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Explainable AI (XAI): Interpreting Machine Learning Models

Learn to build transparent, interpretable, and trustworthy AI systems with practical XAI techniques and tools.
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Course Duration: 10 Hours
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Explainable AI (XAI): Interpreting Machine Learning Models – Online Course
 
Explainable AI (XAI): Interpreting Machine Learning Models is a comprehensive, hands-on course designed for AI practitioners, data scientists, ML engineers, researchers, and business professionals who want to ensure transparency and accountability in their AI models. As artificial intelligence systems become increasingly embedded in high-stakes domains like finance, healthcare, law, and security, there’s a growing demand for explanations—models must not only be accurate but also interpretable and justifiable.
 
Explainable AI (XAI) refers to methods and techniques that make the behavior of machine learning models understandable to humans. It bridges the gap between the predictions of complex models (like deep neural networks or ensemble learners) and human comprehension. By demystifying the "black-box" nature of AI, XAI empowers stakeholders to trust, evaluate, and audit models effectively.
 
This course introduces you to the foundational concepts of interpretability and explainability, and then dives deep into practical, real-world techniques like SHAP, LIME, Integrated Gradients, counterfactuals, and saliency maps. You'll apply these techniques to popular models built with Scikit-learn, TensorFlow, PyTorch, and XGBoost. Case studies will highlight real-world implications and challenges of deploying explainable models in regulated environments.
 
 
How to Use This Course
 
To get the most from this course, follow this roadmap:
  1. Begin with the Foundations
    The initial modules lay the groundwork—covering the need for XAI, key regulatory and ethical considerations, and categories of interpretability (global vs. local).
  2. Learn by Doing
    You’ll work on multiple datasets (tabular, text, image) using real-world tools like SHAP, LIME, and Captum. Code along with the instructor and analyze each visualization deeply.
  3. Bridge Theory and Application
    Understand the “why” behind each technique: What does SHAP value mean? Why might LIME be misleading? This blend of theory and code is what sets this course apart.
  4. Document Your Insights
    Maintain a learning journal where you record observations from each explainability technique, their advantages, and limitations. This becomes valuable when presenting or defending your models.
  5. Use Case Studies Strategically
    The course includes case studies in healthcare, credit scoring, and legal AI. Use them to connect concepts to business impact and policy requirements.
  6. Experiment with Your Models
    Apply XAI to your personal or company projects. Test different techniques, compare results, and refine model transparency.
  7. Review and Reflect
    Interpretability is nuanced. Revisit visualizations and decisions periodically. Reflect on how XAI supports fairness, accountability, and ethical AI deployment.
Whether you're trying to comply with regulations like GDPR or you're aiming to build user trust in AI systems, this course gives you the tools, theory, and confidence to explain your models clearly and effectively.

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  • The videos for this course are being recorded freshly and should be available in a few days. Please contact info@uplatz.com to know the exact date of the release of this course.

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Course Objectives Back to Top
By the end of this course, learners will be able to:
 
  1. Understand the principles and motivations behind Explainable AI.
  2. Differentiate between black-box, gray-box, and white-box models.
  3. Apply SHAP, LIME, and permutation importance to interpret tabular models.
  4. Explain neural network decisions using saliency maps, Integrated Gradients, and Captum.
  5. Use counterfactuals and adversarial examples to analyze model robustness.
  6. Evaluate trade-offs between accuracy and interpretability in model selection.
  7. Interpret time-series and NLP models using attention and LIME for text.
  8. Communicate AI decisions clearly to stakeholders and non-technical users.
  9. Understand ethical, regulatory, and legal implications of model explainability.
  10. Incorporate XAI practices into the AI/ML lifecycle and MLOps pipelines.
Course Syllabus Back to Top
Course Syllabus
 
Module 1: Introduction to Explainable AI
  • What is XAI?
  • Why Interpretability Matters
  • Regulatory Context (GDPR, HIPAA, etc.)
  • Types of Explanations (Global vs. Local)
Module 2: Models and Interpretability Spectrum
  • Black-box vs. White-box Models
  • Interpretable Models: Linear, Decision Trees
  • Complexity vs. Transparency Trade-offs
Module 3: Feature Importance Techniques
  • Permutation Importance
  • Partial Dependence Plots (PDPs)
  • Accumulated Local Effects (ALE)
Module 4: Local Explanation Methods
  • LIME (Local Interpretable Model-agnostic Explanations)
  • SHAP (SHapley Additive exPlanations)
  • Comparing SHAP and LIME
Module 5: Explaining Tree-Based and Ensemble Models
  • SHAP for XGBoost and Random Forests
  • TreeExplainer
  • Real-world Case Study: Credit Risk Model
Module 6: Neural Networks and Deep Learning
  • Saliency Maps
  • Grad-CAM and Integrated Gradients
  • Using Captum with PyTorch
Module 7: NLP Model Explainability
  • LIME for Text Classification
  • Attention Mechanisms in Transformers
  • Explaining BERT with SHAP
Module 8: Counterfactuals and Adversarial Interpretations
  • What-if Analysis
  • Counterfactual Explanations
  • Adversarial Examples and Fairness
Module 9: Visualization Tools and Dashboards
  • Explainability Dashboards with Streamlit/Gradio
  • Visualizing SHAP Values
  • UX for Interpretability
Module 10: Ethics, Fairness, and Trust in AI
  • Bias Detection
  • Fairness Metrics and Visualization
  • Case Study: Healthcare Model Bias
Module 11: Explainability in MLOps
  • Integrating XAI into CI/CD pipelines
  • Model Monitoring and Drift Explanation
  • Scalable Interpretability in Production
Module 12–14: Capstone Projects
 
  • Image Classifier Transparency
  • Credit Scoring Risk Justification
  • Explainable NLP Chatbot
Certification Back to Top

Upon completing the course, learners will receive a Certificate of Completion from Uplatz, recognizing their expertise in Explainable AI techniques and tools. This credential validates your ability to interpret machine learning models, apply advanced XAI techniques like SHAP and LIME, and communicate insights clearly. It serves as a strong signal to employers, compliance teams, and research institutions that you understand both the technical and ethical dimensions of interpretable AI. The certificate enhances your credibility in AI governance, risk assessment, and fairness analysis, especially in industries where model transparency is critical.

Career & Jobs Back to Top
With growing regulations and ethical concerns surrounding AI, Explainable AI has become a mission-critical skill in organizations across sectors. Professionals with XAI expertise are increasingly sought after for roles such as:
  • AI/ML Research Scientist
  • Data Scientist (with Trustworthy AI focus)
  • Model Risk Analyst
  • Responsible AI Engineer
  • AI Governance Specialist
  • AI Product Manager
Industries like healthcare, banking, insurance, legal tech, and defense are adopting XAI to comply with laws and build user trust. As a certified XAI expert, you can contribute to ethical model development, create responsible AI frameworks, or even lead AI audit teams. Your skills will be invaluable not only in building models but also in defending them in front of regulators, stakeholders, and customers.
Interview Questions Back to Top
1. What is Explainable AI (XAI)?
Explainable AI refers to techniques that make the outputs and decisions of AI models understandable to humans. It aims to provide transparency, trust, and accountability in machine learning.
 
2. How does SHAP differ from LIME?
SHAP is based on game theory and provides consistent global and local explanations. LIME builds surrogate models locally. SHAP is more theoretically sound but computationally intensive.
 
3. What are global vs. local explanations?
Global explanations describe how a model behaves overall, while local explanations clarify individual predictions.
 
4. Why is model interpretability important in regulated industries?
Regulations like GDPR require explanations for automated decisions affecting individuals. Interpretability ensures compliance, trust, and risk mitigation.
 
5. What is a saliency map in neural networks?
A saliency map shows which pixels of an input image are most influential in a model’s decision, offering visual insights into convolutional neural networks.
 
6. What is permutation feature importance?
It evaluates feature importance by measuring how the model’s performance changes when a feature’s values are randomly shuffled.
 
7. What are counterfactual explanations?
They answer the question: “What minimal changes would have led to a different prediction?” Useful for fairness and transparency.
 
8. What’s the trade-off between accuracy and interpretability?
More accurate models like deep nets are often harder to interpret, while simpler models like decision trees are easier to explain but might be less accurate.
 
9. How does Captum help with explainability in PyTorch?
Captum is a library that provides interpretability algorithms like Integrated Gradients and DeepLIFT for PyTorch models.
 
10. Can XAI help detect model bias?
Yes. By exposing how models weigh features, XAI can reveal patterns of bias and discrimination, enabling corrective action.
Course Quiz Back to Top
Start Quiz
Q1. What are the payment options?
A1. We have multiple payment options: 1) Book your course on our webiste by clicking on Buy this course button on top right of this course page 2) Pay via Invoice using any credit or debit card 3) Pay to our UK or India bank account 4) If your HR or employer is making the payment, then we can send them an invoice to pay.

Q2. Will I get certificate?
A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php

Q3. How long is the course access?
A3. All our video courses comes with lifetime access. Once you purchase a video course with Uplatz you have lifetime access to the course i.e. forever. You can access your course any time via our website and/or mobile app and learn at your own convenience.

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A9. Overview courses are 1-2 hours short to help you decide if you want to go for the full course on that particular subject. Uplatz overview courses are either free or minimally charged such as GBP 1 / USD 2 / EUR 2 / INR 100

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A11. Bundle courses offered by Uplatz are combo of 2 or more video courses. We have Bundle up the similar technologies together in Bundles so offer you better value in pricing and give you an enhaced learning experience. Check all Bundle courses here https://training.uplatz.com/online-it-courses.php?search=bundle

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A12. Career Path programs are our comprehensive learning package of video course. These are combined in a way by keeping in mind the career you would like to aim after doing career path program. Career path programs ranges from 100 hours to 600 hours and covers wide variety of courses for you to become an expert on those technologies. Check all Career Path Programs here https://training.uplatz.com/online-it-courses.php?career_path_courses=done

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A13. Learning Path programs are dedicated courses designed by SAP professionals to start and enhance their career in an SAP domain. It covers from basic to advance level of all courses across each business function. These programs are available across SAP finance, SAP Logistics, SAP HR, SAP succcessfactors, SAP Technical, SAP Sales, SAP S/4HANA and many more Check all Learning path here https://training.uplatz.com/online-it-courses.php?learning_path_courses=done

Q14. What are Premium Career tracks?
A14. Premium Career tracks are programs consisting of video courses that lead to skills required by C-suite executives such as CEO, CTO, CFO, and so on. These programs will help you gain knowledge and acumen to become a senior management executive.

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Q16. Do you provide software access with video course?
A16. Software access can be purchased seperately at an additional cost. The cost varies from course to course but is generally in between GBP 20 to GBP 40 per month.

Q17. Does your course guarantee a job?
A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience. Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey!

Q18. Do you provide placement services?
A18. While our course is designed to provide you with a comprehensive understanding of the subject, we currently do not offer placement services as part of the course package. Our main focus is on delivering high-quality education and equipping you with essential skills in this field. However, we understand that finding job opportunities is a crucial aspect of your career journey. We recommend exploring various avenues to enhance your job search:
a) Career Counseling: Seek guidance from career counselors who can provide personalized advice and help you tailor your job search strategy.
b) Networking: Attend industry events, workshops, and conferences to build connections with professionals in your field. Networking can often lead to job referrals and valuable insights.
c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests.
d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin.
While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities.

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Q21. Can I get help from a tutor if I have doubts while learning from a video course?
A21. Tutor support is not available for our video course. If you believe you require assistance from a tutor, we recommend considering our live class option. Please contact our team for the most up-to-date availability. The pricing for live classes typically begins at USD 999 and may vary.
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