Introduction to Artificial Intelligence course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course provides a clear and accessible introduction to artificial intelligence, designed for beginners with no prior technical background. You'll gain essential AI literacy by exploring foundational concepts, key technologies, real-world applications, and ethical considerations. The course is structured into five core modules and a final project, requiring approximately 20-25 hours of learning over 6-8 weeks. Each module combines conceptual understanding with real-life examples to build a strong foundation for further study or informed decision-making in AI-driven environments.
Module 1: Foundations of Artificial Intelligence
Estimated time: 4 hours
- What is Artificial Intelligence?
- Historical development of AI
- Core AI terminology and concepts
- Examples of AI in everyday life
Module 2: Machine Learning and Core Techniques
Estimated time: 6 hours
- Introduction to supervised learning
- Introduction to unsupervised learning
- How AI models are trained and evaluated
- Basic AI problem-solving methods
Module 3: AI Applications Across Industries
Estimated time: 6 hours
- AI in healthcare: diagnostics and patient care
- AI in finance: fraud detection and risk analysis
- AI in retail: recommendation systems
- AI in manufacturing: predictive maintenance and automation
Module 4: Key AI Domains
Estimated time: 5 hours
- Natural language processing (NLP)
- Computer vision and image recognition
- Introduction to robotics and intelligent systems
Module 5: Ethics, Bias, and Responsible AI
Estimated time: 4 hours
- Fairness, transparency, and accountability in AI
- Data privacy and ethical risks
- Responsible AI frameworks and governance
Module 6: Final Project
Estimated time: 5 hours
- Analyze a real-world AI application
- Evaluate its technical approach and societal impact
- Present recommendations for ethical implementation
Prerequisites
- No programming experience required
- Basic familiarity with technology and digital tools
- Interest in AI and its societal implications
What You'll Be Able to Do After
- Explain the differences between AI, machine learning, and deep learning
- Identify how AI systems learn from data and make decisions
- Recognize key AI domains and their practical applications
- Analyze ethical challenges and biases in AI technologies
- Apply foundational AI knowledge to business or policy contexts