Explainable AI (XAI) Course

SKU: 3786
12 Lesson
|
40 Hours
Explainable AI (XAI) Course by igmGuru helps you understand how machine learning and deep learning models generate predictions and how those decisions can be interpreted, validated, and trusted. As organizations face increasing demands for AI transparency, fairness, and regulatory compliance, XAI has become a critical skill for AI professionals. This training covers SHAP, LIME, feature attribution methods, bias detection, model auditing, and responsible AI practices, enabling you to explain model behavior and build trustworthy AI solutions for real-world applications.

Overview

Prerequisites

  • Python Programming
  • NumPy and Scikit-learn
  • Machine Learning Fundamentals
  • Supervised Learning Models
  • Basic Neural Networks
  • Linear Algebra
  • Probability and Statistics

What Will You Learn

  • Explainable AI (XAI) Fundamentals
  • Model Interpretability Techniques
  • Global and Local Explanations
  • SHAP Explanations
  • LIME Explanations
  • Feature Importance Analysis
  • Partial Dependence Plots (PDP)
  • Bias Detection and Fairness Evaluation
  • Explainability for Machine Learning Models
  • Explainability for Deep Learning Models
  • Model Auditing and Transparency
  • Responsible AI and Governance

Who Should Do This Course

  • Data Scientists
  • Machine Learning Engineers
  • AI Engineers
  • Data Analysts
  • AI Researchers
  • Deep Learning Engineers
  • MLOps Engineers
  • AI Product Managers
  • Risk and Compliance Professionals
  • AI Software Engineers

Key Features

Course Curriculum

1. Explainable AI Fundamentals
2. Interpretability vs Explainability
3. Trustworthy AI Principles
1. Supervised Learning Models
2. Decision Trees and Random Forests
3. Neural Network Basics
1. Global Interpretability
2. Local Interpretability
3. Model-Agnostic Methods
1. Feature Importance Techniques
2. Permutation Importance
3. Feature Contribution Analysis
1. Shapley Values
2. SHAP Visualizations
3. Model Prediction Explanations
1. LIME Fundamentals
2. Local Prediction Analysis
3. Interpretable Surrogate Models
1. Partial Dependence Plots (PDP)
2. Individual Conditional Expectation (ICE) Plots
3. Explanation Dashboards
1. Saliency Maps
2. DeepLIFT
3. Layer-wise Relevance Propagation (LRP)
1. Bias Detection Techniques
2. Fairness Metrics
3. Responsible AI Evaluation
1. Text Classification Explanations
2. Attention Mechanisms
3. Transformer Model Interpretability
1. Image Model Explanations
2. Visual Attribution Methods
3. Object Recognition Interpretability
1. AI Ethics
2. Regulatory Compliance
3. Explainable AI Best Practices
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Course Fees

Online Class Room Program

US $ 799.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 Jun 2026
  • Weekday Batch 29 Jun 2026
  • Weekend Batch 04 Jul 2026

1 ON 1 Training

US $ 899.00
100% Money Back Guarantee
  • Duration : 40 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 28 Jun 2026
  • Weekday Batch 29 Jun 2026
  • Weekend Batch 04 Jul 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support

Trusted By Top Companies Worldwide

MITSUBISHI
Emirates
BECHTEL
Tech Mahindra
Techmill
metacube
Fareportal
Trelleborg
Capgemini
AU Small Finance Bank
United Nations
Inter Mid
SoftFlex
align
utthunga
Rimini Street
EJADAH
Yash Technologies
suyati
Hettich
APPCINO

Want to know Today's Offer

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Explainable AI (XAI) Certification Training

After completing the Explainable AI (XAI) Course and practical exercises, learners receive a Course Completion Certificate from igmGuru. This certification validates your ability to interpret machine learning models, apply explainability techniques such as SHAP and LIME, analyze feature importance, evaluate model fairness, and implement responsible AI practices in real-world AI and data science projects

Explainable AI (XAI) Certification Training

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