Introduction to Artificial Intelligence

Learn the fundamentals of AI, including machine learning, neural networks, and ethical considerations.

Course objectives

Foundations of Artificial Intelligence

This section introduces the history and evolution of artificial intelligence, tracing its development from early symbolic AI to modern deep learning techniques. Students will explore the fundamental concepts of AI, including the difference between weak and strong AI, knowledge representation, and heuristic search algorithms. Key topics include machine learning paradigms such as supervised, unsupervised, and reinforcement learning, alongside an introduction to major AI frameworks like TensorFlow and PyTorch.

Practical Applications and Hands-on Learning

Students will apply AI techniques to real-world scenarios, developing models for image recognition, natural language processing, and predictive analytics. Hands-on projects will involve building neural networks, training models on datasets, and evaluating algorithm performance. The course will also cover industry applications of AI in healthcare, finance, robotics, and entertainment, providing insight into how AI is transforming various fields.

Ethical Considerations and the Future of AI

The course concludes with an in-depth discussion on AI ethics, including issues of bias, fairness, and privacy. Students will explore case studies on algorithmic discrimination, deepfake technology, and surveillance concerns, developing critical thinking skills around responsible AI development. Emerging trends in AI, such as explainable AI (XAI) and AI regulation, will also be examined to prepare students for the evolving landscape of artificial intelligence.

Tutors

Assist. Prof. Aisha Patel

Assistant Professor – Artificial Intelligence & Data Science

Dr. Patel is a leading AI researcher with expertise in machine learning, neural networks, and ethical AI development. She has worked on projects for autonomous systems and speech recognition at major tech firms and holds a PhD in Computer Science from Stanford University. She is passionate about bridging the gap between AI innovation and responsible technology policies.

Prof. Hiroshi Tanaka

Professor – Cybersecurity & Information Technology

Professor Tanaka is a cybersecurity expert with a background in ethical hacking, network security, and cyber threat intelligence. After working with Japan’s top tech firms on cybersecurity infrastructure, he transitioned to academia to train the next generation of security professionals. He holds certifications in CISSP and CEH and teaches at Tokyo Institute of Technology.

Prof. John Veith

Professor – Psychology & Behavioral Science

Dr. Veith is a cognitive psychologist specializing in behavioral analysis and human decision-making. She has conducted research on mental health interventions and workplace psychology. Holding a PhD from the University of Cape Town, she integrates neuroscience and psychology to better understand human behavior.