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SHAP (SHapley Additive exPlanations)

Learn SHAP from scratch to explain machine learning predictions, improve transparency, and build trust in AI with hands-on applications.
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Course Duration: 10 Hours
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SHAP – Explainable AI and Model Interpretability – Online Course
 
This SHAP (SHapley Additive exPlanations) course is a comprehensive program designed for data scientists, AI practitioners, and machine learning engineers who want to master the art of model explainability and interpretability. Whether you are working in regulated industries (finance, healthcare, insurance) or simply want to build trustworthy AI systems, this course will equip you with the skills to analyze, interpret, and visualize predictions of complex machine learning models.
 
What is SHAP?
 
SHAP is an advanced explainable AI technique based on cooperative game theory and Shapley values. It assigns each feature an importance value for a particular prediction, enabling you to break down how machine learning models arrive at their results. Unlike traditional feature importance methods, SHAP provides both global (overall model) and local (individual prediction) explanations, making it a gold standard for interpretable AI.
 
This course teaches you how to leverage SHAP for multiple ML models such as decision trees, random forests, gradient boosting (XGBoost, LightGBM), and deep learning models. You will learn to integrate SHAP with frameworks like Scikit-learn, TensorFlow, PyTorch, and XGBoost, and effectively visualize explanations to communicate insights to stakeholders.
 
How to Use This Course
 
To maximize learning:
  1. Start from Fundamentals: Begin with foundational modules covering explainable AI concepts and Shapley theory.
  2. Hands-on Practice: Follow along with coding examples, run SHAP visualizations, and analyze feature attributions in real-world datasets.
  3. Work on Projects: Implement SHAP in end-to-end ML pipelines and explain models in domains such as finance, healthcare, and NLP.
  4. Integrate into Workflow: Learn how to use SHAP for debugging ML models, improving fairness, and ensuring compliance with regulatory frameworks like GDPR and AI Act.
  5. Portfolio Building: By the end, you’ll build interpretable AI projects suitable for showcasing to employers or stakeholders.
By completing this course, you will understand how SHAP can bridge the gap between complex AI models and human interpretability, thus enabling better decision-making and trust in AI systems.

Course/Topic 1 - Coming Soon

  • 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, you will be able to:
 
  1. Understand the concept of Shapley values and their application in explainable AI.
  2. Implement SHAP with popular ML models (Tree-based, Linear, Deep Learning).
  3. Generate global feature importance and local explanations.
  4. Visualize SHAP outputs with force plots, dependence plots, and summary plots.
  5. Diagnose model biases and unfairness using SHAP explanations.
  6. Explain complex black-box models to non-technical stakeholders.
  7. Use SHAP to debug and improve machine learning models.
  8. Apply SHAP in real-world domains like healthcare, finance, and NLP.
  9. Integrate SHAP into ML pipelines and deployment workflows.
  10. Comply with AI governance and regulatory requirements for interpretability.
Course Syllabus Back to Top
Course Syllabus
 
Module 1: Introduction to Explainable AI
  • Importance of model interpretability
  • AI governance and compliance needs
  • Overview of interpretability techniques
Module 2: Fundamentals of Shapley Values
  • Game theory basics
  • From Shapley values to SHAP
  • Properties: Local accuracy, consistency, missingness
Module 3: Getting Started with SHAP
  • Installing and setting up SHAP
  • Explaining simple linear models
  • SHAP in Scikit-learn
Module 4: SHAP for Tree-Based Models
  • TreeExplainer for XGBoost, LightGBM, CatBoost
  • Global feature importance plots
  • Local explanations with force plots
Module 5: SHAP for Deep Learning Models
  • DeepExplainer in TensorFlow and PyTorch
  • Explaining CNNs and RNNs
  • Visualization of deep model explanations
Module 6: Visualizing SHAP Values
  • Summary plots (beeswarm plots)
  • Dependence and interaction plots
  • Decision plot analysis
Module 7: Debugging Models with SHAP
  • Identifying data drift and feature leakage
  • Detecting overfitting
  • Using SHAP for model refinement
Module 8: Fairness and Bias Detection
  • Using SHAP for bias detection
  • Fairness-aware AI modeling
  • Regulatory compliance checks
Module 9: SHAP for NLP and Text Models
  • Explaining transformer-based models
  • Token-level importance visualization
Module 10: Real-World Projects (Hands-On)
  • Healthcare: Explaining patient diagnosis models
  • Finance: Credit risk scoring interpretability
  • NLP: Sentiment classification explanations
Module 11: SHAP in Production
  • Integrating SHAP in MLOps workflows
  • Serving SHAP explanations via APIs
  • Deploying explainable models
Module 12: Advanced Topics
 
  • KernelExplainer for black-box models
  • SHAP with reinforcement learning models
  • Combining SHAP with LIME and AI 360
Certification Back to Top

Upon successful completion, learners will receive an industry-recognized Certificate of Completion from Uplatz. This certification validates expertise in explainable AI and SHAP-based interpretability techniques. It demonstrates a candidate’s ability to implement SHAP across machine learning models, generate actionable explanations, and ensure AI transparency. Such a certification is highly valued in industries like finance, healthcare, and regulated AI domains, where model accountability is critical. It enhances employability for roles in data science, ML engineering, AI governance, and compliance-focused AI development.

Career & Jobs Back to Top
SHAP skills are in high demand as companies adopt trustworthy and transparent AI practices. Professionals trained in SHAP can pursue roles such as:
  • Explainable AI Engineer
  • Data Scientist (AI Governance)
  • ML Engineer with Interpretability Specialization
  • AI Ethics and Compliance Specialist
  • Risk Modeling Analyst in Finance or Healthcare
Organizations like banks, insurance companies, healthcare providers, government agencies, and AI startups actively seek experts who can explain and validate complex models. Explainable AI is also becoming a regulatory requirement in many jurisdictions, positioning SHAP-trained professionals at the forefront of responsible AI adoption. Furthermore, SHAP knowledge is valuable for AI research roles, consulting positions, and senior-level data science jobs where interpretability is essential for stakeholder trust.
Interview Questions Back to Top
1. What is SHAP and why is it used in machine learning?
SHAP is an interpretability technique based on Shapley values from game theory that explains how each feature contributes to individual predictions, improving transparency and trust in AI models.
 
2. How does SHAP differ from traditional feature importance methods?
Unlike global feature importance, SHAP provides both global and local explanations, allowing interpretation of individual predictions.
 
3. What are the main types of SHAP explainers?
TreeExplainer (tree models), KernelExplainer (black-box models), and DeepExplainer (deep neural networks).
 
4. How do you interpret a SHAP summary plot?
It shows feature importance across the dataset and how feature values impact predictions. Colors indicate high/low feature values.
 
5. Can SHAP be used for deep learning models?
Yes, DeepExplainer supports TensorFlow and PyTorch to explain deep networks like CNNs and RNNs.
 
6. What is the difference between SHAP and LIME?
LIME approximates local behavior using simple surrogate models, while SHAP is theoretically grounded in Shapley values and ensures consistency.
 
7. How does SHAP help detect bias in models?
By analyzing SHAP values across sensitive features, bias and fairness issues can be identified and mitigated.
 
8. What are SHAP force plots used for?
They provide a visual explanation of how each feature pushes an individual prediction higher or lower.
 
9. How is SHAP integrated into model deployment?
By embedding SHAP in APIs or dashboards to provide real-time explanations alongside predictions in production.
 
10. In which industries is SHAP particularly important?
Finance, healthcare, insurance, and any domain where AI accountability, transparency, and compliance are critical.
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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A5. We do not take exam as part of the our training programs whether it is video course or live online class. These courses are professional courses and are offered to upskill and move on in the career ladder. However if there is an associated exam to the subject you are learning with us then you need to contact the relevant examination authority for booking your exam.

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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

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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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