DEV Community: Sailee Shingare

The OSI Model Explained: A Beginner's Guide to Network Layers

Sailee Shingare — Sat, 27 Jun 2026 05:28:46 +0000

The OSI Model sounds like something only network engineers need to know. But it's actually a simple framework that explains how data moves across the internet.

If you've ever wondered what happens when you click a link, the OSI Model is your answer.

What Is the OSI Model?

OSI stands for Open Systems Interconnection. It's a model that breaks down how computer networks work into 7 layers. Think of it like a stack of steps — data travels down the stack when you send something, and up the stack when you receive it.

Each layer has a specific job. Each layer depends on the layer below it.

Why care? Understanding these layers helps you troubleshoot network problems, understand security, and grasp how the internet actually works.

The 7 Layers (Top to Bottom)

Layer 7: Application

Where users interact. Email, web browsers, file transfers, chat apps — they all live here.

When you visit a website, your browser is operating at Layer 7.

Layer 6: Presentation

Formats the data for display. Encryption, compression, translation. Converts data into something readable.

Example: Your browser decrypts HTTPS data so you can read the webpage.

Layer 5: Session

Manages connections. Starts, maintains, and ends conversations between devices.

Example: When you log into email, this layer keeps your session alive while you're checking messages.

Layer 4: Transport

Reliable delivery. Decides how data gets from point A to point B. Uses protocols like TCP (reliable, slower) and UDP (fast, less reliable).

TCP: Email (important, must arrive)
UDP: Video streaming (fast matters more than perfection)

Layer 3: Network

Routing. Finds the best path for data across the internet. IP addresses live here (192.168.1.1).

This layer asks: "How do I get to that IP address?"

Layer 2: Data Link

Moves data between devices on the same network. MAC addresses live here (physical addresses, not IP).

Example: Your laptop connects to your WiFi router. Layer 2 handles that.

Layer 1: Physical

The actual wires, cables, radio waves. The hardware.

Example: Your Ethernet cable, WiFi signal, fiber optic cable.

How Data Flows

When you send an email:

Going down (your computer):

You write an email (Layer 7)
Browser encrypts it (Layer 6)
Session is maintained (Layer 5)
Email travels via TCP (Layer 4)
Routed to recipient's IP (Layer 3)
Converted to frames for the network (Layer 2)
Sent as electrical signals (Layer 1)

Going up (recipient's computer):
Same layers, reverse order. Data arrives as signals, reconstructed as frames, routed, transported, formatted, presented, and displayed in their email app.

Practical Examples

Why your WiFi is slow:
Could be Layer 1 (weak signal), Layer 2 (WiFi channel congestion), Layer 3 (bad routing), Layer 4 (too many connections), or Layer 7 (app issue).

Why HTTPS is secure:
Encryption happens at Layer 6. Your data is encrypted before it leaves, travels encrypted, and decrypts only at the destination.

Why ping tests troubleshooting:
Ping tests Layer 3 (routing) and Layer 4 (transport). If ping works but email doesn't, the problem is likely Layer 5, 6, or 7.

DNS (Domain Name System):
Sits between Layer 5 and Layer 7. Translates domain names (google.com) to IP addresses (142.250.185.46).

The Takeaway

The OSI Model is a mental framework. It helps you understand that the internet isn't magic — it's layers of systems, each doing a specific job, all working together.

You don't need to memorize all 7. Just remember: upper layers (5-7) handle data meaning. Middle layers (3-4) handle delivery. Lower layers (1-2) handle the physical transport.

Next time something doesn't work online, think OSI. It'll make troubleshooting easier.

Ever had a network problem? Share what layer it turned out to be. I'm curious what surprised you most about how networks actually work.

By Sailee Shingare | M.S. in Computer Science, Northern Illinois University

Machine Learning Explained for Beginners

Sailee Shingare — Wed, 24 Jun 2026 10:21:22 +0000

Machine Learning sounds complex, but it’s surprisingly simple: instead of coding rules, you teach computers to learn from data.

Traditional Code vs. Machine Learning

Traditional programming: Write explicit rules. “If email contains spam words, flag it.”

Machine Learning: Show examples. Feed the system 10,000 labeled emails (spam/not spam). Let it find patterns you might miss.

How It Works

Step 1: Training Feed the algorithm examples with known answers. A spam detector learns from thousands of labeled emails.

Step 2: Testing Test on new data it hasn’t seen. Does it still work?

Step 3: Predict Deploy it. New emails arrive, the model predicts.

The key: it learns patterns, not memorizes.

Three Types

Supervised Learning — You have labeled data (right answers). Email spam detection, house price prediction, medical diagnosis.

Unsupervised Learning — No labels. Find hidden patterns. Customer grouping, fraud detection, document clustering.

Reinforcement Learning — Learn by trial and error with rewards. Game AI, robot control, self-driving cars.

Key Concepts

Features: Inputs. For house prices: square footage, location, bedrooms.

Training Data: Examples the model learns from. More data usually helps, but quality beats quantity.

Overfitting: Model memorizes training data instead of learning patterns. Performs great on training data, fails on new data.

Accuracy: What percentage of predictions are correct? 95% accuracy sounds good until you realize context matters.

Real Examples

Netflix: Learns from what you watch. Recommends similar content.

Banks: Detect fraud by learning normal vs. suspicious transactions.

Doctors: ML models learn from thousands of X-rays to spot tumors.

Common Mistakes

Don’t use too little data. Don’t use dirty data. Don’t skip testing on separate data. Not every problem needs ML — sometimes a spreadsheet works better.

Getting Started

Learn the concepts (supervised vs. unsupervised)
Pick a tool (scikit-learn for Python, easiest)
Find beginner data (Iris flowers, Titanic dataset)
Build something simple (predict house prices)
Iterate (try more data, better features, different models)

ML vs. Gen AI

ML: Broad category. Learn patterns, make predictions.

Deep Learning: ML subset using neural networks.

Gen AI: Deep learning that generates new content (ChatGPT).

So Gen AI is ML, but not all ML is generative.

Why It Matters

ML powers recommendations, fraud detection, medical diagnosis, and thousands of apps. Understanding it helps you know when it’s actually useful vs. oversold.

By Sailee Shingare

Generative AI Explained: What It Is and Why It Matters

Sailee Shingare — Mon, 22 Jun 2026 23:40:39 +0000

ChatGPT, DALL-E, Copilot — you’ve probably heard the buzz. But what’s actually happening? Let me break it down simply.

What Is Gen AI?

Generative AI creates new content: text, images, code, videos. It doesn’t just retrieve data; it generates something original based on patterns it learned from massive amounts of training data.

The difference: Traditional software follows explicit rules. Gen AI learns patterns and makes educated guesses about what should come next.

Simple analogy: If a traditional AI is a librarian retrieving exact books, Gen AI is like a knowledgeable friend crafting an original answer based on everything they’ve read.

The Breakthrough

Large Language Models (LLMs) are the game-changer. ChatGPT, Claude, and similar tools are trained on enormous amounts of text from the internet and books. They don’t memorize facts; they learn patterns: what words usually follow each other, how sentences flow, what makes sense in context.

When you ask a question, the model predicts what text should come next, word by word. That’s it. But because the model is so large and trained on so much data, it produces surprisingly coherent, useful answers.

Key Things to Know

Prompts: Your instruction to Gen AI. “Write a haiku” is vague. “Write a haiku about coffee in a busy office” is specific and gets better results.

Hallucinations: Sometimes Gen AI confidently makes things up — fake studies, invented facts, plausible-sounding nonsense. It’s not lying; it’s just predicting text that should come next. Verify important information.

Knowledge cutoff: Most models have a date after which they don’t know what happened. ChatGPT, for example, knows events through April 2024 but nothing after.

Tokens: Text gets broken into chunks called tokens. You’re limited by token count — roughly 3,000 words per conversation in most tools.

Where It’s Useful

Content creation: Brainstorming, drafting, email templates
Learning: Explaining complex topics at any level
Code: Auto-completing code, suggesting functions (GitHub Copilot)
Customer support: Chatbots handling routine questions
Marketing: Generating descriptions, captions, campaign ideas

The Limitations

Hallucinates confidently
No real-time knowledge (can’t browse the internet)
Trained on internet text, so it reflects human bias
Gets worse the longer the output
It’s pattern-matching, not reasoning — can’t solve truly novel problems
Requires massive computational power

How to Use It Well

Be specific. Vague prompts = vague answers.
Iterate. Don’t accept the first answer; ask follow-ups.
Verify facts. Always check important information.
Use it for ideation. Great for brainstorming and breaking writer’s block; less ideal as your only tool.
Disclose AI use. Be transparent when you publish AI-assisted work.

Tools to Try

ChatGPT (OpenAI) — Text and code
Claude (Anthropic) — Text, often strong on reasoning
Google Gemini — Google’s alternative
DALL-E, Midjourney — Image generation
GitHub Copilot — Code-focused

Most offer free tiers.

The Real Story

Gen AI isn’t replacing workers; it’s changing jobs. Writers, developers, analysts — you’re not being automated away. You’re evolving. The skill now is knowing how to work with these tools effectively.

It’s like when spreadsheets arrived: they didn’t eliminate financial analysts. They made better ones.

Bottom Line

Generative AI is a powerful tool built on patterns and probability — not magic, not consciousness. It accelerates work, sparks creativity, and solves problems. But it’s not perfect, and it’s not a replacement for critical thinking.

Want to understand it? Play with it. Try ChatGPT for an hour. See where it helps you. Because the future isn’t AI vs. humans — it’s humans who know how to work with AI.

Tried Gen AI? What surprised you most? Let me know in the comments.

By Sailee Shingare | M.S in Computer Science, Northern Illinois University

HTTP vs HTTPS — What Actually Happens When You Visit a Website

Sailee Shingare — Tue, 16 Jun 2026 03:14:12 +0000

Every time you visit a website, your browser and the server have a conversation. That conversation happens over a protocol — either HTTP or HTTPS.

You’ve seen both in your browser’s address bar. But what’s actually different between them, and why does it matter?

Let’s break it down.

What is HTTP?

HTTP stands for HyperText Transfer Protocol. It’s the foundation of data communication on the web — the set of rules that defines how your browser requests information and how servers respond.

When you visit a website over HTTP, here’s what happens:

You type a URL in your browser
Your browser sends a request to the server
The server sends back the webpage
Your browser displays it

Simple. But there’s a problem — everything is sent in plain text. Anyone sitting between you and the server can read it. Your passwords, your credit card numbers, your messages — all visible.

This is where HTTPS comes in.

What is HTTPS?

HTTPS stands for HyperText Transfer Protocol Secure. It’s HTTP with an extra layer of security called TLS (Transport Layer Security) — previously known as SSL.

The S in HTTPS means everything between your browser and the server is encrypted. Even if someone intercepts the data, they see nothing but scrambled gibberish.

What Actually Happens When You Visit an HTTPS Website

When you visit an HTTPS site, your browser and the server perform a TLS Handshake before any data is exchanged. Here’s what happens step by step:

Step 1 — Client Hello Your browser says hello to the server and shares which encryption methods it supports.

Step 2 — Server Hello The server picks an encryption method and sends back its SSL certificate — a digital document that proves the server is who it claims to be.

Step 3 — Certificate Verification Your browser checks the certificate against a list of trusted authorities. If it’s valid, the connection proceeds. If not, you see a warning — “Your connection is not private.”

Step 4 — Key Exchange Your browser and the server agree on a secret key used to encrypt the session. This key is never sent over the internet — both sides calculate it independently.

Step 5 — Encrypted Communication Begins From this point on, everything is encrypted. Your data is safe.

This entire handshake happens in milliseconds — you never notice it.

Why Does Google Prefer HTTPS?
Since 2014, Google has used HTTPS as a ranking signal. Websites using HTTPS rank higher in search results than HTTP equivalents.

Additionally, since 2018, Google Chrome marks all HTTP sites as “Not Secure” in the address bar. This immediately reduces user trust and increases bounce rates.

If you run a website, HTTPS is no longer optional — it’s essential.

What is an SSL Certificate?

An SSL certificate is a digital document issued by a trusted Certificate Authority (CA) like Let’s Encrypt, DigiCert, or Comodo. It contains:

The website’s domain name
The certificate’s expiration date
The public key used for encryption
The CA’s digital signature

When your browser sees a valid certificate from a trusted CA, it displays the padlock icon. When the certificate is missing, expired, or from an untrusted source — you get a security warning.

Getting HTTPS for Free

You don’t need to pay for HTTPS anymore. Let’s Encrypt is a free, automated Certificate Authority trusted by all major browsers.

Most hosting providers — AWS, Azure, Cloudflare, Netlify — offer free SSL certificates with one-click setup. There’s no excuse for running an HTTP website in 2024.

The Bottom Line

HTTP = fast but insecure, data sent in plain text
HTTPS = secure, encrypted, trusted by browsers and Google
The TLS handshake happens in milliseconds and protects everything you send
Always look for the padlock before entering passwords or payment details

If you run a website, use HTTPS — it’s free and essential
Next time you see that padlock in your browser, you’ll know exactly what’s happening behind the scenes.

By Sailee Shingare | M.S in Computer Science, Northern Illinois University