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DI05016011 · Semester 5 · 5G scheme

Artificial Intelligence with Prompt Engineering

Notes and solutions following the Gujarat Technological University (GTU) syllabus for DI05016011. Independent material — not issued by the university.

Information Technology

Materials

Syllabus

The official syllabus this material follows.

  • Syllabus

    7 pages

    FreeRead

Complete Book

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

Syllabus units

Unit 1: Foundations of Artificial Intelligence and Generative AI
  • 1.1.1 Definition and history of AI
  • 1.1.2 AI vs Machine Learning vs Deep Learning
  • 1.2.1 Narrow AI vs General AI
  • 1.3.1 AI in daily life
  • 1.3.2 AI in education
  • 1.3.3 AI in healthcare
  • 1.3.4 AI in cybersecurity
  • 1.4.1 Concept of Generative AI
  • 1.4.2 Types of Generative AI systems
  • 1.4.3 Text generation, Image generation, Code generation
  • 1.5.1 ChatGPT
  • 1.5.2 Google Gemini
  • 1.5.3 DALL·E
  • 1.6.1 Concept of NLP
  • 1.6.2 Role of NLP in chatbots and LLMs
Unit 2: Basics of Large Language Models (LLMs)
  • 2.1.1 Concept of LLMs
  • 2.1.2 Training data and parameters
  • 2.2.1 Tokens
  • 2.2.2 Embeddings (conceptual)
  • 2.2.3 How LLM predicts the next word
  • 2.3.1 GPT models
  • 2.3.2 Claude
  • 2.3.3 LlaMA
  • 2.3.4 Gemini
  • 2.4.1 Hallucination problem
  • 2.4.2 Context window limitations
  • 2.4.3 Bias in AI systems
Unit 3: Prompt Engineering Fundamentals
  • 3.1.1 Definition and importance
  • 3.1.2 Prompt lifecycle
  • 3.2.1 Instruction
  • 3.2.2 Context
  • 3.2.3 Input data
  • 3.2.4 Output format
  • 3.3.1 Zero-shot prompting
  • 3.3.2 Few-shot prompting
  • 3.3.3 Role-based prompting
  • 3.3.4 Instruction prompting
  • 3.4.1 Writing effective prompts
  • 3.4.2 Prompt testing and evaluation
Unit 4: Prompt Engineering Techniques
  • 4.1.1 Chain-of-Thought prompting
  • 4.1.2 Prompt chaining
  • 4.1.3 Self-consistency prompting
  • 4.1.4 ReAct prompting
  • 4.2 Step-by-step reasoning prompts
  • 4.3.1 Text summarization
  • 4.3.2 Content generation
  • 4.3.3 Code generation
  • 4.3.4 Question answering
  • 4.3.5 Language translation
  • 4.4.1 Concept of RAG
  • 4.4.2 Using external knowledge sources
Unit 5: AI application development: Generative AI, Agentic AI
  • 5.1.1 Writing emails
  • 5.1.2 Generating reports
  • 5.1.3 Creating presentations
  • 5.2.1 Code generation
  • 5.2.2 Code explanation
  • 5.2.3 Code documentation
  • 5.3.1 Finding errors in code
  • 5.3.2 Fixing bugs using AI
  • 5.4.1 Concept of APIs
  • 5.4.2 Examples: OpenAI API, Gemini API
  • 5.5.1 AI chatbot
  • 5.5.2 AI blog writer
  • 5.5.3 AI document summarizer
  • 5.5.4 AI question generator
  • 5.6.1 Concept of AI agents
  • 5.6.2 Autonomous task execution
  • 5.6.3 Examples: AutoGPT, CrewAI
  • 5.7.1 Ethical AI usage
  • 5.7.2 Bias and fairness, Data privacy
  • 5.7.3 Risks and limitations of AI systems

About this course

Study materials, question papers, and solutions for Artificial Intelligence with Prompt Engineering (DI05016011) - Information Technology, Semester 5