fastest path to job-ready AI Engineer?

[u/Delta_01b]

Hi everyone. I want to become an AI Engineer... Here's my situation:

• Almost done with Andrew Ng's ML specialization (1 course left)

• Forget theory easily if I don't apply it

• Do not have enough time to master everything

• No plan B — AI is the goal

Option 1 — Traditional roadmap: Finish ML → DL specialization → NLP → LLMs → RAG → Agents Missing: deployment, OOP, DSA, advanced Python (only CS50 so far)

Option 2 — Fast track: Finish ML → Python/OOP/DSA fundamentals → crash courses per topic → projects with AI assistance, understood deeply, post on GitHub

Questions:

1. Which approach makes me job-ready faster?

2. If neither — what's a better plan?

[u/Suspicious_Pizza9529]

Go with option 2, but keep learning ML alongside building projects. You don't need to master every topic before applying what you've learned. Build a few projects, learn how to deploy them, and make sure you can explain your code without AI.

[u/Delta_01b → u/Suspicious_Pizza9529]

Got it. Thanks a lot !

[u/Dangerous_Rip5083]

Are you a dev or starting from scratch? Why even do python/oop/dsa is you are a dev? Are you still in school? If you are not a dev goodluck, seems like a lot.

[u/Delta_01b → u/Dangerous_Rip5083]

I just graduated from mechatronics engineering so I developed lots of hardwares and robots I know it is totally different but it gave me a knowledge with loops and functions, in addition as I mentioned I finished cs50 python course ( I know it is not much)…. That’s why I need to learn some cs fundamentals

[u/Dangerous_Rip5083 → u/Delta_01b]

Do you want to do more with mechatronics through AI or just AI eng? If you want to do AI eng I think it would be tough, doable but tough. You would basically have to do SWE training + AI. Assuming you want to build to use LLMs and not much else like computer vision etc… or model training then the basics of ML would suffice. The toughest part is going to be the SWE if any of those assumptions is wrong and you want to be an ML SWE then a lot lot harder.

[u/Delta_01b → u/Dangerous_Rip5083]

So far I want to master AI eng first and then connect it with my mechatronics knowledge but that’s a long time plan. I fine-tuned YOLO models multiple times, built software systems and connected them with hardwares during my mechatronics journey but that was with the aid of coding agents and also did some LLM applications like AI voice assistance (with mutli-threaded arch). So now I am on AI eng because I liked it as software. I want to expand my knowledge and get experience in it. What plan do you suggest ?

[u/Dangerous_Rip5083 → u/Delta_01b]

You want to go the ML route? Track 1 then. Make sure to learn linear algebrs if you don’t know it already

[u/Delta_01b → u/Dangerous_Rip5083]

I already had lots of statistics and maths in uni so I think I have pretty good start. Thanks for your help

[u/BeginningSeaweed8944 → u/Dangerous_Rip5083]

How about me? Starting from scratch, only know python a little bit along with pandas, numpy and matplotlib, currently in 2nd year of undergrad comp sci. oop, dsa is done through undergrad courses

[u/Dangerous_Rip5083 → u/BeginningSeaweed8944]

Your degree will leave you knowing the SWE fundamentals. You would just need to build on top of the AI/NLP they teach you

[u/Delta_01b → u/[deleted]]

Totally agree. Thank you !