# Generative AI Full Course (Free)

URL: https://aiseason.tech/generative-ai-course

A free generative AI full course you can follow on your own: what generative AI is, then a module-by-module syllabus from LLM basics to RAG, agents and deployment — each module with free material, a project and a checkpoint. Built for students in Pakistan and India with basic Python.

| Fact | Value |
| --- | --- |
| Cost | Free — open-source code, free guides and free API tiers |
| You need | Basic Python and a laptop; no GPU and no machine-learning background |
| Modules | 8, from LLM APIs to deployed agents |
| Time | About 8–12 weeks part-time |
| Ends with | A portfolio of working generative AI projects on GitHub |

### What is generative AI?

**Generative AI** is AI that creates new content — text, code, images, audio or video — instead of only classifying or predicting. Large language models (LLMs) such as GPT, Claude, Gemini and Llama generate text and code; diffusion models generate images. You use generative AI every time you ask a chatbot to write, summarise or explain something.

**Agentic AI** is the next step: generative models that plan and take actions with tools to reach a goal. This course covers both, because most real generative AI jobs now involve building agents. For the difference in depth, read [what agentic AI is](https://aiseason.tech/what-is-agentic-ai).

### The free generative AI syllabus

| Module | What you learn | Free material |
| --- | --- | --- |
| 1. How LLMs work | Tokens, context windows, temperature, why models hallucinate | [AI agents glossary](https://aiseason.tech/ai-agents-glossary) |
| 2. Calling an LLM from code | APIs, streaming, chat history, errors and cost | [Session 1 code](https://github.com/AbdulRahmanAzam/AI-Season-Course-Material/tree/main/Session%201) |
| 3. Prompt engineering | System prompts, few-shot examples, structured JSON output | [Prompt engineering guide](https://aiseason.tech/prompt-engineering) |
| 4. RAG over your own documents | Chunking, embeddings, vector databases, citations | [RAG guide](https://aiseason.tech/rag-ai-agents) · [Session 3 code](https://github.com/AbdulRahmanAzam/AI-Season-Course-Material/tree/main/session%203) |
| 5. Tool calling and AI agents | The agent loop, tools, guardrails | [Build an AI agent](https://aiseason.tech/how-to-build-an-ai-agent) · [Session 4 code](https://github.com/AbdulRahmanAzam/AI-Season-Course-Material/tree/main/Session%204) |
| 6. Frameworks | LangChain, LangGraph and no-code tools | [LangChain tutorial](https://aiseason.tech/langchain-tutorial) · [n8n AI agents](https://aiseason.tech/n8n-ai-agent) |
| 7. Multimodal and MCP | Images and audio as inputs; connecting tools through MCP | [Session 5 code](https://github.com/AbdulRahmanAzam/AI-Season-Course-Material/tree/main/session%205) · [MCP guide](https://aiseason.tech/mcp-course) |
| 8. Production | Evaluation, self-correction, deployment and monitoring | [Session 8 code](https://github.com/AbdulRahmanAzam/AI-Season-Course-Material/tree/main/session%208) |

> Want to see what is inside a language model? The optional ARGPT module in the [free course material](https://aiseason.tech/free-ai-agents-course) trains a small language model from scratch.

### A project for every module

1. A command-line chatbot with streaming and a switchable system prompt.
2. A CV or invoice extractor that returns validated JSON.
3. A question-answering bot over your university handbook that cites its sources.
4. A tool-using agent — currency, weather or your own API.
5. The same agent rebuilt in LangChain, plus an n8n version for comparison.
6. An agent that reads an image or a PDF and acts on it.
7. An evaluation suite of 30 test questions for your RAG bot.
8. One project deployed to a public URL that a friend can use.

Put each project on GitHub with a short README explaining what it does and how you tested it. Eight small, working projects impress employers and clients far more than a certificate.

### How to study it for free

- **Models** — use a provider's free tier or run a small local model; you do not need a paid plan to learn.
- **Schedule** — one module every 1–2 weeks, with the project finished before moving on.
- **Order** — follow the modules in order; RAG and agents are much easier once prompting and APIs are solid.
- **Stuck?** — read the error, check the model and key, and compare with the reference code before searching for a new tutorial.

For the complete learning path beyond generative AI, see [how to learn AI](https://aiseason.tech/learn-ai) and the [AI agents roadmap](https://aiseason.tech/ai-agents-learning-roadmap).

### Free course vs a live cohort

Self-study works if you are disciplined. What it cannot give you is live help when your code breaks, deadlines, and feedback on your projects. The [AI Season bootcamp](https://aiseason.tech/) teaches this syllabus live — 12 sessions over 6 weeks, explained in Urdu, coded in English — for PKR 3,000 early-bird, with a full refund for the top 3 scorers. Cohort 02 starts 1st January 2027.

### Frequently asked questions

**Can I learn generative AI for free?**
Yes. With basic Python you can follow a free syllabus using open-source course code, free guides and free model tiers, and build a portfolio of projects without paying for a course.

**What is the difference between generative AI and agentic AI?**
Generative AI creates content such as text, code and images. Agentic AI uses generative models to plan and take actions with tools towards a goal. Agents are built on top of generative models, so you learn generative AI first.

**How long does it take to learn generative AI?**
About 8–12 weeks of steady part-time study to finish this syllabus with basic Python, or 6 weeks in a structured live bootcamp.

**Do I need maths or machine learning for generative AI?**
No, not to build applications. Building with LLMs is mostly programming, prompting, retrieval, tool design and evaluation. Maths matters if you want to research or train models.

**Is there a generative AI course in Urdu or Hindi?**
AI Season teaches generative AI and AI agents live in Urdu and English, easy to follow for Hindi speakers, with all code in English.

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_Last updated: 2026-09-27. Canonical page: https://aiseason.tech/generative-ai-course. Source: AI Season (https://aiseason.tech/)._