Calculus: The Power of Integration
Built for undergrads and beyond in math, engineering, CS, data science, physics, and life sciences — learn by implementing, not just deriving, with hands-on Python, NumPy, and Matplotlib.
Taught byM Sanjeeva ReddyM.Sc. MathematicsWhat you'll learn
Learn numerical integration in Python — from error analysis and convergence to probabilities, Fourier analysis, and real-world applications in medical imaging, drug exposure, and bioinformatics
Course content
3 modules10 lessons3h 43m
NUMERICAL INTEGRATION METHODS3 lessons · 1h 03m
- Numerical Integration Methods
- 01The power of integration video 1
- From Formula to Python Code
- 02The power of integration video 2
- Error Bounds & Convergence
- 03The power of integration video 3
PROBABILITY THROUGH INTEGRATION4 lessons · 1h 28m
- Continuous Probability Distributions
- 04The power of integration video 4
- Expected Value & Variance via Integration
- 05The power of integration video 5
- Multiple Integrals & Joint Distributions
- 06The power of integration video 6
- Marginal Distributions & Integrating Out
- 07The power of integration video 7
INTEGRALS IN SIGNALS AND SYSTEMS3 lessons · 1h 11m
- Improper Integrals & Signal Processing
- 08The power of integration video 8
- Fourier Transforms — Frequency Analysis
- 09The power of integration video 9
- Medical Imaging & Bioinformatics (
- 10The power of integration video 10
About this course
Course Outcomes:
- Implement trapezoidal and Simpson integration using Python and NumPy.
- Measure numerical error, estimate convergence order, and select a suitable method.
- Compute probabilities, moments, marginals, and conditional densities through integration.
Your teacher
M Sanjeeva Reddy
M.Sc. MathematicsFuture-ready mathematics innovator, blending AI, machine learning, and timeless principles to make math accessible and empowering.
