Teaching with Notebooks: Getting Student Feedback

Related lectures (30)

Page 3 of 3

Covers Python sets operations, including creation, modification, and comparison, as well as set operations like union and intersection.

Explores the analysis of structures and mechanisms through a sample problem of opening a box with a string-held lid.

Explores data manipulation, exploration, and visualization in data science projects using Python.

Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.

Covers classical mechanics, molecular dynamics, integrators, constant-temperature simulations, and melting point calculations for aluminum.

Delves into advanced Spark optimization techniques, emphasizing data partitioning, shuffle operations, and memory management.

Explores recursive functions, including factorials and Fibonacci sequences, and their scope and namespaces.

Introduces Renku, a platform for collaborative data science, emphasizing reproducibility, shareability, reusability, and security.

Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.

Covers the usage of Anaconda in its graphical interface, including package management and virtual environments.