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PhAI Faculty Development Program

Generative AI for
Engineering Educators

A 2-week immersive training program to equip engineering college lecturers with the knowledge, tools, and hands-on experience to integrate Gen AI into teaching, research, and academic practice.

Duration
10 Days / 55 Hours
Audience
All Engineering Faculty
Prerequisites
No Coding Required
Mode
Offline / Classroom
Program Structure

Daily Schedule & Learning Approach

Each day follows a structured format balancing theory with practice.

TimeActivity
9:30 – 9:45Recap Quiz & Discussion (Day 2 onward)
9:45 – 11:15Session 1 — Theory, Concepts & Demos
11:15 – 11:30Tea Break
11:30 – 13:00Session 2 — Theory, Concepts & Demos
13:00 – 13:45Lunch Break
13:45 – 15:45Hands-on Workshop (No-Code / GUI Tools)
15:45 – 16:15Wrap-up Discussion & Reflection
Assessment
Daily Quizzes + Capstone Project
Engagement
Reflection Journals + Group Work
Certificate
80% Attendance + Capstone
10-Day Roadmap

Two Weeks at a Glance

WEEK 1 AI Foundations & the Gen AI Revolution

1
The AI Story
History, industry landscape, country strategies & infrastructure
2
How Machines Learn
ML concepts, neural networks & deep learning fundamentals
3
The Generative AI Revolution
Gen AI types, LLMs, transformers & how they work
4
The Gen AI Ecosystem
Models, tools, hardware, cloud & open-source landscape
5
Prompt Engineering
Core skill mastery — techniques, patterns & educator applications

WEEK 2 Applications, Practice & Future Directions

6
AI-Powered Productivity
Research tools, presentation builders & teaching aids
7
RAG & Knowledge Systems
Building knowledge assistants & AI applications across industries
8
AI Agents & Multi-Modal AI
Autonomous systems, vision, audio, video & emerging trends
9
Vibe Coding
Building applications with natural language — no coding required
10
Ethics, Education & Capstone
AI challenges, regulation, education strategy & final projects
1
WEEK 1 · Monday
The AI Story — History, Industry & the Big Picture
Trace AI's evolution from Turing to ChatGPT. Grasp the global industry landscape, key players, country strategies, and AI infrastructure. Experience modern AI tools firsthand.
Session 1 — 1.5 hrs
Journey of AI: From Turing to ChatGPT
  • What is AI? Timeline from 1950 to present
  • Key milestones: Deep Blue, AlphaGo, GPT-3, ChatGPT
  • AI Winters and the cycles of hype
  • The "ChatGPT moment" — why Nov 2022 changed everything
  • Demo: ELIZA (1966) vs ChatGPT side-by-side
Session 2 — 1.5 hrs
The AI Industry Landscape
  • Global AI market, investments & growth projections
  • Key players: OpenAI, Google, Anthropic, Meta, NVIDIA
  • GPUs, data centers & cloud computing (simplified)
  • Country strategies: USA, EU, China, India (IndiaAI Mission)
  • AI across industries: Healthcare, Manufacturing, Finance, Education
WORKSHOP Your First AI Conversations — 2 hrs
ChatGPT: Explore subject-specific Q&A, test knowledge boundaries
Claude: Compare responses with ChatGPT on the same questions
Gemini: Try multi-modal — upload an image and ask about it
Group Work: Map 5 ways AI could impact your subject domain
2
WEEK 1 · Tuesday
How Machines Learn — AI/ML Concepts Made Simple
Understand core ML concepts intuitively without math or code. Grasp supervised, unsupervised, and reinforcement learning. Learn how neural networks and deep learning work conceptually.
Session 1 — 1.5 hrs
The Building Blocks of AI/ML
  • Traditional programming vs machine learning
  • Supervised, Unsupervised & Reinforcement Learning (with analogies)
  • Key concepts: Models, training, features, labels
  • Data quality, bias in data & "garbage in, garbage out"
  • Overfitting vs underfitting (memorizing vs understanding)
Session 2 — 1.5 hrs
From Data to Decisions: The ML Pipeline
  • End-to-end ML workflow: Data → Training → Evaluation → Deploy
  • Classification, Regression & Clustering
  • Neural networks: The brain-inspired approach (no math)
  • Deep learning: What makes it "deep" and why it works now
  • CNNs, RNNs & Transfer Learning (conceptual overview)
WORKSHOP ML Without Code — 2 hrs
Teachable Machine: Train an image classifier with your webcam (pen vs eraser)
Kaggle: Explore ML datasets and visualizations
Google AI Experiments: Quick, Draw! & Talk to Books
3
WEEK 1 · Wednesday
The Generative AI Revolution — What, Why & How
Distinguish discriminative from generative AI. Understand how LLMs work: tokenization, embeddings, transformers, and attention. Learn about hallucinations and their causes.
Session 1 — 1.5 hrs
What Is Generative AI?
  • Discriminative vs Generative: Art critic vs Artist
  • Types: Text, Image, Audio, Video & Code generation
  • Evolution: GANs → VAEs → Diffusion → Transformers
  • Why Gen AI exploded: Scale + Data + Compute + RLHF
  • Demo reel: State-of-the-art across modalities
Session 2 — 1.5 hrs
How Do LLMs Actually Work?
  • LLMs as sophisticated "next word predictors"
  • Tokenization & Embeddings (King - Man + Woman = Queen)
  • The Transformer & Self-Attention (intuitive explanation)
  • Training: Pre-training → Fine-tuning → RLHF
  • Hallucinations: Why LLMs make things up
WORKSHOP Exploring Gen AI Across Modalities — 2 hrs
Text: Generate & critique a research abstract; test hallucinations
Image: Create engineering visuals with Bing Image Creator / DALL-E
Research: Perplexity.ai & Consensus for AI-powered search
Multi-modal: Upload diagrams to Gemini / GPT-4 Vision for analysis
4
WEEK 1 · Thursday
The Gen AI Ecosystem — Models, Tools & Infrastructure
Map the full Gen AI ecosystem. Compare open-source vs proprietary models. Understand AI hardware, cloud platforms, costs, and run a model locally.
Session 1 — 1.5 hrs
The Model Landscape
  • Proprietary: GPT-4o, Claude, Gemini, Grok
  • Open-Source: Llama, Mistral, Phi, Qwen, DeepSeek
  • Open vs Closed: Cost, privacy, customization trade-offs
  • Model leaderboards & specialized models
  • The DeepSeek story — how it shook the industry
Session 2 — 1.5 hrs
AI Infrastructure & the Business of AI
  • Hardware: NVIDIA GPUs, TPUs, custom chips
  • Training vs Inference costs (GPT-4 = $100M+ to train)
  • Cloud platforms & API economics (tokens & pricing)
  • Running AI locally: Ollama & LM Studio
  • AI regulation: EU AI Act, India's approach
WORKSHOP Exploring the Ecosystem — 2 hrs
Hugging Face: Browse models, datasets & Spaces; try 3 demos
Ollama: Run a small AI model locally on your laptop
LMSYS Arena: Blind model comparisons — vote on the best
Group Work: Find 3 AI tools specific to your discipline
5
WEEK 1 · Friday
Prompt Engineering — The Core Skill
Master prompt engineering techniques. Apply zero-shot, few-shot, chain-of-thought, and role prompting. Create custom AI assistants and generate lesson plans, assessments, and teaching materials.
Session 1 — 1.5 hrs
The Science of Prompting
  • Prompt anatomy: Role, Context, Format, Task, Constraints, Examples
  • Zero-shot, Few-shot & Chain-of-Thought prompting
  • Role prompting & System prompts
  • Patterns: Persona, Template, Critique, Flipped Interaction
  • Good vs bad prompts: Before & after examples
Session 2 — 1.5 hrs
Advanced Prompting & Educator Applications
  • Tree of Thought, Self-consistency & Meta-prompting
  • Prompt chaining for complex tasks
  • Custom GPTs, Claude Projects & Gemini Gems
  • Creating lesson plans, assessments & rubrics with AI
  • Generating practice problems with step-by-step solutions
WORKSHOP Prompt Engineering Lab — 2.5 hrs
Prompt Makeover: Improve 5 weak prompts, compare before vs after outputs
Build Your TA: Craft a system prompt for an AI teaching assistant
Content Sprint: Create a lesson plan + 10 questions + visual explanation
Showcase: Best prompts & outputs shared with the class
6
WEEK 2 · Monday
AI-Powered Productivity & Research Tools
Discover and master AI tools for academic research, content creation, and teaching productivity. Build a personalized AI toolkit for your discipline. Navigate plagiarism detection and academic integrity.
Session 1 — 1.5 hrs
AI Tools for Academic Work
  • Research: Perplexity, NotebookLM, Semantic Scholar, Elicit, Consensus
  • Writing & docs: Grammarly AI, QuillBot, LaTeX generation
  • Plagiarism detection: Turnitin AI, GPTZero & their limitations
  • Presentations: Gamma.app, Beautiful.ai, Canva AI
Session 2 — 1.5 hrs
AI for Content Creation & Teaching
  • AI videos: Synthesia, HeyGen — lectures without being on camera
  • AI diagrams: Napkin.ai, Whimsical AI, Mermaid via ChatGPT
  • Quiz platforms: Quizizz AI, Kahoot AI
  • NotebookLM deep dive: Audio overviews & grounded Q&A
  • Managing AI in the classroom: Policies & academic integrity
WORKSHOP Building Your AI Teaching Toolkit — 2 hrs
NotebookLM: Upload papers, generate audio overviews & study guides
Gamma.app: Create a full lecture presentation with AI
Tool Exploration: Find & document AI tools for your department
7
WEEK 2 · Tuesday
RAG, Knowledge Systems & AI Applications
Understand Retrieval-Augmented Generation (RAG) and why it solves LLM hallucination. Explore AI applications across engineering disciplines. Build a knowledge assistant without code.
Session 1 — 1.5 hrs
Why RAG? Solving AI's Biggest Problems
  • LLM limitations: Knowledge cutoff, hallucination, no private data
  • RAG = the "open book exam" for AI
  • Pipeline: Ingest → Chunk → Embed → Store → Retrieve → Generate
  • Vector embeddings & semantic search (library analogy)
  • Real-world RAG: Support bots, research assistants, university Q&A
Session 2 — 1.5 hrs
AI Applications Across Industries
  • Healthcare: Drug discovery, medical imaging, AlphaFold
  • Manufacturing: Predictive maintenance, digital twins
  • Finance, Agriculture, Legal & Education applications
  • Engineering: Civil, Mechanical, Electrical, ECE, CS-specific AI tools
WORKSHOP Build Your Knowledge Assistant — 2 hrs
Custom GPT / Gem: Upload syllabus & notes to create a subject-specific assistant
Dify.ai: Explore a no-code RAG builder — see the pipeline visually
Group Discussion: Design a knowledge assistant for your department
8
WEEK 2 · Wednesday
AI Agents, Automation & Multi-Modal AI
Understand AI agents and how they differ from chatbots. Experience multi-modal AI across vision, audio, and video. Explore emerging trends: robotics, edge AI, and the AGI conversation.
Session 1 — 1.5 hrs
AI Agents — The Next Frontier
  • Evolution: Chatbot → Assistant → Co-pilot → Agent
  • Agent loop: Perceive → Plan → Act → Reflect
  • Tool use & function calling: Search, calculate, browse, write
  • Multi-agent systems: Teams of specialized AI agents
  • Real-world: Devin, research agents, customer service bots
Session 2 — 1.5 hrs
Multi-Modal AI & Emerging Trends
  • Models that see, hear, read & create: GPT-4o, Gemini 2.5
  • Speech AI: Whisper transcription, ElevenLabs TTS, voice cloning
  • Video generation: Sora, Runway Gen-3, Kling
  • Robotics + AI, Edge AI, on-device processing
  • The AGI conversation & what's coming next
WORKSHOP Agents & Multi-Modal Exploration — 2 hrs
AI Agents: Upload CSV to ChatGPT — watch it plan, code & visualize
Multi-Modal: Vision (upload diagrams), Audio (Whisper, TTS), Video (Runway)
Design Challenge: Design an AI agent for your department on paper
9
WEEK 2 · Thursday
Vibe Coding — Building Software with Natural Language
Experience vibe coding — build working applications by describing them in plain English. Use no-code platforms for data analysis and AI application building. No programming required.
Session 1 — 1.5 hrs
What Is Vibe Coding?
  • "Describe what you want, AI builds it" — Andrej Karpathy
  • Tools: Bolt.new, Cursor, Lovable, Replit Agent, v0.dev
  • Live demo: Build a web app in real-time using Bolt.new
  • Implications for CS education & non-CS engineers
  • Limitations: Bugs, security & when human expertise matters
Session 2 — 1.5 hrs
AI-Assisted Development & No-Code AI
  • No-code platforms: Google AI Studio, Copilot Studio, Dify.ai
  • Data analysis without code: ChatGPT, Julius.ai, Google Sheets AI
  • AI automation: Zapier AI, Make.com
  • Building tools: Feedback analyzers, grade trackers, paper summarizers
WORKSHOP Vibe Coding Lab — 2.5 hrs
Bolt.new: Build a subject-specific web app — quiz, calculator, flashcards
AI Studio: Experiment with Gemini models, structured prompts, parameters
Data Analysis: Upload a dataset to ChatGPT — get charts & a full report
Showcase: Demo your apps & analysis results to the class
10
WEEK 2 · Friday
Ethics, Challenges, AI in Education & Capstone
Grapple with AI ethics and real-world challenges. Develop a strategy for integrating AI into your teaching. Present a capstone project with your department team.
Session 1 — 1.5 hrs
AI Ethics, Risks & Challenges
  • Bias & fairness: Amazon hiring, facial recognition case studies
  • Hallucination & reliability: Real consequences & mitigation
  • Privacy, security & prompt injection risks
  • Deepfakes, misinformation & academic integrity
  • AI regulation: EU AI Act, India's governance approach, copyright
Session 2 — 1 hr
Gen AI in Higher Education — Strategy & Action
  • AI-proofing vs AI-integrating assessments
  • AI literacy as a core competency for students
  • Redesigning curricula for the AI age
  • Faculty development roadmap: What to learn next
  • Resources: DeepLearning.AI, fast.ai, NPTEL, newsletters
CAPSTONE PROJECT Subject-Specific AI Integration Plan — 2.5 hrs
Phase 1 — Build (60 min): Teams create an AI Integration Plan: 3 use cases, lesson plan, AI policy, toolkit, risk analysis
Phase 2 — Present (60 min): 8-10 min team presentations with peer feedback
Phase 3 — Close (30 min): Reflection, key takeaways, certificates & photo
Participant Setup

Tools & Accounts (All Free)

Participants create accounts before Day 1. All tools used in workshops are free or have free tiers.

Essential Tools

ChatGPT
Claude
Google Gemini
Perplexity AI
NotebookLM
Teachable Machine
Hugging Face
Gamma.app
Bolt.new
Google AI Studio

Optional (Free Tier)

Canva AI
ElevenLabs
Runway (trial)
Bing Image Creator
Julius.ai
Quizizz AI
Dify.ai
Consensus

Infrastructure Requirements

Participant
Laptop + Chrome/Edge + Internet
Classroom
Projector + Stable WiFi
Trainer
ChatGPT Plus + Ollama (local demos)
Collaboration
Shared Google Drive folder
Thank You

Ready to Transform
Engineering Education

10 days. 55 hours. From AI foundations to vibe coding. From understanding transformers to building knowledge assistants. Equipping educators for the AI age.

Contact
PhAI Training Team
Let's Connect
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