Faculty: Graduate School of Natural and Applied Sciences The Artificial Intelligence major focuses on the development of intelligent machines and software that can perform tasks typically requiring human intelligence. Students gain skills in machine learning, natural language processing, computer vision, robotics, and ethical considerations in AI, preparing for careers in tech companies, research institutions, and related fields. **Learning Objectives:** - Understand the fundamentals of artificial intelligence and its applications. - Develop skills in machine learning algorithms and techniques. - Learn natural language processing and computer vision technologies. - Explore robotics and autonomous systems. - Analyze ethical considerations and societal impacts of AI. - Develop critical thinking, problem-solving, and programming skills. - Gain practical experience through projects and internships. **Major Outline:** 1. **Introduction to Artificial Intelligence** - Overview of AI, its history, principles, and industry trends. 2. **Machine Learning** - Fundamentals of machine learning, algorithms, and applications. 3. **Natural Language Processing (NLP)** - Techniques for processing and understanding human language. 4. **Computer Vision** - Methods for enabling computers to interpret and understand visual information. 5. **Robotics and Autonomous Systems** - Principles of robotics, autonomous systems, and their applications. 6. **Ethical Considerations in AI** - Ethical issues, societal impacts, and responsible AI development. 7. **Data Mining and Big Data Analytics** - Techniques for extracting insights and patterns from large datasets. 8. **AI in Industry** - Applications of AI in various industries such as healthcare, finance, and transportation. 9. **AI Research Methods** - Methods for conducting AI research, experiment design, and data analysis. 10. **Capstone Project/Internship** - Comprehensive project or internship applying AI skills, such as developing an AI application, conducting research, or completing a field placement. **Assessment Methods:** - AI fundamentals analyses - Machine learning algorithm implementations - Natural language processing projects - Computer vision reports - Robotics and autonomous systems designs - Ethical considerations in AI essays - Data mining and big data analytics projects - AI in industry case studies - AI research methods reports - Capstone projects/internship reports and presentations **Recommended Textbooks:** - "Introduction to Artificial Intelligence" by Stuart Russell and Peter Norvig - "Machine Learning" by Tom M. Mitchell - "Natural Language Processing" by Daniel Jurafsky and James H. Martin - "Computer Vision" by Richard Szeliski - "Robotics and Autonomous Systems" by various authors - "Ethical Considerations in AI" by various authors - "Data Mining and Big Data Analytics" by various authors - "AI in Industry" by various authors - "AI Research Methods" by various authors **Prerequisites:** Basic knowledge of computer science, mathematics, and programming. **Major Duration:** Typically 4 years for a bachelor's degree or 2 years for a master's degree in Artificial Intelligence. **Certification:** Graduates may pursue certifications such as: - Certified Associate in Artificial Intelligence (CAIA) from the AI Society - IBM Data Science Professional Certificate - Google Cloud Certified - Professional Machine Learning Engineer - Microsoft Certified: Azure AI Engineer Associate **Target Audience:** Aspiring AI specialists, machine learning engineers, data scientists, robotics engineers, and professionals seeking careers in tech companies, research institutions, healthcare, finance, and related fields. This major equips students with the technical and analytical skills needed to excel in artificial intelligence, supporting careers in various roles within tech companies, research institutions, and related fields.