Introduction to Artificial Intelligence — Full Syllabus
Duration: 8–12 Weeks | Level: Beginner to Intermediate
Format: Concept + Case Study + Hands-on Labs + Mini Projects
Goal: Understand what AI is, how it works, and how it’s changing the world.
Module 1: What is Artificial Intelligence?
- Definition of AI (in simple words)
- Difference between AI, Machine Learning, Deep Learning
- History & evolution of AI
- Why AI is booming now
- Real-life applications: ChatGPT, Netflix, YouTube, self-driving cars
Mini Task: Create a list of AI tools you use unknowingly every day.
Module 2: Types of Artificial Intelligence
- Narrow AI vs General AI vs Super AI
- Reactive Machines, Limited Memory, Theory of Mind, Self-Aware AI
- Real-world examples (Alexa, Siri, Google Maps)
Activity: Identify the type of AI behind famous apps.
Module 3: Machine Learning Basics
- What is Machine Learning?
- Types of ML: Supervised, Unsupervised, Reinforcement
- Real-life example: Email spam detection, YouTube recommendations
- How machines “learn” from data
- Steps of a basic ML pipeline
Hands-on: Use a no-code tool like Teachable Machine or Google’s AutoML
Module 4: Data – The Fuel of AI
- What is data in AI?
- Types: Structured, Unstructured
- Data collection, cleaning, and labeling
- Bias in data and its consequences
Case Study: How biased data created issues in facial recognition systems
Module 5: Neural Networks & Deep Learning (Simple Way)
- What is a neural network?
- How the brain inspired AI
- Deep Learning vs Machine Learning
- Real-world examples: Face ID, chatbots, image recognition
Visual Activity: Use TensorFlow Playground to explore a neural net
Module 6: Natural Language Processing (NLP)
- What is NLP?
- How machines understand human language
- Sentiment analysis, ChatGPT, Google Translate
- Language Models (very basic intro)
Hands-on: Try Hugging Face demo models or use ChatGPT for text analysis
Module 7: AI in the Real World
- AI in healthcare, agriculture, education, marketing, and finance
- Chatbots, recommendation engines, fraud detection, virtual assistants
- Good vs. Bad AI: Use cases with real impact
Project: Create a slide deck or video on “AI in [your field]”
Module 8: Ethics, Risks & The Future of AI
- Can AI replace humans?
- Privacy concerns
- Deepfakes, surveillance, job automation
- Bias & fairness in AI
- Responsible AI development
- The future of work and creativity with AI
Discussion: Should we limit AI? How can we use it ethically?
Bonus Practical Modules (Optional but Powerful)
- AI Without Code: Make AI models with tools like Teachable Machine or Pictory
- Build a Simple Chatbot with a no-code platform
- Intro to Prompt Engineering (how to talk to AI like ChatGPT effectively)
- Free AI Tools for Students & Creators
Final Project Ideas (Choose One)
- “Build your own AI tool” using no-code platforms
- Create a YouTube explainer video on an AI concept
- Design an infographic/poster about AI’s risks and benefits
- Use ChatGPT to generate a story or poem and analyze it
