Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - Course Resources

The video tutorial provides an overview of resources available for the course, including free materials accessible via a specific URL. It explains the use of Google Collab for course activities and offers guidance on setting it up. Additionally, it covers installing Python and associated libraries on local machines, with a focus on Windows users. The instructor recommends using Anaconda and virtual environments. The video also addresses common questions about course order and introduces a forum for student interaction. Finally, it emphasizes the importance of coding along with the course material rather than passively watching.

Where can you find additional resources for this course?

• Anaconda website

• Google Collab

• forum dot lazy programmer dot me

• lazy programmer dot ME slash numpy

What is recommended for managing Python libraries and versions?

• Avoiding library updates

• Using a single global environment

• Installing libraries directly on the system

• Using virtual environments

Where can students ask questions or share thoughts about the course?

• In a live chat during lectures

• Via email to the instructor

• On the forum at forum dot lazy programmer dot me

• In the course comments section

What is the recommended approach to learning in this course?

• Reading textbooks

• Coding along with the course material

• Downloading and running pre-written notebooks

• Watching videos without coding

Why is it discouraged to just download and run notebooks?

• It enhances understanding

• It saves time

• It is the best way to learn

• It is considered a waste of time