NumPy
Master numerical computing with NumPy in Python. Explore arrays, mathematical functions, and high-performance operations for scientific and data analysis.
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Learning Objectives
What You will Learn in This Course
Understand NumPy ndarray and its properties.
Master array creation and manipulation techniques.
Perform complex mathematical and statistical operations.
Implement vectorized operations for performance.
Learn indexing, slicing, and broadcasting.
Handle missing data and data cleaning with NumPy.
Integrate NumPy with other Data Science libraries.
Optimize memory usage and execution speed.
Course Schedule
Stay on Track with This Schedule
Advanced Manipulation
Understand Memory layout, dtypes, and Structured Arrays in depth.
Mathematical Modeling
Apply Linear Algebra, Fourier Transforms, and Complex Numbers.
Randomization & Simulation
Generate Random distributions and model Stochastic processes.
Performance Tuning
Compare Vectorization vs Loops and use Memory-mapped files.
Scientific Integration
Integrate with SciPy and other low-level numerical engines.
Full Analysis Project
Process a large-scale Meteorological or Genomic dataset.
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