Part 1: Foundations

1. Chapter 1: What NumPy Is
2. Chapter 2: Installing and Importing NumPy
3. Chapter 3: Python Lists vs NumPy Arrays
4. Chapter 4: Creating One-Dimensional Arrays
5. Chapter 5: Creating Two-Dimensional Arrays
6. Chapter 6: Array Shapes
7. Chapter 7: Array Dimensions
8. Chapter 8: Array Size
9. Chapter 9: Data Types
10. Chapter 10: Changing Data Types

Part 2: Core Operations

1. Chapter 11: Zeros Ones and Full Arrays
2. Chapter 12: Ranges with arange
3. Chapter 13: Evenly Spaced Values with linspace
4. Chapter 14: Reshaping Arrays
5. Chapter 15: Flattening Arrays
6. Chapter 16: Transposing Arrays
7. Chapter 17: Indexing Basics
8. Chapter 18: Negative Indexing
9. Chapter 19: Slicing Arrays
10. Chapter 20: Boolean Indexing

Part 3: Data Analysis

1. Chapter 21: Fancy Indexing
2. Chapter 22: Copy vs View
3. Chapter 23: Changing Array Values
4. Chapter 24: Adding Arrays
5. Chapter 25: Subtracting Arrays
6. Chapter 26: Multiplying Arrays
7. Chapter 27: Dividing Arrays
8. Chapter 28: Powers and Roots
9. Chapter 29: Rounding Numbers
10. Chapter 30: Absolute Values

Part 4: Advanced Techniques

1. Chapter 31: Aggregation with sum
2. Chapter 32: Mean Median and Standard Deviation
3. Chapter 33: Minimum and Maximum
4. Chapter 34: Argmin and Argmax
5. Chapter 35: Sorting Arrays
6. Chapter 36: Unique Values
7. Chapter 37: Counting Values
8. Chapter 38: Broadcasting
9. Chapter 39: Broadcasting Rules
10. Chapter 40: Vectorized Operations

Part 5: AI Workflows

1. Chapter 41: Comparisons and Masks
2. Chapter 42: Combining Conditions
3. Chapter 43: Where
4. Chapter 44: Concatenating Arrays
5. Chapter 45: Stacking Arrays
6. Chapter 46: Splitting Arrays
7. Chapter 47: Matrix Multiplication
8. Chapter 48: Dot Products
9. Chapter 49: Identity Matrices
10. Chapter 50: Determinants Concepts

Part 6: Projects and Review

1. Chapter 51: Inverse Matrices Concepts
2. Chapter 52: Solving Linear Systems Concepts
3. Chapter 53: Eigenvalues Concepts
4. Chapter 54: Random Numbers
5. Chapter 55: Random Sampling
6. Chapter 56: Reproducible Randomness
7. Chapter 57: Mini Project: Normalize Features
8. Chapter 58: Mini Project: Similarity Calculator
9. Chapter 59: Mini Project: Image Pixel Array
10. Chapter 60: Capstone: AI Numerical Data Pipeline