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DI05016021 · Semester 5 · 5G scheme

AI Product Design

Notes and solutions following the Gujarat Technological University (GTU) syllabus for DI05016021. Independent material — not issued by the university.

Information Technology

Materials

Syllabus

The official syllabus this material follows.

  • Syllabus

    8 pages

    FreeRead

Complete Book

The whole syllabus, unit by unit, written for the exam.

Syllabus units

Unit 1: Fundamentals of AI Products & Emerging AI Systems
  • Introduction to AI products
  • Difference between AI tool and AI product
  • Components of AI systems
  • Overview of Generative AI
  • Introduction to Large Language Models (LLMs)
  • Types of AI models: Text, Image, Speech, Embeddings (conceptual overview only)
  • Generative AI vs Analytical AI
  • AI model selection for product use
  • Introduction to Multi-Agent AI (basic idea and applications)
  • Human-in-the-loop systems
  • Basic AI system architecture (conceptual diagram)
Unit 2: Design Thinking & Human-Centred AI
  • Introduction to Design Thinking
  • Empathy Mapping
  • User Persona Development
  • Problem Statement Writing
  • Customer Journey Mapping
  • UX principles for AI systems
  • Human-AI interaction design
  • Bias in AI systems (basic understanding)
  • Explainable AI (conceptual overview)
Unit 3: AI Product Strategy & OpenAI Integration
  • Product lifecycle management
  • Minimum Viable Product (MVP)
  • Feature prioritization
  • AI monetization models (SaaS, API-based, subscription)
  • Business Model Canvas
  • Introduction to API concept
  • Understanding AI APIs (e.g., OpenAI API - concepts only)
  • Basic API key and security awareness
  • Cost awareness in AI products (token concept)
  • Basic AI evaluation methods
Unit 4: AI in Social Media & Digital Experience
  • AI in content creation
  • AI recommendation systems (concept)
  • AI chatbots for customer service
  • AI-driven ad targeting (concept)
  • Virtual influencers and AI avatars
  • Risks in Social Media AI
  • AI Tools & Prototyping
Unit 5: Privacy, Data Governance & Responsible AI
  • Data privacy concepts
  • Personal vs. sensitive data
  • Data lifecycle in AI systems
  • Data minimization principle
  • Data anonymization (basic concept)
  • Transparency and user consent
  • Responsible AI principles
  • Overview of Indian data protection law (basic idea)
  • Basic AI governance principles (organizational level overview)
Unit 6: AI Threats & Mitigation Strategies
  • AI Threats
  • Mitigation Strategies

About this course

Study materials, question papers, and solutions for AI Product Design (DI05016021) - Information Technology, Semester 5