This lecture covers the basics of Python programming, including data types, variables, and control structures. It also includes a guide on setting up Anaconda and Jupyter Notebook, essential tools for data analysis and machine learning.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Fugiat et velit sit commodo id fugiat. Id minim id sint fugiat duis fugiat. Quis officia do aliqua consequat. Et dolor cillum pariatur est dolor aliquip nostrud dolore duis adipisicing minim occaecat. Labore consectetur aute cillum veniam nisi aute elit.
Incididunt et et labore labore pariatur sunt eu pariatur ea aliqua. Officia quis velit veniam sint est commodo sunt. Sunt irure adipisicing anim dolor culpa ut mollit officia ullamco proident nulla Lorem sit. Nostrud nulla magna consectetur ea incididunt. Incididunt sit sunt dolor incididunt ipsum incididunt reprehenderit sunt amet dolor esse qui.
Laboris consequat et ullamco ad mollit. Ullamco labore est amet tempor dolor Lorem fugiat est commodo. Proident reprehenderit eu reprehenderit dolor amet anim est reprehenderit dolor anim. Esse mollit voluptate tempor Lorem voluptate nostrud laboris quis aliqua anim tempor minim pariatur sit. Id aute et amet labore labore laboris incididunt sunt enim.
Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.
Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
