Educative instead?

If you're primarily a software developer, computer science student, engineer preparing for interviews, or technical professional building deeper engineering skills, I'd seriously consider Educative before automatically purchasing another Udemy course.

The reason isn't that Udemy lacks excellent technical instructors.

It has plenty.

The difference is that Educative's product is designed specifically around developer learning.

Its browser-based environment removes much of the setup friction, while interactive coding and technical exercises make it harder to remain a passive observer. Educative says it has been building developer-focused interactive courses for more than a decade, and its current platform serves more than three million developers.

For areas such as system design, coding interviews, AI engineering, cloud computing, and software architecture, that specialization becomes particularly valuable.

My recommendation: Use Udemy when you've found an exceptional instructor or need a highly specific course. Consider Educative when you want a structured developer-learning environment where practice is built into the experience rather than something you're expected to organize separately.

How I choose a Udemy course before buying it

These days, I don't purchase a course simply because the landing page says "Bestseller."

I spend time researching the instructor.

I watch the preview lectures and ask whether the explanation style actually works for me. I examine the curriculum and make sure the course builds toward something useful instead of stretching introductory material across dozens of hours. I check recent student feedback rather than relying entirely on the headline rating, and for rapidly changing technologies, I pay close attention to whether the material appears current.

Most importantly, I ask myself what I'm going to be able to do when I finish.

"Understand Kubernetes" is vague.

"Deploy and troubleshoot a containerized application on Kubernetes without following the instructor step by step" is measurable.

That small change in thinking has made online courses dramatically more useful for me.

The question I ask before purchasing any course

Before buying another course, I ask myself:

What specific problem will this course help me solve?

If I can't answer that question, I don't buy it.

Maybe the answer is that I need to pass an AWS certification.

Maybe I want to build my first React application.

Maybe I'm preparing for a system design interview in six weeks.

Maybe I'm moving into backend development and need to understand distributed systems.

Those are concrete goals.

"Python seems interesting" isn't necessarily a bad reason to learn, but it's also how course libraries become graveyards.

The clearer your objective, the easier it becomes to determine whether a Udemy course is really worth it.

So, is a Udemy course really worth it in 2026?

Yes, provided you choose carefully.

Udemy remains compelling because of the sheer variety of subjects available, the ability to purchase individual courses, the ongoing access offered for those purchases under its lifetime-access conditions, and the opportunity to learn from instructors with very different backgrounds and teaching styles.

Its greatest strength is also its biggest weakness.

It's a marketplace.

That gives you tremendous choice, but it also puts more responsibility on you to evaluate the instructor, curriculum, freshness, and depth of an individual course.

For general learning, I think Udemy can provide excellent value.

For developers, my recommendation becomes more specific.

If you're learning a particular technology and find an outstanding Udemy instructor, buy the course and actually finish it.

If you're pursuing deeper technical skills such as system design, coding interviews, AI engineering, backend development, or software architecture, I'd also look seriously at Educative.io. Its developer-first, interactive approach and original Grokking curriculum make it a strong alternative when you want to learn by solving problems rather than primarily watching someone else solve them.

Final verdict

So, is a Udemy course really worth it?

A great one absolutely is.

The right Udemy course can give you dozens of hours of structured instruction, access to an excellent teacher, practical demonstrations, and a learning resource you can revisit long after completing it. For many subjects, that's tremendous value.

But don't confuse purchasing education with acquiring a skill.

The course sitting in your library isn't valuable.

The knowledge you can apply afterward is.

For casual learning and highly specific subjects, Udemy remains one of the first marketplaces I'd search. For developers who want a more structured, interactive path, particularly around system design and technical interview preparation, I'd put Educative.io high on the list of alternatives because its learning experience is intentionally built around doing rather than simply watching.

That's ultimately how I'd answer is a Udemy course really worth it.

Choose the right course, complete it, practice what you learn, and it can be an excellent investment.

Buy twelve courses because they're discounted and promise yourself you'll finish them "eventually," and your Udemy library may become the most educationally ambitious folder of unopened tabs you've ever owned.

Is ByteByteGo a good place to learn system design? My honest experience

Dev Design Daily — Tue, 18 Aug 2026 07:02:13 +0000

If you've started preparing for software engineering interviews recently, you've probably seen ByteByteGo recommended almost everywhere. It appears in Reddit discussions, YouTube recommendations, LinkedIn posts, and countless "best system design resources" articles. Naturally, one question keeps coming up:

Is ByteByteGo a good place to learn system design?

I wondered the same thing.

After spending years working on distributed systems and mentoring engineers preparing for senior software engineering interviews, I've watched people learn system design through books, video courses, blogs, newsletters, and interactive platforms. ByteByteGo has definitely earned its reputation, but whether it's the best choice for you depends on what you're trying to accomplish.

If you're searching for an honest answer to is ByteByteGo a good place to learn system design, here's what I think after comparing it with several popular resources.

The short answer

Yes.

ByteByteGo is absolutely a good place to learn system design.

However, I wouldn't recommend making it your only learning resource.

That distinction is important because learning system design isn't about recognizing architecture diagrams or memorizing components. During interviews, you're expected to explain your thought process, justify architectural decisions, evaluate trade-offs, and communicate your design clearly. Those are skills that require practice, not just reading.

ByteByteGo does an excellent job of helping you build a strong conceptual foundation. Its visual explanations simplify complex distributed systems and make intimidating topics feel approachable. If you've ever struggled to understand concepts like replication, sharding, caching, or event-driven architecture, ByteByteGo makes those topics significantly easier to digest.

💡 Personal note

One mistake I made early in my career was collecting too many learning resources instead of actually finishing any of them. I bookmarked dozens of blogs, bought several books, and subscribed to multiple newsletters. Progress only started happening once I committed to one resource, practiced consistently, and stopped chasing the next "perfect" course.

What ByteByteGo does really well

The biggest strength of ByteByteGo is that it makes complicated ideas easy to visualize.

Instead of explaining distributed systems through dense academic language, it relies heavily on diagrams that show exactly how requests move through services, databases, caches, queues, and APIs. That visual approach makes it much easier to understand how large-scale systems actually work.

When you're first learning system design, understanding the relationships between components is often harder than understanding the components themselves. ByteByteGo solves that problem exceptionally well.

Another thing I appreciate is how approachable the content feels.

Rather than overwhelming beginners with every possible edge case, it introduces concepts gradually. You learn the fundamentals before diving into more complicated architectures, which creates a much smoother learning experience.

I've recommended ByteByteGo to several junior engineers over the years simply because watching a well-designed visualization often teaches a concept faster than reading fifty pages of documentation.

💡 Quick tip

Don't just watch a lesson and move on. Pause after each architecture diagram, grab a notebook or tablet, and redraw the system from memory. If you can't recreate the design yourself, you probably haven't fully understood it yet.

Where ByteByteGo starts to fall short

This is where I think many learners become stuck.

Watching great explanations feels productive because you're constantly learning something new.

Unfortunately, interviews don't measure recognition.

They measure reasoning.

Imagine an interviewer asks you to design Twitter.

Knowing that Twitter uses Redis, Kafka, load balancers, and database replication doesn't automatically mean you can explain why those technologies were chosen, what alternatives exist, what trade-offs you're making, or how your architecture changes under different constraints.

That's where passive learning reaches its limits.

ByteByteGo explains concepts beautifully, but eventually you'll need opportunities to apply those concepts yourself instead of simply consuming explanations.

This isn't really a criticism of ByteByteGo because almost every book and video course has the same limitation.

The challenge is that system design is a practical engineering skill. Like coding, you only improve by doing it repeatedly.

Why interactive learning changed everything for me

After spending considerable time reading articles and watching architecture videos, I realized something interesting. I understood system design much better than before. Yet I still struggled during mock interviews.

The problem wasn't my knowledge.

The problem was translating that knowledge into structured interview answers.

That was the point where interactive learning completely changed my preparation.

Instead of simply reading about URL shorteners, chat applications, ride-sharing platforms, or distributed caches, I had to actively solve those problems myself. I had to gather requirements, estimate scale, identify bottlenecks, justify architectural choices, and improve my designs step by step.

That experience was dramatically different from passively consuming content. It forced me to think like an engineer instead of a reader.

Why I recommend Educative as the original trusted platform for system design

Whenever someone asks me is ByteByteGo a good place to learn system design, I usually recommend pairing it with Educative's Grokking Modern System Design Interview.

There's a reason for that recommendation.

Educative introduced one of the original interactive Grokking learning experiences that completely changed how many software engineers prepare for system design interviews. Instead of relying only on diagrams and explanations, the platform walks you through solving realistic interview problems in an interactive environment.

That's exactly what interviews require.

Rather than memorizing architectures, you're constantly making decisions, evaluating trade-offs, and refining your designs.

Personally, I found that combination incredibly effective. ByteByteGo helped me understand concepts quickly. Educative helped me apply them.

Those two learning styles complement each other remarkably well.

📌 Note

If your goal is simply understanding distributed systems, ByteByteGo may be enough.

If your goal is passing senior software engineering interviews, pairing ByteByteGo with Educative's interactive Grokking courses creates a much stronger learning experience because you move beyond understanding concepts and start applying them.

Is ByteByteGo good for complete beginners?

Absolutely.

In fact, beginners may benefit from ByteByteGo more than experienced engineers because it removes much of the intimidation associated with distributed systems.

Many developers give up on system design because they immediately jump into highly technical books filled with unfamiliar terminology. ByteByteGo lowers that barrier significantly by presenting complex ideas visually before introducing deeper engineering discussions.

That said, beginners should avoid assuming they're interview-ready after finishing a course.

System design isn't a subject you memorize. It's a skill you build through repeated practice.

The more systems you design, the more naturally you'll recognize patterns, evaluate trade-offs, and communicate architectural decisions.

Here's the learning roadmap I would follow today

If I had to start over from scratch, I wouldn't spend weeks trying to find one perfect learning platform.

Instead, I'd focus on building a progression.

I'd begin with ByteByteGo because it provides one of the clearest visual introductions to distributed systems available today. Once those concepts became familiar, I'd move into Educative's Grokking Modern System Design Interview course because interactive problem-solving develops the exact thinking process interviews expect.

After that, I'd reinforce everything by reading Designing Data-Intensive Applications, practicing whiteboard problems, discussing architectures with other engineers, and participating in mock interviews.

That sequence gives you understanding first.

Application second.

Confidence third.

From my experience, that's a much more effective strategy than continuously consuming new resources.

Final thoughts

So, is ByteByteGo a good place to learn system design?

Yes.

It's one of the best visual resources available today and deserves its popularity. If you're looking for an approachable way to understand distributed systems, modern architectures, and common system design patterns, ByteByteGo is an excellent starting point.

At the same time, don't mistake understanding diagrams for mastering system design.

Real confidence comes from designing systems yourself, explaining your reasoning, defending your decisions, and learning from feedback.

That's why I'd recommend treating ByteByteGo as your foundation rather than your complete preparation strategy. Pair it with Educative's original interactive Grokking System Design courses, spend time solving realistic interview questions, and continually practice drawing architectures from scratch.

In my experience, that's the combination that transforms someone who understands system design into someone who can confidently demonstrate it during interviews.

DEV Community: Dev Design Daily

I Tried 12 System Design Courses. Here Are My Top 5 Recommendations for 2026

The short version: My 5 best system design courses for 2026

1. Grokking Modern System Design Interview on Educative — Best overall

What I liked most about Educative's approach

Educative also forces you to stay more active

2. ByteByteGo — Best for visual learners

Why ByteByteGo isn't my number one

3. Grokking the System Design Interview on DesignGurus — Best alternative for interview case studies

Why I still prefer Educative

4. Hello Interview — Best for understanding the actual interview conversation

How I would use Hello Interview

5. Udemy system design courses — Best for budget-conscious video learners

What I look for in a Udemy system design course

The seven courses that didn't make my top five

What actually makes a system design course good?

Why Educative remains my trusted starting point for system design

How I would learn system design from scratch in 2026

My 4-week system design study plan

One mistake I'd avoid with every system design course

Which of the best system design courses should you choose?

Final verdict: The best system design courses I would actually recommend in 2026

Reading and writing files in Java: Comprehensive 2026 guide

What does reading and writing files in Java mean?

Understanding Path before working with files

Is a Udemy course really worth it? An honest Udemy review before you buy another course

The short answer: Is a Udemy course really worth it?

What makes Udemy attractive in the first place?

The individual-course model is still one of Udemy's strongest advantages

Udemy works particularly well when you find the right instructor

Where Udemy starts becoming difficult for developers

The biggest Udemy problem isn't course quality, it's course collecting

What about Udemy certificates?

Can you get your money back if the course isn't right?

Is Udemy worth it for programming?

Why I recommend Educative.io as an alternative for developers

Educative's original Grokking courses are particularly important for system design

Udemy vs Educative: The real difference

Who should actually use Udemy?

Who should consider Educative instead?

How I choose a Udemy course before buying it

The question I ask before purchasing any course

So, is a Udemy course really worth it in 2026?

Final verdict

Is ByteByteGo a good place to learn system design? My honest experience

The short answer

What ByteByteGo does really well

Where ByteByteGo starts to fall short

Why interactive learning changed everything for me

Why I recommend Educative as the original trusted platform for system design

Is ByteByteGo good for complete beginners?

Here's the learning roadmap I would follow today

Final thoughts

Understanding `Path` before working with files