I am seeking advice on the optimal sequence of courses to pursue in order to establish a solid foundation in the field of data science. Could anyone kindly share insights on the recommended ordering of these courses? Your guidance would be greatly appreciated.
Hi @ZAYEDHEMAID
great question!
My take: the best personal sequence for you depends on:
- where you stand now (e.g beginner or medium)
- what you want to achieve (e.g. become an AI engineer in the field of IoT / Automotive)
- your strength and background of the industry you want to work (e.g. background in image processing with focus on sensor fusion and deep learning)
- your timeline, considering how much time you want to invest in your learning roadmap (e.g. 5 hours per week for 8 months or so)
see also these threads:
- How to become an AI Engineer - #4 by Christian_Simonis
- After completing DLS, what's next - #4 by Christian_Simonis
A quite classic sequence which seems to be popular among fellow learners seems to be:
- AI for everyone (if you are a beginner)
- machine learning specialization for the basics and core concepts
- deep learning specialization if this suits your plans and you work rather with big unstructured data and want to apply or work with CV, NLP, LLM etc.
- (MLOps or TF specialization dependent on your requirements and plans)
@saifkhanengr: anything you want to add? I think you also advised recently some students on a similar question, right?
Best regards
Christian
no, I was asking about the courses I have sent, what is the right order for them to take if I am a beginner like the first course is AI for every, the second mathematics for machine learning and data science specialization, third is machine learning specialization fourth is deep learning specialization
i have asked about the ordering for the courses I have sent
Yes, and I have sent you my answer in the previous post for exactly the courses you have sent, haven‘t I?
To be clear:
I think you do not need to take all courses in the beginner section before moving to medium (or taking all medium courses before moving to advanced)…
As mentioned already: If you are an absolute beginner, I would suggest to start with:
-
AI 4 everyone (3rd one in your screenshot). Afterwards I would suggest so reflect on your experience and
-
afterwards: if you want to learn more of the fundamental concepts follow the path of the mentioned machine learning specialization (1st one in your screenshot). Then I would suggest to reflect again and adapt your plans if needed.
Hope that helps, happy learning & Good luck, @ZAYEDHEMAID!
Best regards
Christian
I meant the ordering for them as a roadmap (what is the right ordering for all courses in my pictures ) : like this formal
1.AI for Everyone
2. Mathematics for Machine Learning and Data Science Specialization
3. Machine Learning Specialization
4. Deep Learning Specialization
5.
.
.
and so on, hope u got my point
Again, dear @ZAYEDHEMAID: a general roadmap does not really make sense in my opinion since:
-
the optimum sequence and order would be different for different learners based on their goals, see my first post, (e.g. a cloud practitioner might never take the math specialization but rather focus on MLOps and Tensorflow instead to boost her career)
-
this would mean a waterfall planning over several years and as mentioned it’s important to reflect and adapt in my experience, see my second post
-
I do not know a single person so far who took all these courses and specializations that you mentioned. Personally, I took 3 specialisations and in addition couple of courses based on personal interest. I think to obtain a „solid foundation in the field of data science“ as you have asked, I have provided you with my answer and even though I really want, I am afraid I cannot add much more to my reply. Sorry!
Potentially and maybe some of my fellow mentors can help you better than me, e.g. if they have taken more specialisations or so…
Anyway - Wish you all the best and a good experience along your learning journey.
Have a good one!
Best regards
Christian
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You do not need to attend all of those courses, nor do you need to complete all of the courses in any level.
No customized roadmap is possible, unless we know a very great deal about your skills, your interests, your ability to learn, and your goals.
You have to decide for yourself as you proceed, based on your understanding of the courses you have completed and what you learn about areas which may interest you.
The Machine Learning field is far too large now for anyone to know everthing.
Certainly, since we don’t know anything about you, its safe to recommend you start with AI for Everyone, and see where that leads you.
In general most students end up attending the Machine Learning Specialization followed by the Deep Learning Specialization. They’re both general courses that touch on many topics.
Then students branch out into other specialities where they have specific interests.
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i relly appreciate it thank u very much
Hi Christian! You and Tom mentioned everything in your messages and nothing is left. I posted a generic roadmap to AI in my LinkedIn post but, as you guys already mentioned, without knowing @ZAYEDHEMAID current level and future goal, we cannot provide a custom roadmap.
Best,
Saif.
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