Calculus: The Engine of AI
Undergraduate STEM students aged 18–22 and working professionals seeking to transition or advance into AI/ML careers with strong practical and mathematical skills.
Taught byM Sanjeeva ReddyM.Sc. MathematicsWhat you'll learn
Master gradients with mathematical rigour and hands-on coding—learn to compute derivatives, visualise gradient fields, and implement optimisation algorithms like momentum and Adam. Apply these powerful techniques to machine learning, engineering, finance, medicine, and speech recognition, gaining practical AI/ML skills that set you apart in global careers.
Course content
3 modules10 lessons3h 20m
GRADIENT FOUNDATIONS3 lessons · 58 min
- Tip 8 - Gradient Vector
- 01Calculus c3 video 1
- Tip 8(a) - Partial Derivatives
- 02Calculus c3 video 2
- Tip 8(b) - Gradient Notation
- 03Calculus c3 video 3
AI & NEURAL OPTIMISATION4 lessons · 1h 14m
- Tip 9 - Steepest Ascent and Descent
- 04Calculus c3 video 4
- Tip 9(a) - Hiker Analogy
- 05Calculus c3 video 5
- Tip 9(b) - Gradient Descent Algorithm
- 06Calculus c3 video 6
- Tip 10 - Optimisation in ML & EdTech
- 07Calculus c3 video 7
CROSS-INDUSTRY APPLICATIONS3 lessons · 1h 07m
- Tip 11(a) - Backpropagation
- 08Calculus c3 video 8
- Tip 11(b) - Speech Recognition Video
- 09Calculus c3 video 9
- Tip 12(a) + Tip 12(b) - Finance & Economics + Biology & Medicine
- 10Calculus c3 video 10
About this course
Course Outcomes:
- Compute gradients of multivariable functions using partial derivatives and implement gradient descent algorithms in Python with convergence to optimal solutions within specified tolerance
- Apply gradient-based optimisation to real-world problems including portfolio optimisation, options pricing, and medical image processing with demonstrable improvement from baseline methods
- Feel confident in implementing mathematical concepts from research papers into working Python code for machine learning applications
Your teacher
M Sanjeeva Reddy
M.Sc. MathematicsFuture-ready mathematics innovator, blending AI, machine learning, and timeless principles to make math accessible and empowering.
