SHAP Courses and Certifications

DigitalSreeni

Understanding Model Predictions with SHAP - XGBoost vs Neural Networks

Discover how SHAP explains machine learning predictions using game theory concepts, comparing XGBoost and neural networks on breast cancer data for interpretable AI decisions.

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

SF Python

Beyond the Black Box - Interpreting ML Models with SHAP

Discover how SHAP uses game theory to interpret ML model predictions, making black box algorithms explainable through feature importance attribution and practical case studies.

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

Coursera

Validate and Explain Your ML Models

Master ML model validation using k-fold cross-validation, stratified sampling, and SHAP to explain decisions clearly for responsible deployment in domains like fraud detection.

• Coursera
• 2 hours 30 minutes
• Self-Paced
• Paid Course

Explainable AI in Python

Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.

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

Explainable Artificial Intelligence (XAI) Concepts

Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.

• DataCamp
• 1 hour
• Self-Paced
• Free Trial Available

1littlecoder

What is Interpretable Machine Learning - ML Explainability - with Python LIME Shap Tutorial

Explore interpretable machine learning with Python, covering LIME and SHAP techniques for explainable AI. Learn why ML explainability matters and how to implement it in your projects.

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

1littlecoder

Understanding SHAP Summary Plot - Interpretable Machine Learning - Day 19

Explore SHAP and Shapley values for interpretable machine learning, focusing on summary plots and dependence plots to enhance model explainability and insights.

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

Association for Computing Machinery (ACM)

Probing ML Models for Fairness with the What-if Tool and SHAP

Explore ML model fairness using What-if Tool and SHAP. Learn to analyze and visualize model behavior, detect biases, and understand feature importance for responsible AI development.

• YouTube
• 56 minutes
• Self-Paced
• Conference Talk

1littlecoder

SHAP and Shapley Values for Interpretable Machine Learning - Kaggle 30 Days of ML Day 18

Explore SHAP and Shapley Values for interpretable machine learning. Learn local interpretation techniques, Python implementation, and visualization methods for explainable AI.

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

Mitigating Bias in Models with SHAP and Fairlearn

Learn techniques to identify and mitigate bias in machine learning models using SHAP and Fairlearn, enhancing fairness and transparency in AI systems.

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

NashKnolX

Interpretable Machine Learning: Understanding Black-Box Models with SHAP and LIME

Discover essential techniques for making complex ML models transparent, from SHAP to LIME, and learn to explain predictions, detect biases, and build trustworthy AI systems through practical demonstrations.

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

Explainable Machine Learning (XAI)

27 ratings at Coursera

Develop transparent and trustworthy AI solutions using explainable machine learning techniques. Implement local and global explainability methods, visualize neural networks, and explore emerging approaches for large language models.

• Coursera
• 14 hours 48 minutes
• Self-Paced
• Paid Course

AI for Business - AI Applications for Business Success

3159 ratings at Udemy

Learn how to leverage the power of AI to solve your business objectives

• Udemy
• 2 hours 15 minutes
• Self-Paced
• Paid Course

Coursera Credential

Building Trustworthy AI

11 ratings at Coursera

Master comprehensive AI security, ethics, and governance frameworks to build resilient, transparent systems that align with human values and enterprise standards.

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

Coursera

Building and Optimizing AI Agent Workflows

Master autonomous AI agent design with reinforcement learning, ethical frameworks, modular architectures, and optimization techniques for production-ready systems.

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