Optimization Algorithms Courses and Certifications

Foundations of Optimization Algorithms

Master optimization algorithms from Newton's Method to adaptive learning rates, covering gradient descent, momentum techniques, and Adagrad for effective machine learning model tuning.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Artificial Intelligence: Optimization Algorithms in Python

607 ratings at Udemy

Learn how to build optimization algorithms from the ground up!

• Udemy
• 6 hours 46 minutes
• On-Demand
• Paid Course

Erwin Schrödinger International Institute for Mathematics and Physics (ESI)

Bilevel Optimization Problems: Algorithms and Theory

Explore recent developments in bilevel optimization algorithms, their theoretical analysis, and challenges in machine learning and data science applications.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Centre for Networked Intelligence, IISc

Optimal Algorithms for Online Convex Optimization with Adversarial Constraints

Discover optimal algorithms for online convex optimization with adversarial constraints, exploring how to achieve small regret and constraint violation simultaneously through Lyapunov optimization and AdaGrad techniques.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Optimization Algorithms Using Gibbs State Preparation and Beyond

Explore quantum optimization algorithms using Gibbs state preparation for semidefinite and second-order cone programming, with applications to portfolio optimization.

• YouTube
• 49 minutes
• On-Demand
• Free Video

Microcredential

Operations Research

722 ratings at Coursera

Master mathematical programming and optimization algorithms to solve real-world business and engineering problems through systematic evaluation methods and theoretical foundations.

• Coursera
• 8 weeks, 10 hours a week
• On-Demand
• Paid Course
• 4 courses

Gradient Descent: Building Optimization Algorithms from Scratch

Master optimization algorithms by implementing Gradient Descent variants from scratch, including Stochastic, Mini-Batch, Momentum, RMSProp, and Adam methods, with hands-on Python implementation and practical applications.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate

Gradient Descent: Building Optimization Algorithms from Scratch

Master optimization algorithms by implementing SGD, Mini-Batch GD, Momentum, RMSProp, and Adam from scratch in C++ without relying on high-level libraries for deep understanding.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate

The Grey Wolf Optimizer

286 ratings at Udemy

Learn Inspirations, Theories, Mathematical Models, and Practical Applications of the Grey Wolf Optimizer

• Udemy
• 3 hours 13 minutes
• On-Demand
• Paid Course

Operations Research (2): Optimization Algorithms

158 ratings at Coursera

Explore optimization algorithms for linear, integer, and nonlinear programs. Learn efficient methods like simplex, branch-and-bound, gradient descent, and Newton's method. Apply concepts to real-world business cases.

• Coursera
• 12 hours
• On-Demand
• Paid Course

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

63510 ratings at Coursera

Enhance deep learning skills: master hyperparameter tuning, regularization, optimization, and TensorFlow implementation for improved neural network performance and systematic results generation.

• Coursera
• 23 hours 35 minutes
• On-Demand
• Paid Course

Yannic Kilcher

Descending Through a Crowded Valley - Benchmarking Deep Learning Optimizers

Comprehensive analysis of popular deep learning optimizers, comparing performance across tasks and providing evidence-based recommendations for algorithm selection and parameter tuning.

• YouTube
• 41 minutes
• On-Demand
• Free Video

Yannic Kilcher

Training More Effective Learned Optimizers, and Using Them to Train Themselves - Paper Explained

Explores a novel approach to machine learning optimization using neural networks, discussing its architecture, training process, and potential to revolutionize model training through self-improvement and generalization.

• YouTube
• 54 minutes
• On-Demand
• Free Video

Alfredo Canziani

Optimisation

Explore optimization techniques for neural networks, including gradient descent, SGD, momentum, adaptive methods, and normalization layers, with real-world applications in MRI technology.

• YouTube
• 1 hour 29 minutes
• On-Demand
• Free Video

Alan Turing Institute

Delayed Column Generation in Large Scale Integer Optimization Problems

Explore delayed column generation for solving large-scale mixed integer programming problems, focusing on applications in data science and decision mathematics.

• YouTube
• 2 hours 41 minutes
• On-Demand
• Free Video