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Feuille de route complète LM
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Module 5
Scientific Computing with NumPy
1
Creating NumPy Arrays
Create NumPy arrays from lists and using built-in functions (arange, linspace, zeros, ones).
2
Array Indexing and Slicing
Access and modify array elements using indexing and slicing.
3
NumPy Array Arithmetic
Perform element-wise arithmetic operations on NumPy arrays.
4
Array Broadcasting Fundamentals
Explain and apply broadcasting rules for operations on arrays of different shapes.
5
NumPy Statistics: Mean, Std, Sum, Min, Max
Use NumPy functions for statistical computations (mean, std, sum, min, max).
6
NumPy Matrix Operations
Perform matrix operations using NumPy (dot product, transpose, inverse).
7
Reshaping NumPy Arrays
Reshape a NumPy array to a compatible new shape.
8
Combining NumPy Arrays: Concatenation Basics
Concatenate multiple NumPy arrays along a specified axis.
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Python Data Structures and Modular Code
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Data Analysis with Pandas and Visualization