Hyperparameter Tuning Courses and Certifications

Coursera Career Certificate

Machine Learning Made Easy for Software Engineers

Master the full ML lifecycle—from training and optimizing models to deploying production-ready microservices—with hands-on projects covering pipelines, monitoring, and debugging.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

Coursera

Building, Optimizing, and Validating Machine Learning Models

Master building, optimizing, and validating ML models using hyperparameter tuning, cross-validation, SHAP explanations, and automated pipelines for efficient, reproducible workflows.

• Coursera
• 12 hours 9 minutes
• Self-Paced
• Paid Course

EDUCBA

Credit Default Prediction with Python: Apply & Analyze

Master credit default prediction using Python through logistic regression, decision trees, and ensemble methods with hands-on data preprocessing and model optimization techniques.

• Coursera
• 5 hours 52 minutes
• Self-Paced
• Paid Course

Whizlabs

Fundamentals of Machine Learning

Master machine learning fundamentals with hands-on experience in supervised/unsupervised learning, data preparation, model optimization, and cloud deployment on AWS and Azure.

• Coursera
• 12 hours 39 minutes
• Self-Paced
• Paid Course

KodeKloud

Deploy ML Models to Production

Master MLOps by deploying ML models from development to production using MLflow, BentoML, and AWS SageMaker with hands-on insurance claim application project.

• Coursera
• 3 hours 53 minutes
• Self-Paced
• Paid Course

Coursera

Optimize Deep Learning: Tune PyTorch Models

Master PyTorch Lightning to implement custom callbacks, debug training issues, and optimize deep learning models for stable, production-ready performance.

• Coursera
• 3 hours 40 minutes
• Self-Paced
• Paid Course

Packt

Applied Machine Learning and Model Optimization

Master advanced ML algorithms, hyperparameter tuning, and model optimization techniques through hands-on projects with XGBoost, ensemble methods, and real-world applications.

• Coursera
• 21 hours 9 minutes
• Self-Paced
• Paid Course

KodeKloud

ML Model Development and Tracking: Hands-on Guide

Master MLOps "Middle Loop" with MLflow tracking, model versioning, and production deployment through hands-on insurance claim automation project.

• Coursera
• 3 hours 3 minutes
• Self-Paced
• Paid Course

Packt

Real-world End to End Machine Learning Ops on Google Cloud

Master the complete ML lifecycle on Google Cloud with CI/CD pipelines, Vertex AI, Kubeflow, and automated deployment using real-world hands-on projects and industry best practices.

• Coursera
• 9 hours 13 minutes
• Self-Paced
• Paid Course

Practical Machine Learning without Coding

Discover how to build, optimize, and deploy machine learning models using no-code platforms, from standard algorithms to advanced automation and real-world business integration.

• Coursera
• 3 hours 20 minutes
• Self-Paced
• Paid Course

Coursera

Track and Evaluate ML Model Experiments

Master systematic ML experiment tracking with DVC and Weights & Biases to build reproducible, auditable workflows that eliminate "it worked on my machine" problems.

• Coursera
• 2 hours 57 minutes
• Self-Paced
• Paid Course

Packt

Core Machine Learning & Evaluation

Master machine learning fundamentals, feature engineering, advanced algorithms, and model optimization through hands-on projects and real-world applications.

• Coursera
• 11 hours 25 minutes
• Self-Paced
• Paid Course

Packt

AI Product Manager Explorer

Explore Python programming, machine learning, and AI agent development. Build skills in feature engineering, AutoGPT, and GPT deployment for business, healthcare, and robotics applications.

• Coursera
• 14 hours 38 minutes
• Self-Paced
• Paid Course

Coursera

Engineer AI Models: Explain, Tune & Experiment

Master AI model engineering through feature tuning, explainability methods like SHAP/LIME, and structured experimentation to transform black box models into trusted, business-ready solutions.

• Coursera
• 2 hours 21 minutes
• Self-Paced
• Paid Course

Coursera

Learn to Choose the Right ML Model

Discover how to systematically select and deploy ML models using structured problem typing, algorithm comparison, and metrics-driven workflows for production success.

• Coursera
• 2 hours 45 minutes
• Self-Paced
• Paid Course