Artificial Intelligence and Prompt Engineering
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Follow on Instagram for UpdatesArtificial Intelligence and Prompt Engineering Syllabus — Unit-wise Content
The official GTU curriculum for Artificial Intelligence and Prompt Engineering (subject code DI04000161) as prescribed for Production · Semester 4 divides the course into 5 units, covering 20 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (DI04000161)Unit 1 Introduction to AI & Generative AI
- 1.1 Definitions: Intelligence
- Artificial Intelligence
- Machine Learning 1.2 Evolution of AI: From Rule-based systems to Generative AI. 1.3 Types of AI: Narrow AI (ANI) vs
- General AI (AGI). 1.4 Concept of Generative AI: How text and image generators work (prediction logic vs. search engine). 1.5 Common AI Tools overview: ChatGPT
Unit 2 Generative Models & Tools
- Concepts and Safe Use 2.1 How LLMs behave (tokens
- instructions—no coding) 2.2 Types of AI tools: chat LLMs
- multimodal tools
- assistants 2.3 Responsible AI use: privacy
- ethics 2.4 Selecting the right AI tool for a task (accuracy
- limitations) 2.5 Understanding bias and fairness in generative models
- including strategies to identify
- mitigate, and monitor potential biases in AI systems
Unit 3 Prompt Engineering
- Foundations 3.1 What is a prompt? Structure and components Instruction Context Constraints Examples Output format 3.2 Types of prompts Role prompts Instruction prompts Task prompts Information extraction prompts w.e.f.2025-26 http://syllabus.gtu.ac.in/ Pageno.3 of 7 Program Name: Diploma Engineering Level: Diploma Branch: Automobile Engineering / Mechanical Engineering /Mechanical Engineering (CAD/CAM)/ Civil Engineering / Environmental Engineering / Mechatronics Engineering / Mining Engineering /Fabrication Technology Subject Code : DI04000161 Subject Name: Artificial Intelligence and Prompt Engineering 3.3 Core prompting strategies Step-by-step prompting Clarification prompts Decomposition of complex tasks Simple few-shot prompting 3.4 Building prompt templates Report template Checklist template SOP template 3.5 Evaluating prompt output quality Accuracy Clarity Completeness Verifiability
Unit 4 Engineering
- Advanced Methods & Practical Applications (Non-Coding) 4.1 Advanced prompting techniques Scaffolding prompts Prompt chaining & iterative refinement Meta-prompts (prompts about prompts) Constraint-based prompting (format
- sections) 4.2 Critical evaluation & validation Detecting hallucinations Verification and reverse-prompting Cross-checking with standards/manuals Uncertainty prompts (“what info is missing?”
- “assumptions?”) 4.3 Multimodal prompting (conceptual) How to describe an image to an AI How to ask for analysis (without relying on domain knowledge) Preparing annotated checklists 4.4 Designing workflow-level prompts Maintenance workflow prompts w.e.f.2025-26 http://syllabus.gtu.ac.in/ Pageno.4 of 7 Program Name: Diploma Engineering Level: Diploma Branch: Automobile Engineering / Mechanical Engineering /Mechanical Engineering (CAD/CAM)/ Civil Engineering / Environmental Engineering / Mechatronics Engineering / Mining Engineering /Fabrication Technology Subject Code : DI04000161 Subject Name: Artificial Intelligence and Prompt Engineering Inspection workflow prompts Safety workflow prompts 4.5 Building your own Prompt Library Categorisation Version control (simple documentation) Sharing prompts within departments
Unit 5 Governance, Ethics, Security and Future Trends
- 5.1 AI Ethics: Bias in data
- Deep fakes, and Copyright issues. 5.2 Data Privacy: What not to share with public AI tools (Proprietary designs
- Passwords). 5.3 The Future of Work: How AI changes the role of an Engineer (Human-in-the-loop). 5.4 Responsible AI usage in academia and industry. 5.5 Indian cyber regulations overview (non-legal
- awareness level) 5.6 Capstone project: prompt-based solution to real engineering task
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