Introduction to Artificial Intelligence
Unveiling the Power and Potential of Intelligent Systems
Confidence Building
Interactive lectures enriched with visual aids and clear explanations.
Live demonstrations of AI technologies and tools to illustrate concepts.
Engaging small group discussions and collaborative problem-solving activities.
Hands-on exercises using Jupyter notebooks with simplified Python implementations of AI concepts.
Analysis of insightful case studies and real-world examples of AI in action.
Focus on developing a clear understanding, critical thinking, and the ability to discuss AI confidently
Who is This Course For?
Key Outcomes
Individuals with basic Python knowledge eager to explore AI concepts.
Students and professionals seeking to understand the fundamentals of machine learning and AI applications.
Anyone curious about the mechanics behind AI, its capabilities, and its ethical considerations.
Learners who have completed “AI Literacy” or possess equivalent foundational knowledge.
Those aiming to understand how AI is transforming industries and daily life.
Understand core AI concepts, historical context, and terminology
Distinguish between different AI approaches (e.g., search, logic, machine learning) and their applications
Grasp the fundamentals of supervised, unsupervised, and deep learning
Recognize the capabilities and limitations of modern AI systems in areas like NLP and Computer Vision
Evaluate the ethical implications and societal impact of AI technologies
Identify appropriate AI techniques for solving specific types of problems
Appreciate the interdisciplinary nature of artificial intelligence
Communicate ideas about AI clearly to both technical and non-technical audiences
Be prepared for further study or exploration in specialized AI fields
Prerequisites
Basic Python programming knowledge (comfortable with variables, control flow, functions).
Basic level mathematics (understanding of fundamental concepts).
A strong curiosity about artificial intelligence and its applications.
Access to a computer with an internet connection.
Course Format
14 sessions (1.5 hrs each)
Choose between: 2x/week for 7 weeks 3x/week for ~5 weeks
Interactive lectures, live demonstrations, and hands-on activities
Access to course materials and Jupyter notebooks