Optimization Algorithms Courses and Certifications

Foundations of Optimization Algorithms

Explore Newton’s method, gradient descent, momentum, and Adagrad through hands-on function minimization and visualized optimization paths.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Optimization problems and algorithms [2024]

1721 ratings at Udemy

Understand, Formulate & Tackle Optimization Problems Using Heuristic Algorithms in Matlab

• Udemy
• 8 hours 4 minutes
• Self-Paced
• Paid Course

Quantum-Inspired Algorithms and the Azure Quantum Optimization Service

2 ratings

See how quantum-inspired algorithms formulate and solve difficult optimization problems with Azure Quantum and Python, using a Secret Santa example.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Gradient Descent: Building Optimization Algorithms from Scratch

Implement optimization algorithms from scratch in Python: stochastic and mini-batch gradient descent, Momentum, RMSProp, and Adam, tuning learning rates, batch sizes, and decay parameters.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate

Coursera

Optimize with GA & RL

Apply genetic algorithms to inventory-replenishment problems, train Q-learning agents in grid-world supply-chain simulations, and tune ε-greedy parameters while weighing convergence speed against solution quality.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Introduction to optimization on smooth manifolds: first order methods

Learn to optimize on smooth, nonlinear spaces: Join us to build your foundations (starting at "what is a manifold?") and confidently implement your first algorithm (Riemannian gradient descent).

• edX
• 6 weeks, 5-6 hours a week
• Self-Paced
• Free Online Course (Audit)

Solving Algorithms for Discrete Optimization

44 ratings at Coursera

Learn how discrete optimization solvers work: constraint propagation and search in MiniZinc, branch and bound, simplex and Gomory cuts, and local search with simulated annealing.

• Coursera
• 4 weeks, 5 hours a week
• Self-Paced
• Paid Course

IIT Madras;  NPTEL

Optimization Theory and Algorithms

Study descent, conjugate-gradient, Newton, and constrained optimization algorithms through theory, convergence analysis, and MATLAB assignments.

• Swayam
• 12 weeks
• Available until Oct 9, 2026
• Free Online Course

Gradient Descent: Building Optimization Algorithms from Scratch

Implement stochastic, mini-batch, momentum, RMSProp, and Adam gradient descent optimizers from scratch in C++ while tuning their parameters.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate

NPTEL-NOC IITM

Convergence Analysis of a Descent Algorithm - Part 2

Explore convergence analysis of descent algorithms, including condition number concepts and MATLAB implementation for optimization problems.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Unconstrained Optimization - Identifying a Local Minima - 1st and 2nd Order Conditions - Part 2

Explore the necessary and sufficient conditions for identifying local minima in unconstrained optimization, including Taylor's theorem, first-order conditions, and descent direction algorithms.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

BFGS Method

Explore the BFGS method, a powerful optimization algorithm used in numerical analysis and machine learning applications.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Convergence Analysis of a Descent Algorithm - Part 1

Explore the convergence analysis of descent algorithms, including condition number concepts and MATLAB implementation techniques for optimization.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Unconstrained Optimization - Proof of 1st Order Condition - Lecture 3

Understand the proof of first order condition in unconstrained optimization, including Taylor's theorem, necessary conditions, and descent direction identification.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

Yacine Mahdid

AdamW Optimizer from Scratch in Python

Discover how to implement the state-of-the-art AdamW optimizer from scratch, understanding its unique weight decay regularization that outperforms traditional Adam + L2.

• YouTube
• 20 minutes
• Self-Paced
• Free Video