Hello . I am still on week 1 . In the course when they explain the topic , I understand it . I know python basics too . However in the optional labs , when there is new python code which I’ve not used till now , like using python libraries like numpy and matplotlib , what should I do ? should I just go through it once , and try to understand it , or should I learn it all first ?
MLOps is an intermediate level course. As shown on the coursera course page under the Recommended experience
section, the following are the prerequisites:
- Some knowledge of AI / deep learning
- Intermediate Python skills
- Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
If / how to meet the requirements is your choice. That said, there are plenty of courses on coursera that cover the above listed topics.
Have you done python courses?
you could start with AI for python beginner course provided by deep learning.ai beta learning platform.
can we know why chose to start with mlops course
Sorry I put this question under the MLOps course . I am currently doing the course 1 from the ML specialization ,which is the Supervised and Unsupervised learning course
Sorry I put this question under the MLOps course . I am currently doing the Supervised learning course , which is part of the ML specialization course
I have moved the thread to the forum area for that course.
ok then can I know if you have done any python course? or programming course?
Honestly even when I started I didn’t know much, so whenever I had any such doubt silly as silly, I would research myself, ask doubt here in discourse forum, and understanding python coding.
but if you ask me what different I would have done is doing a python course as a beginner journey where I would practice by myself to understand what numpy does, what is the significance of matplotlib. Some of this module were similar to other programming language which I already was doing, so that was my plus point when I started my ai journey.
Thanks
I know c++ . I had a python course in my university , but that was a beginner course .
Hello, @HMDPatil,
I think that generally three key goals of these labs are: (1) to implement the algorithm, (2) to see that things work like explained in lectures, and (3) as a experimentation platform for challenging concepts learned.
To achieve these goals, you do not really need to understand numpy and matplotlib. You may skip all the matplotlib code and just to focus on the visualization brought by it. You will only want to learn matplotlib when you wish to make additional plots.
For numpy, this course implements algorithm in a baseline approach that uses loops, whereas the more advanced approach with numpy is considered optional for the scope of these courses.
Therefore, I would say you don’t need to learn it all first. If I were you, I would read them and make sense of it but without having to be like able to write it from scratch myself. I would not dig deep unless I had my own reason to.
I have a similar background with you in that I had known C++ before started Python, so I believe the syntax wouldn’t be a problem for you, and you may well guess the purpose by function’s name and understand why those functions accept those arguments.
Cheers,
Raymond