IBE840 Applied AI (Spring 2027)

In an era where Artificial Intelligence (AI) is revolutionizing industries, "Applied Artificial Intelligence" is a master's level course designed to provide students with the advanced skills and knowledge necessary to harness AI technologies effectively. This course focuses on the practical application of AI in solving real-world problems, emphasizing the integration of AI tools and techniques within various domains. Students will explore various AI methodologies and learn how to implement AI solutions. Through a blend of theoretical insights and hands-on projects, students will develop the ability to design and deploy AI systems that enhance decision-making and drive innovation. This course empowers non-technical students by teaching them how to harness the potential of AI and apply it to real-world scenarios. It provides a practical understanding of AI technologies and demonstrates their relevance in solving specific business challenges. Additionally, the course offers valuable insights for technical students, helping them bridge the gap between AI concepts and their application in business contexts to drive innovation and enhance operational efficiency. Both groups will gain the skills needed to implement AI solutions that improve business outcomes.

Key Topics:

• Fundamentals of machine learning and deep learning
• AI-driven decision-making processes
• Ethical considerations and bias in AI
• Evaluating AI models and performance metrics
• Automation and intelligent systems integration
• Future trends in AI technology

Knowledge:

• Has advanced knowledge within the academic field and specialized insight in the uunderstand the core principles of AI and machine learning.
• Has advanced knowledge within the academic field and specialized insight in analyze the impact of AI on various industries.
• Has advanced knowledge within the academic field and specialized insight in evaluate the ethical implications of AI technologies.

Skills:

• Ability to design and implement machine learning models.
• Ability to apply AI techniques to solve complex problems.
• Ability to assess the performance of AI systems.

General Competence:

• Can analyze relevant academic, professional and research ethical problems
• Can apply his/her knowledge and skills in to critically evaluate the societal impact of AI.
• Can apply his/her knowledge and skills in to lead projects involving AI integration.
• Can apply his/her knowledge and skills to adapt to emerging trends in AI technology.

• Lectures with practical demonstrations
• Guest lectures by industry experts
• Hands-on projects and labs
• Case studies