DI04000161 · Semester 4 · 5G scheme
Artificial Intelligence and Prompt Engineering
Notes and solutions following the Gujarat Technological University (GTU) syllabus for DI04000161. Independent material — not issued by the university.
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Materials
Complete Book
The whole syllabus, unit by unit, written for the exam.
Complete Book
104 pages
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PYQ Solutions
Past university papers, fully solved.
Solved past papers — detailed answers
23 pages · English + ગુજરાતી
Premium Preview · 3 pages
Syllabus units
Unit 1: Introduction to AI & Generative AI
- Definitions: Intelligence, Artificial Intelligence, Machine Learning
- Evolution of AI: From Rule-based systems to Generative AI
- Types of AI: Narrow AI (ANI) vs. General AI (AGI)
- Concept of Generative AI: How text and image generators work (prediction logic vs. search engine)
- Common AI Tools overview: ChatGPT, Gemini, Copilot, Claude
Unit 2: Generative Models & Tools: Concepts and Safe Use
- How LLMs behave (tokens, context, instructions-no coding)
- Types of AI tools: chat LLMs, multimodal tools, assistants
- Responsible AI use: privacy, safety, ethics
- Selecting the right AI tool for a task (accuracy, reliability, limitations)
- Understanding bias and fairness in generative models, including strategies to identify, mitigate, and monitor potential biases in AI systems
Unit 3: Prompt Engineering: Foundations
- What is a prompt? Structure and components – Instruction, Context, Constraints, Examples, Output format
- Types of prompts – Role prompts, Instruction prompts, Task prompts, Information extraction prompts
- Core prompting strategies – Step-by-step prompting, Clarification prompts, Decomposition of complex tasks, Simple few-shot prompting
- Building prompt templates – Report template, Checklist template, SOP template
- Evaluating prompt output quality – Accuracy, Clarity, Completeness, Verifiability
Unit 4: Engineering: Advanced Methods & Practical Applications (Non-Coding)
- Advanced prompting techniques – Scaffolding prompts, Prompt chaining & iterative refinement, Meta-prompts (prompts about prompts), Constraint-based prompting (format, tables, sections)
- Critical evaluation & validation – Detecting hallucinations, Verification and reverse-prompting, Cross-checking with standards/manuals, Uncertainty prompts ('what info is missing?', 'assumptions?')
- Multimodal prompting (conceptual) – How to describe an image to an AI, How to ask for analysis (without relying on domain knowledge)
- Preparing annotated checklists
- Building your own Prompt Library – Categorisation, Version control (simple documentation), Sharing prompts within departments
Unit 5: Governance, Ethics, Security and Future Trends
- AI Ethics: Bias in data, Deep fakes, and Copyright issues
- Data Privacy: What not to share with public AI tools (Proprietary designs, Passwords)
- The Future of Work: How AI changes the role of an Engineer (Human-in-the-loop)
- Responsible AI usage in academia and industry
- Indian cyber regulations overview (non-legal, awareness level)
- Capstone project: prompt-based solution to a real engineering task
About this course
Study materials, question papers, and solutions for Artificial Intelligence and Prompt Engineering (DI04000161) - Diploma Engineering, Semester 4