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Related lectures (30)

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Real Functions: Definitions and Properties

Explores real functions, covering parity, periodicity, and polynomial functions.

Mathematics: Sets and Functions

Introduces sets, functions, Cartesian products, and compositions, discussing images, preimages, and function properties.

Scopes and Lambdas: Data Science with Python

Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.

Python Complement: Numpy, Scipy, Matplotlib

Covers advanced Python topics like numpy operations, scipy linear algebra, and matplotlib for creating figures.

Python Basics: Functions and Lists

Introduces Python basics like types, functions, conditions, loops, and lists, with examples of string manipulation and list operations.

Python Object: Exercises and Syntax Basics

Covers Python object exercises and basic syntax questions, including classes, dictionaries, file operations, and functions.

Variables, Objects, Types

Introduces variables, objects, and types in Python, emphasizing the significance of object mutability and its implications when passing objects to functions.

Recursive Functions: Examples and Applications

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

Python Basics: Syntax, Variables, Functions

Covers Python basics such as syntax, variables, and functions, introducing the Renku platform for collaborative data science.

Functions and Control Structures in Python

Introduces functions and control structures in Python, emphasizing their importance for code organization and reusability.