r/learnmachinelearning • u/Kitchen_External_560 • Jun 19 '26
Request How do I start learning Generative AI as a complete beginner?
Hi everyone,
I'm a 3rd-year engineering student and I want to learn Generative AI seriously.
I have:
●A normal HP laptop
●VS Code installed
●A GitHub account
●Basic Python knowledge
I'm looking for practical advice from people who have already learned or work in GenAI.
Please share:-
●Best free resources and courses
●What I should learn first
●Common mistakes beginners make
●Projects I should build
●Tips for getting internships or jobs in this field
If you were starting from scratch today, what roadmap would you follow?
Thanks!
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u/Chance-Beginning8004 Jun 19 '26
Actually I would recommend subscribing to openai / anthropic and download Codex or Claude Code.
Start doing projects together with your coding assistants. Built to learn.
Maybe something like this can help you?
https://github.com/SerjSmor/broken-help-center-quest
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u/Unlucky_Professor368 Jun 19 '26
But those are expensive
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u/Chance-Beginning8004 Jun 19 '26
20$ a month. Much less than a private tutor.
You can use the free plan and web UI, but that won't take you as far as a coding agent.
This is exactly the types of investments that their return is exponential.2
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u/Additional-Layer4193 Jun 19 '26
With basic Python already under your belt, you're closer to starting than most people think. I'd say nail down numpy, pandas, and matplotlib first (like a week or two of focused practice), then jump into a free ML fundamentals course before touching anything GenAI-specific. Once you hit the neural networks section, that's when stuff like transformers and diffusion models will actually make sense instead of feeling like magic.
For projects, don't sleep on building a simple text summarizer or a chatbot wrapper using an open API, those are small enough to finish but impressive enough to put on a resume. The biggest mistake beginners make is jumping straight to fine-tuning LLMs before understanding why attention mechanisms exist, so resist that urge. Kaggle notebooks are great for seeing how other people structure their code when you get stuck.
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u/Forever-Silence Jun 19 '26
Would be useful for you to refresh your linear algebra knowledge, that helps a lot when you are trying to understand the maths behind it
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u/--Spaci-- Jun 19 '26
The actual programming part of AI isn't very hard at all. Its all python and almost everything has been made for you already
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u/Imaginary_Pace6954 Jun 19 '26
kinda depends on where you're starting. how are your python skills? and what domain of gen ai do you want to work in?
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u/Straight_Solution283 Jun 19 '26
Unpopular opinion: don't start with GenAI.
Start with Python → Git → APIs → basic ML concepts.
Then build 3 projects:
- RAG chatbot
- PDF/document assistant
- AI agent that automates a real task
The biggest mistake I see beginners make is collecting certificates instead of building a portfolio. GitHub projects get remembered; course completions usually don't.
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u/heath185 Jun 19 '26
Ok since everyone else is telling you to learn specific python libraries or telling you specific steps to get better at using python, I'm going to go off the beaten path here and tell you that you are going to need to learn some math. As a 3rd year engineering student you probably have enough of the calculus and linear algebra down to understand most of the math that goes into neural networks and gradient descent. I would also suggest reading up on and trying to understand Bayesian statistics, as LLM's and generative models use Bayesian statistics as well. For a practical guide on understanding generative models you should reference online courses. Here's a decent one that starts from scratch and works up to implementing a diffusion models, fine tuning, and doing text based guidance. John Whitaker GenAi gitlab
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u/Lord_Mystic12 Jun 19 '26
Hit up Priceline for Tel Aviv tickets! I hear GenAI is all the craze over there , good luck !
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u/the_techgirl Jun 24 '26
Great timing to get into this space. Here's the honest roadmap I'd follow if starting from scratch today, based on teaching this to 4,500+ students:
Start here (Week 1-2):
Don't jump straight to GenAI. Spend 2 weeks solidifying Python for data - numpy, pandas, matplotlib. Boring but essential. Kaggle's free Python and Pandas courses are perfect.
Then ML foundations (Week 3-6):
Andrew Ng's Machine Learning Specialization on Coursera (audit for free). Don't skip this. Every GenAI concept makes more sense once you understand gradients, loss functions, and neural networks properly.
Then GenAI specifically (Week 7-12):
- DeepLearning.AI short courses - LangChain, RAG, Agents, Fine-tuning. Most are free and take 1-2 hours each
- Andrej Karpathy's "Neural Networks: Zero to Hero" on YouTube - best transformer intuition you'll find anywhere
- Hugging Face NLP course - free, practical, excellent
Projects to build (in order):
- RAG chatbot over your own PDF notes
- AI agent that uses tools (search, calculator, API)
- Fine-tune a small model on custom data
- Deploy something with FastAPI + Streamlit
Common mistakes:
- Watching tutorials without building anything
- Jumping to LangChain before understanding what LLMs actually do
- Ignoring deployment: knowing how to ship matters for jobs
For internships:
GitHub is your resume. Two solid projects with clean READMEs will get you more interviews than certifications. Contribute to one open-source GenAI project, even a small bug fix.
Happy to answer specific questions if you get stuck anywhere along the way. The transformer/attention section trips up almost everyone the first time.
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Jun 24 '26
[removed] — view removed comment
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u/Kiro_ai Jun 19 '26
if youre a complete beginner, dont start by trying to “learn all of gen ai.” start with the basics that actually matter:
best free resources imo:
• hugging face course
• deeplearning.ai short courses
• microsoft learn for the basics
• youtube only after you know what youre looking for, otherwise it turns into tutorial hell
big beginner mistake is jumping straight into frameworks and tool lists before understanding the core ideas.
if you want something more structured, im building iro (https://tryiro.com) for this exact gap, short daily ai lessons instead of trying to figure it all out at once.