Explainable AI
Make Machine Learning Models Interpretable, Transparent, and Accountable 30+ hours of hands-on training.

30+
Hours
8
Modules
14
Topics
Beginner-Friendly
Level
New
Batches weekly
About Explainable AI
Make Machine Learning Models Interpretable, Transparent, and Accountable
In this course, you will: Distinguish between interpretable models and post-hoc explanation methods; Apply SHAP values for global and local feature importance across model types; Use LIME for instance-level explanations of black-box classifiers and regressors.
What This Training Covers
The Explainable AI programme at Tutorsbot spans 30+ hours across 8 structured modules. Every module is built around hands-on projects and real-world scenarios — not slide-heavy theory. Your instructor walks you through each concept with live demonstrations, code reviews, and practical exercises so you can apply what you learn from day one. The curriculum is aligned with current Technology Training industry expectations and hiring patterns.
Enrollment & Training Quality
Explainable AI is available in 2 flexible learning modes — choose online live classes, classroom, hybrid, self-paced, or one-on-one depending on your schedule. Every batch is limited in size to ensure each learner receives personal attention, code-level feedback, and doubt resolution. Career support and certification are included with every enrolment. Tutorsbot instructors are working professionals who teach from delivery experience, and the training standard stays consistent across all modes and batches.
Course Curriculum
8 modules · 14 topics · 30 hrs
01Interpretability Fundamentals
7 topics
Interpretability Fundamentals
7 topics
- Why explainability matters — Trust, debugging, compliance, and safety
- Interpretability vs explainability — Scope and meaning distinction
- Model complexity spectrum — Linear models to deep neural networks
- Global vs local explanations — Population-level vs single-prediction insights
- Intrinsic vs post-hoc interpretability — Model design vs explanation after training
- Model-agnostic vs model-specific methods — Coverage and trade-offs
- Explanation quality criteria — Fidelity, consistency, completeness, and stability
02Interpretable Models
7 topics
Interpretable Models
7 topics
- Linear and logistic regression — Coefficient interpretation and confidence intervals
- Decision trees — Rule extraction, depth constraints, and visualization
- Rule-based models — RuleFit and decision rule lists for human-readable policies
- Generalized additive models (GAMs) — Shape functions and interaction terms
- EBMs — Explainable Boosting Machines with interaction detection
- Monotonic constraints — Enforcing business logic in gradient boosting models
- When to favor interpretable models over black-box alternatives
SHAP — Shapley Additive Explanations
0 topics
5 more modules available
Enter your details to unlock the complete syllabus
Enrol in This Course
Same curriculum & certification across all formats. Updated Apr 2026.
Online Live
Save ₹2,500Live instructor-led sessions from anywhere, with recordings for catch-up.
EMI from ₹2,083/mo
or
What You Get After Completion
Every graduate receives a verified certificate, a portfolio of real projects, and dedicated career support.
Verified Certificate
Digitally signed with a permanent shareable link — not just for attendance.
LinkedIn-importable·Permanent URL·PDF download
Project Portfolio
Real, deployable projects reviewed by your instructor — ready for interviews.
Instructor-reviewed·GitHub-hosted·Interview-ready
Career Support
Résumé review, mock interviews, LinkedIn guidance, and employer introductions.
1-on-1 coaching·Mock interviews·Employer connect
Meet Your Instructor
Every Explainable AI batch is led by a practitioner who teaches from production experience, not textbooks.
Industry Expert
Senior Technology Professional
Senior professionals with substantial hands-on delivery experience at top companies, bringing real-world projects, industry insights, and best practices.
How We Teach
- Concepts start with a real problem so theory lands in context
- Projects reviewed the way a senior colleague reviews pull requests
- Every topic includes the kind of questions you'll face in interviews
Hire Explainable AI Talent from Tutorsbot
Companies hiring Explainable AI talent from Tutorsbot receive pre-assessed profiles backed by project work, instructor review, and interview-ready candidates who can explain what they built and why.
Why hire from us
Project repositories with documented technical decisions
Assessment outcomes backed by instructor context
Candidate readiness shaped by interview-style practice
Project-based portfolios available
Frequently Asked Questions
Everything you need to know about Explainable AI, answered by our training experts
1Who should take Explainable AI?
2Does Explainable AI include a certificate?
3Is placement support included with Explainable AI?
4How long does Explainable AI take to complete?
5What is the mode of delivery for Explainable AI?
6Can I get a free demo class for Explainable AI?
7What kind of projects will I work on in Explainable AI?
8What if I miss a class?
9Is Explainable AI worth it for experienced professionals?
10What is the refund policy for Explainable AI?
11Do you offer corporate or group training?
12How are the instructors selected at Tutorsbot?
13Will I get lifetime access to Explainable AI materials?
14Can I switch between batch timings?
15What support do I get after completing the course?
Still have questions?
Technology Training