Bayesian Optimization Courses and Certifications

Google TechTalks

Robust Design Discovery and Exploration in Bayesian Optimization

Explore data-driven methods for robust design discovery and optimization, focusing on Bayesian techniques that efficiently handle uncertainties and adversarial scenarios in various scientific domains.

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

VinAI

Knowing the What But Not the Where in Bayesian Optimization

Explore Bayesian optimization techniques for finding optimal inputs when outputs are known. Enhance efficiency in hyperparameter tuning for deep reinforcement and supervised learning.

• YouTube
• 1 hour 8 minutes
• Self-Paced
• Free Video

Coursera

ML Parameters Optimization: GridSearch, Bayesian, Random

Tune machine learning regression models in a hands-on project, optimizing their parameters with grid search, random search, and Bayesian optimization.

• Coursera
• 1 hour 56 minutes
• Self-Paced
• Paid Course

Data Science Festival

Supply Path Optimization: A Bayesian Approach to Take Rate Estimation

Explore Bayesian approaches to bid shading and supply path optimization in programmatic advertising, enhancing pricing strategies and ROI for more effective real-time bidding campaigns.

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

Learning-based control

This MOOC introduces learning-based control (LBC): the use of machine learning in the design or operation of control systems. Participants will build a solid foundation in control, relevant machine le

• edX
• 7 weeks, 2-3 hours a week
• Self-Paced
• Free Online Course (Audit)

Master Hyperparameter Optimization for Tabular Learning

Optimize tabular models with cross-validation, grid and random search, Bayesian and multi-fidelity optimization, and Optuna for reliable, efficient tuning.

• Train in Data
• Self-Paced
• Paid Course

Towards Safe and Efficient Learning in the Physical World - Stanford Seminar

Exploring safe Bayesian optimization and model-based deep reinforcement learning for efficient, safe online learning in real-world applications like robotics and laser tuning.

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

Bayesian Optimization with Python

Implement the Bayesian optimization algorithm in Python with GPyOpt: optimize functions and tune hyperparameters in a machine learning project.

• Coursera
• No Longer Offered
• Paid Course

Google TechTalks

Pathwise Conditioning and Non-Euclidean Gaussian Processes

Explore advanced Gaussian process techniques for efficient Bayesian optimization, including pathwise conditioning and models on graphs and manifolds, enhancing decision-making in complex settings.

• YouTube
• 1 hour 7 minutes
• Self-Paced
• Free Video

Linux Plumbers Conference

Linux Kernel Autotuning for Optimal Performance

Automated solution for optimizing Linux kernel parameters using machine learning, focusing on memory management. Explores design, architecture, and results, proposing future in-kernel ML framework.

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

Digi-Key

Hyperparameter Optimization for Reinforcement Learning Using Meta's Ax

Learn to optimize hyperparameters for reinforcement learning using Meta's Ax framework. Explore grid search, random search, and Bayesian optimization techniques to improve machine learning model performance.

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

EDGE AI FOUNDATION

Physics-Aware Auto Tiny Machine Learning for Edge Devices

Explore physics-aware neurosymbolic AI optimization for resource-constrained devices, combining symbolic techniques with machine learning for enhanced edge computing applications.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

EDGE AI FOUNDATION

Sensitivity Analysis of Hyperparameters in Deep Neural-Network Pruning

Explore the impact of hyperparameter sensitivity in neural network pruning for optimizing model performance on resource-constrained devices through empirical analysis and optimization techniques.

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

The Julia Programming Language

Seamless Transition from Single-core Python to Julia Multi-GPU

Discover how to transform single-core Python code into scalable Julia applications for GPU supercomputers, with focus on automatic verification and parallel computing optimization.

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

Anyscale

How DataRobot Parallelizes Agentic Pipeline Searches with Ray and syftr

Discover how DataRobot's syftr framework uses Ray to optimize agentic LLM pipelines through massive distributed search, finding workflows 9× cheaper while maintaining accuracy.

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