Model Interpretability Courses and Certifications

Association for Computing Machinery (ACM)

Model Explanations with Differential Privacy

Explore techniques for generating privacy-preserving explanations of machine learning models, balancing transparency with data protection in AI systems.

• YouTube
• 15 minutes
• On-Demand
• Conference Talk

NDC Conferences

ML BuzzWords Demystified

Demystifies latest ML trends like Reinforcement Learning, AutoML, and ML bias. Provides clear insights into complex concepts, ensuring you're up-to-date with the field's advancements.

• YouTube
• 53 minutes
• On-Demand
• Conference Talk

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
• On-Demand
• Free Video

GOTO Conferences

Ethical ML - Who's Afraid of the Black Box Models

Explore ethical machine learning beyond interpretability, focusing on responsible data handling and fairness testing to meet GDPR and ALTAI guidelines while using black-box models.

• YouTube
• 39 minutes
• On-Demand
• Conference Talk

Institute for Pure & Applied Mathematics (IPAM)

Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics

Explore machine learning for nonlinear dynamical systems modeling, focusing on the SINDy algorithm and its applications in fluid dynamics, with emphasis on interpretable and physics-respecting solutions.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Explainable Structured Machine Learning in Similarity, Graph and Transformer Models

Explores techniques for explaining complex machine learning models, focusing on similarity, graph, and transformer structures. Discusses applications in knowledge evolution, gender bias, and task-solving.

• YouTube
• 53 minutes
• On-Demand
• Free Video

EuroPython Conference

Trust Me, I'm a Data Scientist - Ethics for Builders of Data-Based Applications

Explore ethical pitfalls in data science through a practical example, covering algorithmic fairness, model interpretability, and handling minority classes in AI applications.

• YouTube
• 25 minutes
• On-Demand
• Conference Talk

Responsible AI for Developers: Interpretability & Transparency

Explore AI interpretability and transparency techniques, including feature-based explanations and practical tools, to enhance responsible AI development and implementation.

• Google Cloud Skills Boost
• 3 hours
• On-Demand
• Paid Course

Troubleshooting and Improving Neural Network Performance

This course will teach you neural network troubleshooting and performance tuning from a data scientist's perspective.

• Pluralsight
• 1 hour 33 minutes
• On-Demand
• Free Trial Available

Amazon Web Services;  Amazon

AWS ML Engineer Associate 2.1 Choose a Modeling Approach

Explore AWS ML stack, SageMaker, and pre-trained solutions for optimal model selection. Learn to choose algorithms and interpret results for efficient problem-solving in machine learning.

• AWS Skill Builder
• 1 hour 30 minutes
• On-Demand
• Paid Course

IEEE

SHERPA: Explainable Robust Algorithms for Privacy-Preserved Federated Learning in Future Networks

Explore robust algorithms for privacy-preserved federated learning in future networks, focusing on explainable and secure data collaboration techniques.

• YouTube
• 15 minutes
• On-Demand
• Free Video

OSACon

Making AI Truly Open Source - Challenges and Solutions

Explore the complexities of truly open-source AI, examining transparency challenges, data attribution issues, and practical solutions for creating genuinely open AI systems.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Data Science Conference

AI Operations: Evolution, Challenges and Solutions in Modern IT Infrastructure

Explore the evolution and implementation challenges of AI Ops, from historical Big Data solutions to modern artificial intelligence integration in IT operations management and workflow optimization.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Data Science Conference

Revealing the Unseen: Visualizing Attention in Transformer Models

Dive into the visualization techniques of attention mechanisms in Transformer models, understanding their inner workings and practical applications through expert insights.

• YouTube
• 24 minutes
• On-Demand
• Free Video

IIIA Hub

A Journey Towards Explainable AI and Its Societal Implications - From Trust Issues to Complex Models

Explore the principles of explainable AI, from feature-based to data-driven models, examining key algorithms like LIME and Shapley while understanding their broader societal impact and applications in search systems.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Video