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Strategies for learning a new programming language.

theDevnotes — Sun, 22 Nov 2020 18:58:06 +0000

Hello World, welcome to Dev Terminology, where we talk about dev concepts.

Today’s topic — Strategies for learning a new programming language.

Note: some of these techniques may work for you, and some may not. If you get stuck or notice that these strategies aren’t working, then pivot. Try other strategies to find what works best for you.

Learning a new language is like learning a new way of thinking.

Strategies for learning a new programming language — The Gist … Practice

Choose your programming language.
Read the Docs and go through the doc tutorial page.
Practice with coding interview problems.
Get started on a small project.
Engage with the community for support.
Dive deeper.

Remember that everybody learns differently, and regardless of your background, you are not alone. Learning to program is a never-ending struggle.

Learning anything requires time, patience, and practice.

Strategies for learning a new programming language — Overview

Choose your programming language.

At this point, I’m going to assume you understand the fundamentals of programming; if not, take a moment to learn them. It’s important to have that foundation.

Programming Fundamentals

Once you’ve got your foundation — choose a language that you want to learn.

Read the Docs and go through the doc tutorial page.

Reading docs can be a real snoozer, so remember that reference docs are generally written to be searched through rather than memorized — so don’t read it like a novel.

Skim through the table of context
Jot down some notes on:

Things that look familiar, and look the way you expected them to.

Things that look familiar, but do something unexpected.

Things that look totally new.

Read about the language and find the differences. Ask yourself questions like, is this language statically typed or dynamically typed? Is it compiled or interpreted? Jot down the paradigm you’ve never seen before.

Now go through the getting started tutorial to get set up.

Print Hello World!

Practice with coding interview problems.

You might be wondering — Why coding interview problems?

Gist — To help you build pattern recognition.

Coding interview problems are preset problems that allow you to focus on a specific idea at a time. Unlike small projects, coding interview problems are a bit more straight forward — you get a question, you give an answer. Solve a problem, then move on.

So how many problems should you do?

50, 100 + maybe? Honestly, it’s really up to you. Do enough to cover the foundational blocks — a set variety of different kinds of problems (i.e., Variables, Loops, Conditional statements, Functions, Data structures, Classes, etc…)

As you go through these problems and encounter something you don’t know how to do — look it up. Call your friend Google to help you out.

While you are solving these problems, consider coding by hand. — Build that muscle memory.

Don’t forget — The Goal of this is to gain a foundational understanding, and it may expose the gaps in your knowledge. Make sure to keep track of what you don’t know so that you can revisit it later.

Where to find coding interview problems

Get started on a small project.

Maybe consider having a toy project that you can implement repeatedly in whatever language you are learning so that you can see the differences between how each language you’ve learned goes about doing the same thing.

Focus on getting your code as clean and idiomatic as possible.

Template projects:

Project Euler
Rosetta Code puzzle
With template projects, you can often compare your solution to those written by others in the same language. Take note of the differences and ask yourself what can you improve on.

Engage with the community for support.

Get your projects code reviewed.

If you need more help, find tutorials, crash courses, articles, books, and/or a mentor.

Dive deeper.

Write production-ready code in the language. Use the language in a more realistic setting to help you explore its real-life advantages and challenges.

Read and test out lots of code — example code and production code.

Practice, Practice, Practice.

Maintain your enthusiasm.

Final note — Once you’ve learned it, teach it in simple terms (see it, write it, speak it, repeat).

This was Dev Terminology. Thanks for reading.

Credits and acknowledgment to the dev community.

Written by Jessica Dosseh

Find Jessica on: [GitHub, LinkedIn, Twitter, Patreon, and Portfolio]

Find theDevnotes on: [GitHub, Twitter, Blog, Medium, Dev.to]

P.S: [Dear reader — visit again sometime :)]

Programming Fundamentals

theDevnotes — Sat, 21 Nov 2020 14:30:29 +0000

Hello World, welcome to Dev Terminology, where we talk about dev concepts.

Today’s topic — Programming Fundamentals; the basic concepts of any programming language.

When learning to code programming fundamentals always need to come first. The more you understand them, the easier it is to build upon it and learn advanced concepts.

The Fundamentals of Programming:

Data Types and Variables
Operators
Control Structures
Data Structures
Syntax
Tools

These Programming Fundamentals — Do Or Complete Different Solutions Together.

It's kind of a cheesy line, but I hope you get my drift.

"It's important to remember that a lot of programming languages are very similar, and knowing what's common between all programming languages will help you transition into any other programming language if you need to!" (Trevor Page).

You can call them building blocks, a road map, blueprints, tools even, but regardless of the name, they are a foundation. The fundamentals tell you where we came from, where we've been, and where we're going. They need to be similar across programming languages because it's that similarity that allows each of us, to some extent, to understand them regardless of what language we speak or interact with. It's what allows us to communicate.

Programming Fundamentals Overview

Data Types and Variables

Data Types are the identity of a variable — an attribute of data which tells the compiler or interpreter how the programmer intends to use the data.

Types of data types:

Boolean, Integer, Float, Character, String,
Nothing Data Types, [Array *], etc ...

Note: know how to convert one data type into another (Data type conversion).

Variables are value placeholders — an element, feature, or factor that is liable to vary or change.

my_name = "Jane"

In this case, my_name holds the value of Jane.

Operators

Operators are symbols that tell you what to do. You know like + - = ...

Common operator types include:

arithmetic, comparison, and logical operators.

Control Structures

Control Structures are used to make decisions on what actions to take — the types of instructions the program should follow.

Types of Control Structures:

Decision control, Selection control, 
and Repetition / Loop control.

These control structures may be better known as:

Functions, Collections, Objects, Classes, 
Loops, Conditional / If Else statements etc...

Data Structures

Data Structures are ways to manage, organize and access data.

Some general data structures are:

Arrays, Linked Lists, Queues, Stacks, Hash Tables, 
Trees, Graphs, Heaps, Matrix, etc...

Syntax

Syntax is the way you order your words. — The rules, principles, and processes that govern the structure of sentences in a given language.

print("Hello World!")

In this case, this sentence structure is python syntax that when executed will print Hello World!

Programming Tools

Hardware with an operating system — A computer (preferably accompanied by a keyboard and mouse).

macOS, Windows, Linux, Other

Some sort of internet connection — WIFI

A terminal — The command line

Terminal command line cheat sheet

Some software — Your language's software developer kit (SDK)

This is where you click the big download button and let it do its magic
Example: Python SDK

A code editor, IDE, and/or whiteboard if you prefer

VSCode, Vim, Sublime Text, Whiteboards ... pen and paper?

Version control — Your remote repositories (where you store your code)

Git, Github

Git cheat sheet

Project management tools

Linter, Debugger

Github project boards, Trello

CI/CD — continuous integration / continuous delivery

For more information consider going to your local google or other browser if you're alternative.

Final note — When you start your developer journey

Go slow

Understand the fundamentals

This was Dev Terminology. Thanks for reading.

Credits and acknowledgment to the dev community.

Written by Jessica Dosseh

Find Jessica on: [GitHub, LinkedIn, Twitter, Patreon, and Portfolio]

Find theDevnotes on: [GitHub, Twitter, Blog, Medium, Dev.to]

P.S: [Dear reader — visit again sometime :)]

What Is Computer Science

theDevnotes — Thu, 19 Nov 2020 01:18:02 +0000

Hello World, welcome to Dev Terminology, where we talk about dev concepts.

Today’s topic — What is Computer Science.

Computer Science could be defined as the study of computers and computational systems with a focus on theory, design, development, and applications.

Computers were originally built to solve mathematical problems (arithmetics), but now it’s used to expand our brains, beings, and humanity even.

Based on Moore’s law it was said that the computational capabilities of computers would double every two years as their physical size continues to get smaller and smaller.

Computer science is usually seen as something extremely complicated, but in a sense it boils down to just flipping between 0’s and 1’s, yet this simplicity is what makes it possible to create a whirlwind of complexity from running the entire internet, creating artificial brains, or even simulating the universe.

Computer science — the study of what computers can do.

The fundamentals of computer science can be broken down into three parts

Theory
Engineering
Applications

The field of computer science is so vast.

There are so many questions, so many different approaches to reaching the same and/or different answers. No wonder computer science can be so intimidating; nevertheless, it’s an art form.

Just like music, or even traditional art, it takes an understanding and an ability to translate your creative ideas into logical instructions.

So should you learn computer science?

I say YES, not necessarily to work in the field (nevertheless, you can if you’d like), but rather to gain an in-depth understanding of creation and problem solving to help you do the things you want to do.

If you have the slightest bit of curiosity, go for it.

So how do you get started?

Join the community — find your people. Whether it’s the tech communities online (on Twitter, Discord, Reddit, etc…), Diversity Tech, or even Women in Tech — You are bound to find your people, and if not, start a community.
It’s important to learn the fundamentals. — Taste all the different flavors. See what’s out there, see what you like. We are all unique, and that’s a good thing.
Choose your language(s) and jump in. Get started. It’s never too late.
It’s okay to make mistakes and to change your mind. You are free to create your own road map, learn the way you need to learn, or quit even — There is no shame in choosing your own path.

Final note — When it comes down to it, It’s really all about practice.

This was Dev Terminology. Thanks for reading.

Credits and acknowledgment to the dev community.

Written by Jessica Dosseh

Find Jessica on: [GitHub,LinkedIn, Twitter, Patreon, and Portfolio]

Find theDevnotes on: [GitHub, Twitter, Blog, Medium, Dev.to]

P.S: [Dear reader — visit again sometime :)]