NumPy
High-performance numerical computing and array manipulation in Python.
Course overview
NumPy is the fundamental package for scientific and numerical computing in Python. This focused course teaches multi-dimensional ndarrays, vectorized operations that replace slow loops, broadcasting rules, advanced boolean indexing, random sampling, and essential matrix math.
Prerequisites
What you'll achieve
- Create and manipulate 1D, 2D, and multi-dimensional NumPy arrays
- Write fast, vectorized numerical code without explicit Python loops
- Apply array broadcasting rules to perform arithmetic across different dimensions
- Perform matrix multiplications, transpositions, and linear algebra operations
Curriculum
- 1Why NumPy: Performance, memory layout & ndarray concept
- 2Array creation routines, data types (dtype) & shape inspection
- 3Array indexing, slicing, views vs. copies & boolean masking
- 4Vectorized operations & universal functions (ufuncs)
- 5Broadcasting rules and multi-dimensional arithmetic
- 6Aggregation functions (sum, mean, std, axis operations)
- 7Linear algebra fundamentals with numpy.linalg
- 8Project: Numerical matrix simulation and dataset transformations
Who is this for?
Python developers, data analysts, science students, and aspiring AI engineers.
Contact admissions for current fee and available learning formats
Enrol in NumPy
- 3 weeks
- Beginner to Intermediate
- Live online · One-to-one available · Group batches when scheduled
- 1-on-1 & small batches
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Ready to start your learning journey?
Apply today and our admissions team will review your application and guide you through the next steps.