Python for Data Science & Machine Learning: Zero to Hero (Udemy.com)

The course provided a solid foundation in NumPy, Pandas, Matplotlib, and Seaborn, clearly explaining their purposes and how they complement each other in data analysis. It effectively covered NumPy for fast numerical operations, Pandas for structured data handling, Matplotlib for customizable plotting, and Seaborn for attractive, high-level statistical visualizations.

This course is excellent for anyone starting to learn Python. It's beneficial and well-structured. Everything is explained simply and easily, with plenty of examples to help reinforce the concepts. I also really appreciate the fluency and smooth flow of the content throughout the course.

best course sir please update the course with foundation of linear algebra, calculus,statistics, all latest ML algorithms, with projects and exercises. also for deep learning also thank you

This is an excellent course for anyone looking to build a strong foundation in Data Science and Machine Learning using Python. It covers all the essential modules and libraries in a clear and structured manner. The practical implementation of concepts is particularly impressive, making it easy to apply what you learn. Highly recommended for beginners and those who want to strengthen their fundamentals in this field.

Yes , this course is amazing and its totally helpful for me and for others also After completing till section 6 i found that some contents are very basic which would not be helpful for other so try to cover all the basic in just one shot video that my be of 15 min , apart form that overall course is good .

This course is a rapid fire of key functions in python from basics of data manipulation to machine learning algorithms, it provides a good reference resource, but you need to practice yourself to get the most out of it.

It is a course with a few number of examples, it just explains one thing, and again shows it in jupyter notebooks, also it doesn´t provide with exercises to practise, just some silly questions.

It was a beginners friendly lecture. Easy to remember and the course resources are very well compiled. I am new to python for data analysis and this is a very helpful stepping stone.

Early content (basics, python syntax, etc.) was good, but later content got advanced quickly and assumed I knew things I don't. Code being written in those examples had content that wasn't familiar and also not explained. I did like the practical application examples throughout. Voiceover and slides had minor disconnections. Pronunciation of the instructor was odd sometimes (and a little distracting). Generally, have a better sense of concepts, but don't think I could go out on my own and implement w/o a lot of reference and additional research.

I am immensely enjoying this course in learning very different things now in this course this is very helpful for to understands that basics of python data computer science