Experiment Tracking Courses and Certifications

Weights & Biases

W&B 101 - Introduction to Weights & Biases for ML Experiment Tracking

Master experiment tracking, visualization, and ML optimization with W&B's comprehensive introduction to streamline collaboration and boost project efficiency.

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

Introduction to Data Versioning with DVC

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

• DataCamp
• 3 hours
• Self-Paced
• Free Trial Available

Prodramp

Smart ML Experiment Tracking and Model Registry with Neptune.AI Platform

Explore Neptune.ai for ML experiment tracking and model registry. Learn to log, compare, and organize model metadata efficiently, enhancing productivity and reproducibility in machine learning projects.

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

MLOps.community

Experiment Tracking in the Age of LLMs - MLOps Podcast

Explore experiment tracking in the age of LLMs with Neptune's CEO. Gain insights on managing ML experiments, prompt engineering, and achieving control and confidence in model development.

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

Evaluating and Debugging Generative AI

10 ratings at Coursera

Learn to evaluate and debug generative AI using MLOps tools. Master experiment tracking, data versioning, and team collaboration with Weights & Biases platform for enhanced productivity in AI projects.

• Coursera
• 1 hour 30 minutes
• Self-Paced
• Paid Course

Weights & Biases

Learn to Use Weights & Biases

Master Weights & Biases for ML experiment tracking, model versioning, hyperparameter tuning, and integration with PyTorch, Keras, and Lightning frameworks.

• YouTube
• 2 hours 37 minutes
• Self-Paced
• Free Video

MLOps Concepts

29 ratings at DataCamp

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

• DataCamp
• 2 hours
• Self-Paced
• Free Trial Available

Introduction to MLflow

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Fully Automated MLOps

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Venelin Valkov

Reproducible Machine Learning and Experiment Tracking Pipeline with Python and DVC

Learn to build reproducible machine learning pipelines using Python and DVC. Track experiments, manage data versions, and compare model metrics for improved ML workflow efficiency.

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

NashKnolX

Databricks for MLOps - Experiment Tracking, Model Packaging, and Deployment

Master MLflow in Databricks: Experiment tracking, model packaging, and deployment for efficient machine learning operations.

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

Databricks

Advanced Experiment Tracking for LLM-Powered Applications with Customized Open-Source MLFlow

Discover Intuit's use of open-source MLFlow for enhancing ML models and LLM applications through experiment tracking, reproducibility, model lineage, and streamlined review workflows.

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

Weights & Biases

W&B Models End-to-End Demo - Complete ML Experiment Tracking and Model Management

Explore W&B Models for end-to-end ML lifecycle management, from training metrics and GPU monitoring to hyperparameter tuning, artifact tracking, and automated evaluations.

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

WestGrid

ML Experiment Tracking with MLflow

Discover how to track and manage machine learning experiments using MLflow for better reproducibility and model versioning in this hands-on training session.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

PyTorch for Deep Learning Bootcamp

5942 ratings at Udemy

Learn PyTorch. Become a Deep Learning Engineer. Get Hired.

• Udemy
• 2 days 4 hours 13 minutes
• Self-Paced
• Paid Course