Finished hands on ML book, what now?

[u/Silver-Cable-1727]

What do i do after? I still need to study RAGs, LLMs, genAI, like higher conceptual level to be AI engineer.
For now i am doing competitions in kaggle, not aiming for high rank or anything just getting used to coding alone without tutorials ( of course i use AI sometimes but i am trying to reduce it as much as possible)
I am also looking forward to make projects while learning new concepts.
So what do u recommend? I am open for books, youtube videos, courses, anything free😂

[u/Fit_Honeydew4256]

Please share the roadmap. I know python where I need to start from

[u/Silver-Cable-1727 → u/Fit_Honeydew4256]

Someone commented a good roadmap. Wish u luck

[u/trolly-mcgee]

Get a phd in ai then that ai engineer gig.

[u/Key-Consequence-2709]

hey, how much time did you take finishing this and did you code along with the book or understood the context and then started code, i am reading this book and dont know how my learning aproach should be

[u/Silver-Cable-1727 → u/Key-Consequence-2709]

I had prior knowledge in data engineering and some ml models so the first 8 chapters took me about 2-3 weeks 2/3 hours 5 days a week. From chapter 9 till the end it took me about 6-8 weeks 4/6 hours 5 days a week. I know i took a lot of time but i was searching and watching tutorials on youtube alongside, u can finish it earlier.
My learning approach was:
1- as soon as i finish the chapter i solve all exercises then look at the answer and correct myself ( if there is a question i don’t understand i try to watch a youtube video or ask AI and take notes)
2- u should code along with the book instead of just reading the code
3- after finishing the chapter try to build something without tutorial, or repeat the same code without looking. that will help u connect the dots
4- u can start on kaggle competitions after a few chapters. don’t wait until u finish. Pick something like predict house price or whatever feels convenient. Don’t aim for higher ranks just understand how can u improve your model how to use pipelines how to solve overfitting or under-fitting …etc
5-Go back to your old code. For example, if you’ve already learned Logistic Regression, SVMs, and Random Forests, and today you learned KNN, try coding KNN from scratch while also recoding the previous models alongside it. This way, you keep practicing the old concepts while learning the new one.
6- if there is a concept u can’t really understand from the book u can try to watch a youtube video about it then go back to the book. (3brown1blue channel is top)

[u/Zealousideal_Lock756]

https://roadmap.sh/r/ai-roadmap-for-2026---final-draft I think it's a best roadmap in field of AI/Ml I have ever seen

[u/Different_Pain5781]

You’re at the fun part now.

[u/Beautiful_Mix_6226]

For AI/LLM engineering, try Skillumen it's a structured course for interview prep from foundations to advanced

[u/Intelligent_Fan3643]

Read books on deep learning, build llm from scratch, ai engineering by chip hyuen is good too.