Explainable AI Courses and Certifications

Coursera

Interpretable Machine Learning Applications: Part 1

102 ratings at Coursera

Learn to create interpretable machine learning applications using decision trees and random forests. Gain insights into feature importance and model behavior for more accountable and trusted ML applications.

• Coursera
• 1 hour 40 minutes
• Self-Paced
• Paid Course

Career Certificate

Informed Clinical Decision Making using Deep Learning

36 ratings at Coursera

Explore deep learning applications in Electronic Health Records, focusing on data mining, predictive analytics, explainable models, and clinical decision support systems for healthcare.

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

Explainable deep learning models for healthcare - CDSS 3

15 ratings at Coursera

Explore interpretability and explainability in machine learning for healthcare, covering global and local methods, state-of-the-art techniques, and attention mechanisms in deep learning models.

• Coursera
• 1 day 6 hours 5 minutes
• Self-Paced
• Paid Course

Clinical Decision Support Systems

Explore key concepts in Clinical Decision Support Systems, including ML evaluation, fairness assessment, decision curve analysis, explainability, and privacy concerns in deep learning models.

• Coursera
• 8 hours
• Self-Paced
• Paid Course

Capstone Assignment

Apply explainable AI techniques—LIME, Grad-CAM, and permutation importance—on real MIMIC-III clinical data to build transparent, trustworthy deep learning models for healthcare decision support.

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

Capstone Assignment - CDSS 5

This course is a capstone assignment requiring you to apply the knowledge and skill you have learnt throughout the specialization. In this course you will choose one of the areas and complete the assignment to pass.

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

Artificial Intelligence

57 ratings at Coursera

Explore AI's business applications, machine learning techniques, and industry impact. Gain insights into AI systems, market trends, and ethical considerations for informed decision-making in the AI-driven business landscape.

• Coursera
• 2 days 10 hours 34 minutes
• Self-Paced
• Paid Course

Copilot Best Practices, Ethics and Regulatory Implications

34 ratings at Coursera

Explore ethical AI use, optimize Copilot, and navigate legal complexities. Gain skills in responsible AI implementation, bias mitigation, and regulatory compliance for generative AI tools.

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

Coursera

Interpretable machine learning applications: Part 3

30 ratings at Coursera

Learn to generate explanations for AI predictions using similar cases, enhancing model interpretability and decision-making in business contexts like loan approvals.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Coursera

Interpretable Machine Learning Applications: Part 2

28 ratings at Coursera

Develop interpretable machine learning applications using LIME to explain individual predictions, enhancing model transparency and accountability for data scientists and decision-makers.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Coursera

Interpretable Machine Learning Applications: Part 4

25 ratings at Coursera

Explore interpretable machine learning using Google's What-If Tool. Learn to analyze and visualize prediction model behavior for white wine quality classification using Decision Trees and Random Forests.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Fractal Analytics

Responsible AI - Principles and Ethical Considerations

24 ratings at Coursera

Explore ethical AI principles, from fairness to privacy. Learn to mitigate bias, ensure transparency, and implement accountability in AI systems for responsible development and deployment.

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

Clemson University

Human-Centered Artificial Intelligence

20 ratings at Coursera

Explore the intersection of AI and humanity in this comprehensive program covering ethics, design thinking, and practical applications of human-centered artificial intelligence systems.

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

Responsible AI for Developers: Interpretability & Transparency

13 ratings at Coursera

Explore AI interpretability and transparency techniques, gaining practical skills to enhance data and model clarity for responsible AI development.

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

Fred Hutchinson Cancer Center

Avoiding AI Harm

12 ratings at Coursera

Explore ethical considerations and mitigation strategies for responsible AI use and development. Learn from real-world examples to make informed decisions about AI implementation in various fields.

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