Curated learning library
Guides, templates, and reading lists for engineering journeys — filtering signal from noise.
Showing 19 resources
AI Trends 2026 India: 5 Shifts Driving ROI
AI trends 2026 for Indian businesses: agentic AI, small language models, EU AI Act rules and a playbook to get real ROI.
AI Photo: How Artificial Intelligence Creates and Edits Images
What an AI photo is, how text-to-image generation works, and why the LLMs, RAG and agents behind it are where the real engineering starts.
Generative AI Roadmap for Beginners
A learning roadmap for generative AI that starts with what the technology actually is, moves through prompting and retrieval, and ends at evaluation and deployment — with the prerequisites stated up front.
Agentic AI Roadmap: From Zero to Production
A staged roadmap for learning agentic AI: what to build at each level, the skills each stage assumes, and the mistakes people make when they skip the boring parts of agent tooling.
What Is MCP? Model Context Protocol Explained
MCP is an open standard that gives AI assistants a common way to reach tools and data. What problem it solves, how the three layers fit together, and where it sits relative to ordinary API integration.
How to Become an AI Engineer: 90-Day Roadmap
A week-by-week 90-day roadmap from programming basics to your first deployed AI project — Python, ML fundamentals, LLMs, RAG, and a portfolio you can defend.
AI Engineer Roadmap for Engineering Students
A semester-by-semester AI engineer roadmap for Indian engineering students — foundations, models, agents, and placements — without switching streams.
How to Choose Your First Engineering Track
A practical framework for 2nd-year students choosing between software, AI, and core engineering — questions that separate genuine interest from prestige.
Build Your First AI Agent in an Afternoon
Build your first AI agent in an afternoon — a working agent needs tools, a loop, and clear boundaries, and here is the simplest possible version to start.
RAG vs Fine-Tuning: A Clear Decision Guide
RAG vs fine-tuning — both improve a model in different ways. A clear decision guide on when to retrieve and answer, and when to adjust the model.
How to Learn LLM Engineering with a Timeline
A month-by-month timeline for learning LLM engineering from tokenization to fine-tuning, with evaluation and context engineering keeping you building.
What Is RAG? Retrieval-Augmented Generation
Retrieval-augmented generation lets LLMs ground answers in the documents you own. Understand the index, retrieve, and generate pipeline behind RAG apps.
Prompt Engineering 101: Getting Useful Answers from AI
Role, context, constraints, and examples — four prompt engineering levers that dramatically improve AI output, with a clear before and after example.
What Is Agentic AI? And How to Learn It
A hands-on path to learning Agentic AI without getting lost — understand the loop, build small first, then add memory and tools one step at a time.
What Is an LLM? How ChatGPT Actually Works
Tokens, attention, and next-word prediction explained in plain language — a friendly walkthrough of how large language models like ChatGPT really work.
AI Agent vs Chatbot: What Actually Changes
Agentic AI vs chatbots — when a question becomes a task, the product changes. See the real differences in tools, loops, grounding, and trust, in plain terms.
Machine Learning Basics: What a Model Actually Does
Training, features, and predictions made simple — the mental model every AI student needs, from supervised learning to inference, in plain language.
What Is an AI Agent? Loops, Tools and Examples
The core mental model behind AI agents — tools, memory, and a decide-act loop — explained with simple examples so you can spot a real agent when you see one.
What Is AI? A Beginner's Map of the Landscape
A beginner-friendly map of AI, machine learning, and generative AI — what each term means, how they connect, and why every engineering student needs them.
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Every resource here is practical, current, and free to use — designed to turn reading into real progress.