Responsible & Ethical AI

To integrate ethical frameworks, governance principles, and responsible AI practices, enabling learners to design, develop, and deploy AI systems that are fair, transparent, accountable, and compliant with global standards.

Program Objective

To integrate ethical frameworks, governance principles, and responsible AI practices, enabling learners to design, develop, and deploy AI systems that are fair, transparent, accountable, and compliant with global standards.

Key Features

Learn Complete AI & ML Skillsets
Build strong foundations in Python, data preprocessing, ML algorithms, deep learning, and model deployment — all in one internship.
Build Real AI/ML Projects
Work on practical projects such as prediction models, neural networks, image classification, NLP-based tools, and end-to-end ML pipelines.
Mentorship from Industry AI Professionals
Learn directly from experienced ML engineers and data scientists working on production-grade AI systems.
Beginner-Friendly with Progressive Advancement
Start with the basics and move toward advanced ML & DL concepts, making it suitable for students from all engineering branches.

Program Outcomes

Topics Covered:

  1. Introduction to Artificial Intelligence & Societal Impact

  2. What is Responsible AI? Why It Matters

  3. History of AI Ethics & Major AI Failures (Case Studies)

  4. Core Principles:

    • Fairness

    • Transparency

    • Accountability

    • Privacy

    • Safety

  5. Human-Centered AI Design

  6. Ethical Theories in Technology (Utilitarianism, Deontology, etc.)

  7. AI Risk Landscape & Emerging Concerns

Topics Covered:

  1. Types of Bias in AI:

    • Data Bias

    • Algorithmic Bias

    • Selection Bias

    • Historical Bias

  2. Fairness Metrics & Evaluation Techniques

  3. Bias Detection Tools & Techniques

  4. Bias Mitigation Strategies:

    • Pre-processing methods

    • In-processing techniques

    • Post-processing adjustments

  5. Inclusive AI Design Practices

  6. Case Studies in Hiring, Lending & Healthcare AI

Topics Covered:

  1. Importance of Explainable AI (XAI)

  2. Black Box vs White Box Models

  3. Model Interpretability Concepts

  4. Explainability Techniques:

    • LIME

    • SHAP

    • Feature Importance

  5. Documentation & Model Cards

  6. Communicating AI Decisions to Non-Technical Stakeholders

  7. Building Trust in AI Systems

Topics Covered:

  1. Data Privacy Principles

  2. Personally Identifiable Information (PII)

  3. Data Minimization & Consent

  4. Privacy-Preserving Techniques:

    • Anonymization

    • Differential Privacy

    • Encryption

  5. Global Regulations Overview:

    • GDPR

    • EU AI Act (Overview)

    • Data Protection Frameworks

  6. AI Security Risks & Adversarial Attacks

  7. Responsible Data Governance

Topics Covered:

  • AI Governance Frameworks

  • Ethical AI Policies & Guidelines

  • AI Risk Management Frameworks

  • Model Risk Management (MRM)

  • Internal AI Audit Practices

  • Human-in-the-Loop Systems

  • Incident Response & Ethical Escalation

  • Responsible AI Lifecycle Management

  • Select an AI use case (Healthcare / Finance / HR / Retail etc.)

  • Conduct ethical risk assessment

  • Perform bias analysis

  • Apply explainability techniques

  • Develop governance & compliance strategy

  • Submit a Responsible AI Implementation Report

Learning Outcome:

Demonstrate industry-ready expertise in implementing responsible AI systems.

Tools & Softwares

Salary Scale

Maximum
35 LPA
Average
20 LPA
Minimum
10 LPA

Career Roles

FAQ's

Yes. You'll receive VTU-compliant certificates and documentation.

No. The program starts from fundamentals and scales gradually.

Prediction models, CNN-based classifiers, NLP applications, and a full ML pipeline.

Yes — resume, LinkedIn, GitHub, mock interviews & job guidance.

Offered in both offline and hybrid formats.

Yes, you will receive a verified completion certificate from Rooman Technologies upon meeting all requirements.

CSE, ISE, AIML, ECE, EEE, Civil, Mechanical and all final-year VTU students.

Python, Scikit-learn, TensorFlow, Pandas, Kaggle workflows, cloud ML basics.

Contact Us

Have questions about our programs or need guidance? Reach out to us and we’ll be happy to help.

Email Us

online@rooman.net

Call Us

080 6945 1000

Send us a Message

Contact Us

Have questions about our programs or need guidance? Reach out to us and we’ll be happy to help.

Email Us

online@rooman.net

Call Us

080 6945 1000

Send us a Message


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