Python Complement: Numpy, Scipy, Matplotlib

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Page 3 of 3

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

Explores Python modules, program hierarchy, module importing, and namespaces, including variables and scopes within functions.

Covers the representation of structured data, arrays, structures, and functions with multiple return values.

Introduces Python programming concepts, focusing on lists, functions, and their applications in problem-solving.

Introduces Python programming basics, focusing on functions to enhance code efficiency.

Covers blocks, functions, and references in C++, including scope, variables, function usage, interfaces, pointers, and references.

Covers the definition of a function to determine if a given number is prime.

Covers functions, compositions, and applications in linear algebra.

Covers conditions, loops, functions, and graphics in R programming with practical examples.

Covers array creation, indexing, manipulation, and broadcasting using NumPy in Python.