LIME Courses and Certifications

Explainable Machine Learning (XAI)

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 43 minutes
• On-Demand
• Free Online Course (Audit)

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
• On-Demand
• Free Online Course (Audit)

Guided Project: Predict World Cup Soccer Results with ML

In this beginner-friendly, hands-on guided project, develop your data science and machine learning skills in under an hour by building a prediction model for the 2022 FIFA World Cup. Perfect for anyone interested in learning more about prediction models.

• edX
• 1 week
• On-Demand
• Free Online Course (Audit)

Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions

121 ratings at LinkedIn Learning

Learn best practices for how to produce explainable AI and interpretable machine learning solutions.

• LinkedIn Learning
• 2 hours 10 minutes
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Video

Prodramp

Apply LIME to Explain, Trust, and Validate Your Predictions for Any ML Model

Learn to implement LIME for explaining ML model predictions, with hands-on exercises using image classification models and custom Python implementations.

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

BruCON Security Conference

Ant-Forensics AF - Dual Core

Explore anti-forensics techniques for Windows, Linux, and Android, covering memory analysis, encryption, and hardware implants. Learn to protect digital evidence and understand forensic challenges.

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

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

Data Council

How to Interpret and Explain Black Box Models

Explore popular model explanation techniques for machine learning interpretability, including LIME, SHAP, and visual analytics. Gain insights into making complex models more understandable and explainable.

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

NPTEL-NOC IITM

Overview of Cement Chemistry and Concrete Performance: Quality Control and Composition

Explore cement chemistry, production, and quality control, from historical binding materials to modern clinker composition and appearance.

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

Explainable Machine Learning with LIME and H2O in R

58 ratings at Coursera

Learn to use LIME and H2O packages in R for interpretable machine learning with Coursera Project Network. Build classification models and interpret predictions. Prior R programming experience recommended.

• Coursera
• 2 hours 10 minutes
• Finished
• Paid Course

Machine Learning Interpretable: interpretML y LIME

Learn to create interpretable Machine Learning models with techniques like interpretML and LIME on Coursera Project Network. Understand prediction reasoning.

• Coursera
• 2 hours 5 minutes
• Finished
• Paid Course