AIS Artificial Intelligence Courses at Global Campus

This course provides students with the understanding of the key principles, techniques, and applications associated with artificial intelligence (AI) for business strategies and transformation. Students will gain knowledge about knowledge representation, game theory, search problems using computational theories. The course will also explore different issues surrounding AI such as ethics and bias. Some key concepts and terms like deep learning and neural networks will also be covered as part of the course.

In this course, students will examine fundamental concepts and theories related to machine learning. Students will explore the different machine learning models that include: supervised and unsupervised learning, and reinforcement learning. Students will gain an understanding of applications of machine learning in different areas and how to select the appropriate model for a particular scenario. Students will also relate machines learning to other related areas like artificial intelligence, data analytics, and data science.

This course introduces you to the basics of artificial intelligence, data science, and data analytics for the handling of massive databases. The course covers concepts and data mining for big data analytics and introduces you to data visualization and some basic statistical concepts for data science.

This course Introduces the essentials of Artificial Intelligence (AI) as a discipline and as it relates to analytics in supporting the process of decision making. Students will learn fundamentals of methods and techniques used to develop business analytics. The course introduces examples, products, and services used by modern day organizations using AI and various types of analytics to make business decisions.

This course introduces statistics, data sciences and their applications when working with and interpreting data at workplace. The course introduces a foundation for understanding of probabilistic reasoning and the evaluation of data for decision making.

This course focuses on best practices for managers in gaining control over AI implementations and ethical data analysis. The course addresses the responsibilities of a data science manager in overseeing automated decision making that goes beyond the delivery of the modeling results and deployment of the systems. The course studies improving the data monitoring procedures for adhering to a higher ethical standard and responsible data management within an organization.