NumPy Course

Module 1: Introduction to NumPy4

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1. 1What is NumPy in Python?
2. 2Why Use NumPy Instead of Python Lists?
3. 3Installing NumPy using pip
4. 4How to Import NumPy in Python

Module 2: NumPy Arrays - Basics7

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1. 1Creating NumPy Arrays in Python
2. 2NumPy Array Data Types
3. 3NumPy Array Attributes
4. 4NumPy Indexing
5. 5Slicing in NumPy
6. 6Modify Array Elements in NumPy
7. 7Array Iteration in NumPy

Module 3: Array Operations6

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1. 1NumPy Arithmetic Operations
2. 2Universal Functions in NumPy
3. 3NumPy Broadcasting
4. 4NumPy Comparison Functions
5. 5NumPy Aggregation Functions
6. 6NumPy Axis-Based Computations

Module 4: Linear Algebra with NumPy7

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1. 1NumPy Axis-Based Computations (1D, 2D, 3D)
2. 2Array Multiplication in NumPy
3. 3Array Transpose in NumPy - Examples
4. 4Inverse of a Matrix in NumPy
5. 5NumPy Determinant Tutorial
6. 6Solve Linear Equations using NumPy
7. 7Eigenvalues, Eigenvectors, and Diagonalization in NumPy

Module 5: Array Reshaping and Manipulation7

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1. 1NumPy Reshape
2. 2Flatten Array in NumPy
3. 3NumPy ravel() – Flatten a Multi-Dimensional Array
4. 4NumPy Concatenation
5. 5Stacking in NumPy - Horizontal, Vertical, Depth
6. 6Splitting Arrays in NumPy
7. 7Adding and Removing Dimensions in NumPy Arrays

Module 6: Advanced Indexing and Masking3

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1. 1Boolean and Fancy Indexing in NumPy
2. 2NumPy where(), nonzero(), and argwhere()
3. 3NumPy Conditional Extraction

Module 7: Useful NumPy Utilities5

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1. 1NumPy Random Module - Examples
2. 2Sorting Arrays in NumPy
3. 3Searching in NumPy Arrays
4. 4NumPy clip() – Limit Values in an Array
5. 5Set Operations and Unique Values in NumPy

Module 8: Working with Missing or Invalid Data4

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1. 1Detecting NaNs in NumPy Arrays
2. 2Detecting Infs in NumPy Arrays
3. 3How to Replace or Remove Missing Data in NumPy Arrays
4. 4Masked Arrays in NumPy - Handle Missing or Invalid Data

Module 9: NumPy with Real Data2

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1. 1Read and Write Data from TXT & CSV Files Using NumPy
2. 2Data Preprocessing in NumPy

Module 10: Performance Optimization3

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1. 1Vectorization Techniques in NumPy
2. 2Memory Layout in NumPy: Views vs Copies
3. 3Timing and Optimizing Code in NumPy

Module 11: NumPy + SciPy + Pandas4

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1. 1Overview of SciPy
2. 2Overview of Pandas
3. 3Using NumPy Arrays with Pandas
4. 4NumPy vs Pandas