I want to start learning ai/ml and get into this field.
Im planning to first take up the machine learning specialization course and then gen ai/nlp roadmap on deeplearning.ai website.
Is it advisable? Any changes you experts would suggest?
Hello @baddu!
Yes the Machine Learning Specialization is a very good point to start.
You could then continue with the Deep Learning Specialization or one of the two other you mentioned. Generally, it also depends on what your goals are, whether you are studying something computer science-related or working in a relevant field etc.
Anyway, the Machine Learning Specialization is great to start with.
Best
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Thank you
Machine Learning Specialization will be still recommended as a starting point who has some experience with programming OR its for experienced developers ?
I am Test engineer and so lost in AI world, not sure where to start in AI field
Hello @Black_hawk_9x!
Basic experience with programming will be sufficient for the Machine Learning Specialization; it is in Python but the requirements for the specialization are basic coding skills (for loops, functions, if/else statements) & high school-level math (arithmetic, algebra).
Machine Learning Specialization is a great place to start, and a valuable resource to revisit later, I highly recommend it. It will provide you with the necessary foundation for understanding ML, and while beginner-friendly, it is not simplistic offering enough depth to equip you with practical skills that can often be directly applied in real-world professional projects.
thanks, Is is possible to share / guide in detail road map if you can. I tried to find information online and on chatgpt but all seems like it will take years to just get in. Huge list of python libraries, frameworks, maths and statistics , data handling, many ML algorithms, etc.
My background is IT graduate, Sr. Test engineer experienced with Python, AWS, API test automation.
I do not have a specific roadmap to share and if I had I assume it would be along the same lines as what you already can find yourself.
In terms of Coursera - deeplearning.ai courses, definitely start with Machine Learning Specialization and then do the Deep Learning Specialization, both are really good resources and provide the fundamentals of ML. I would definitely recommend these two to anyone interested in getting into AI.
Then you will have a clearer picture of the ML landscape and since you already have experience in IT I think you will be able to assess for yourself both what the job market actually demands as well as your specific interests; e.g. image processing, natural language processing, robotics etc (not that all these do not have overlaps).
If your goal at that point is to get a job in ML, maybe performing a gap analysis between your skills and what the market demands would be helpful. As you might know AWS is really in demand, and of course any IT experience is more advantageous than no exprience.
Maybe also check out the differences between the roles of a Data Scientist, a Machine Learning Engineer, a Data Engineer (in this case there also the newly introduced Data Engineering Specialization, which I personally have not yet done, but intend to) etc, and see what seems more accessible/ is more in demand in the market you are aiming for.
E.g. role of a data scientist generally requires a deeper and more comprehensive understanding of statistics than that of a machine learning engineer, the role of data engineer even less (for more nuances like this I have found that chatgpt gives pretty good answers).
Regarding the maths, statistics and algorithms, you can keep learning as you go and as the need for specific knowledge arises (and again chatgpt can be really helpful in this journey), the specializations offers a really good foundation (I believe there is also supplemetary material offered, you can study this according to your interests and needs).
I completely agree that it can be overwhelming, but technically, you don’t need to know everything to get a job in ML or to be able to do it (the issue of the state of the job market and how bad it can be at times for all the various reasons is another story).
You can also check out Andrew Ng’s ebook: [How to Build Your Career in AI eBook - Andrew Ng Collected Insights]
Here you can find more resources suggested by mentors:
[Deep Learning Bibliography]
To sum up, I would suggest starting with MLS and DLS, then deciding on the direction(s) that seem more suitable to you and studying accordingly. You can then look again for a more specifc roadmap/resources, you can even ask again here in the discussions/look for already existing answers. For the latter I also use reddit 
and have found helpful answers there.
Good luck and don’t hesitate to ask again here in the community!
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