Scopes and Lambdas: Data Science with Python

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Covers the basics of writing functions in Python and working with function arguments.

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

Explores the limit of the quotient for sequences and the periodicity of functions.

Covers the Cauchy problem, focusing on differential equations and the role of initial conditions in determining unique solutions.

Covers control structures, loops, and functions in C language, emphasizing the importance of local variables and avoiding global variables.

Covers Fourier series, periodic functions, and Fourier transforms.

Discusses the Taylor series and secant method, focusing on their applications in numerical analysis and root-finding techniques.

Explores advanced Python programming concepts, focusing on list comprehensions and higher order functions.

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Introduces the purpose of mastering mathematics and calculation tools for engineers, emphasizing the need to think methodically and rigorously.