Responsible AI - A Hands-On Approach
AI is a double-edged sword—learn to build trustworthy, fair, safe and secure AI systems while balancing innovation with accountability.
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Course overview
You’ll become a Responsible AI champion—able to build, evaluate and advocate
- Ability to clearly communicate Responsible AI principles to both internal and external stakeholders
- Understand Evaluation Metrics and Frameworks
- Gain hands-on experience with practical tools and frameworks to build Responsible Gen AI applications
Who is this course for
01
Gen AI Practitioners who want to understand and apply Responsible AI principles in real-world systems
02
Product and Engineering Managers who want to drive innovation while embedding Responsible AI
03
Security, Risk, and Compliance professionals or advisors helping organizations manage risks and adopt Responsible AI in Gen.AI systems
What you’ll get out of this course
Understand and apply Responsible AI principles specifically tailored to Generative AI systems.
Identify and use evaluation metrics to assess alignment with key Responsible AI principles (e.g., hallucinations, fairness, bias, safety)
Gain hands-on experience with industry-standard tools and frameworks(such as NIST RMF) to build Responsible AI applications.
What’s included
Live sessions
Learn directly from Bhaskarjit Sarmah & Babul Kamireddy in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
Week 1
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Difference between Gen.AI and traditional AI/ML in the context of Responsible AI
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Responsible AI principles and driving factors
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Explore industry standards, including NIST Responsible AI Principles.
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Overview of tools and frameworks for implementing Responsible AI.
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Understand the importance of reliability in AI systems.
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Major reliability factors such as Hallucinations
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Learn how to select a evaluation metrics and detect and mitigate
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Hands-on practice: Implement strategies to enhance AI reliability
Foundations of Responsible AI
Reliability and Hallucinations
Week 2
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Identify sources and types of biases in AI systems.
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Learn strategies to detect and mitigate biases.
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Hands-on practice: Apply bias detection and mitigation techniques
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Define and their significance in AI systems.
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Learn techniques to explain, interpret LLM applications
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Hands-on practice: Implement methods to explain, interpret model outputs.
Fairness and Bias
Transparency, Explainability and Interpretability
Week 3
- 📄
Understand the importance of robustness in AI systems.
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Learn how to detect and mitigate issues like unsafe content
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Hands-on practice: Implement strategies to enhance AI robustness and safety
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Explore the AI security threat landscape and potential vulnerabilities
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Understand security&privacy considerations in AI applications.
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Hands-on practice: Implement measures to protect AI systems
Robustness and Safety
Security and Privacy
Week 4
- 📄
Define accountability in AI development and deployment
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Learn how to establish governance frameworks for Responsible AI
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Analyze few real-world case studies of AI successes and failures.
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Guest Speaker :Understand real-world case from the industry experts
Accountability and Governance
Case Studies & Guest Speaker
Meet your instructor
Bhaskarjit Sarmah
Bhaskarjit Sarmah
Recognized as a Top 5 Gen AI Leader in India
- 10+ years of corporate experience in AI and Machine Learning. Have led AI teams at BlackRock.
- Top 5 Gen AI Leader (India) award recipient and also received NASSCOM AI Game Changer Award
- Passionate educator, having taught ~12,000 learners across both online and offline platforms including institutes like MIT, NYU, JHU etc.
- Research interests: Responsible AI and Generative AI
Babul Kamireddy
Babul Kamireddy
- 20 years of my career has mirrored the industry analytics maturity evolving from Business Intelligence to Artificial Intelligence, including Generative AI and Trustworthy/Responsible AI.
- As a director at a large regulatory body in US, I have led and implemented many AI and Data analytics programs to bring efficiencies into their regulatory operations.
- I am a technologist and a storyteller who communicates complex concepts in plain English.
Course schedule
4-6 hours per week
Wednesday
9 PM - 11 PM EST
Saturday
11: AM - 1 PM EST
Learning is better with cohorts
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive
You’ll be interacting with other learners
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you