🏫 Programming & Software Development

Essentials for AI & Prompt Mastery

AI and Prompt Engineering for Everyone — ChatGPT, MidJourney, DALL-E & the Modern Generative AI Toolkit

Duration

12 Weeks

Weekly Hours

4 Hours

Course Incharge

Muzammil Bilwani

📋 Prerequisites

✓ Basic computer literacy. No coding or technical background required.

📖 Course Description

A comprehensive, no-code course for students who want to become confident, responsible, and highly capable users of today's generative AI tools. Covers how large language models and diffusion models work conceptually, advanced prompt engineering, AI for writing, research, images, video, audio, and productivity, AI agents and automation tools, and a deep look at AI ethics — preparing students to use AI effectively across academic, creative, and professional contexts.

What You Will Learn

Understand how LLMs and image/video generation models work at a conceptual level

Master prompt engineering frameworks and advanced prompting techniques

Use ChatGPT, Claude, and Gemini effectively for research, writing, and study support

Generate and refine images using MidJourney, DALL-E, and Stable Diffusion

Use AI tools for video, audio, and presentation creation

Use no-code AI automation tools (e.g. Zapier, Make) to build simple workflows

Recognize AI limitations, bias, misinformation risks, and ethical considerations

Build a substantial AI-assisted portfolio project

Course Outline

Understanding Generative AI

→What is AI, machine learning, and generative AI? Demystifying the terminology
→How large language models actually work (conceptually, no math required)
→Tour of the AI tool landscape — chatbots, image, video, and audio tools
→Hands-on: Compare responses across ChatGPT, Claude, and Gemini for the same task

Prompt Engineering Fundamentals

→Anatomy of a good prompt — context, role, task, format, constraints
→Common prompting mistakes and how to fix them
→Iterative refinement — treating AI as a conversation, not a search bar
→Hands-on: Write and refine prompts to solve real study and research tasks

Advanced Prompting Techniques

→Few-shot prompting and providing examples
→Chain-of-thought prompting for complex reasoning tasks
→Role-based and persona prompting
→Hands-on: Solve multi-step problems using advanced prompting techniques

AI for Writing and Editing

→Using AI for brainstorming, outlining, and drafting assignments
→Editing and improving tone, clarity, and structure with AI
→Avoiding over-reliance — using AI as a collaborator, not a replacement
→Hands-on: Draft, edit, and polish a written piece using AI assistance

AI for Research and Fact-Checking

→Using AI for research and literature summarization
→Verifying AI-generated claims and avoiding hallucinations
→Using AI search tools (Perplexity and similar) effectively
→Hands-on: Research and fact-check a topic using multiple AI tools

Introduction to AI Image Generation

→How text-to-image models work (diffusion models explained simply)
→Introduction to MidJourney — interface and basic prompting
→Introduction to DALL-E and Stable Diffusion
→Hands-on: Generate a first set of images from text prompts

Advanced Image Prompting

→Prompt structure for images — style, composition, lighting, mood
→Iterating and refining image outputs
→Understanding copyright, ownership, and ethical use of AI images
→Hands-on: Design a themed image set for a personal or class project

AI for Presentations and Documents

→Using AI to build slide decks and presentation content
→AI tools for document formatting and design
→Combining text and image AI tools into one deliverable
→Hands-on: Build a complete AI-assisted presentation

AI for Video and Audio

→Introduction to AI video generation and editing tools
→AI voice generation and text-to-speech tools
→Use cases: study content, presentations, and creative projects
→Hands-on: Create a short AI-assisted video or narrated clip

AI in Everyday Productivity

→Using AI for scheduling, planning, and organization
→AI-powered note-taking and study tools
→Building personal AI workflows for daily tasks
→Hands-on: Design a personal AI-assisted productivity system

Introduction to AI Agents and Automation

→What are AI agents? How they differ from simple chatbots
→Introduction to no-code automation tools (Zapier, Make)
→Connecting AI tools together into simple workflows
→Hands-on: Build a simple no-code AI automation (e.g. auto-summarize emails)

Custom GPTs and AI Assistants

→Building custom GPTs/assistants without code
→Giving AI assistants specific knowledge and instructions
→Use cases for personal and academic assistants
→Hands-on: Build a custom AI assistant for a specific task

AI Ethics, Bias, and Misinformation

→Understanding bias in AI models and training data
→Misinformation, deepfakes, and how to spot AI-generated content
→Academic integrity and appropriate AI use in school/university
→Hands-on: Analyze a case study involving AI misuse and discuss solutions

AI Privacy and Data Considerations

→How AI companies use your data and conversations
→Privacy best practices when using AI tools
→Understanding AI tool terms of service and limitations
→Hands-on: Audit your own AI tool usage for privacy risks

The Future of AI and Career Applications

→Emerging AI trends and tools to watch
→How AI is changing different industries and career paths
→Building an AI-forward personal brand/portfolio
→Hands-on: Research how AI is transforming a career field of interest

Capstone Planning and Tool Integration

→Planning a multi-tool AI-assisted capstone project
→Combining text, image, and automation tools into one workflow
→Project scoping and structure
→Hands-on: Draft the plan and initial assets for the capstone project

Capstone Build

→Building out the full capstone project using multiple AI tools
→Refining outputs and ensuring quality and originality
→Preparing a presentation of the finished work
→Hands-on: Complete the capstone project

Capstone Presentation and Course Wrap-Up

→Final polish and rehearsal
→Capstone: Present an AI-assisted project (presentation, campaign, or creative piece) using at least three AI tools
→Reflection on responsible AI use and course wrap-up

📊 Grading Criteria

Component	Percentage
Quizzes	20%
Class Participation / Attendance	15%
Projects	25%
Final Projects	40%
Total	100%

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