Clemson University - Master of Science in Computer Science 

offered by Coursera

Design and Analysis of Algorithms This course provides fundamental design techniques like divide and conquer and dynamic programming strategies to theoretical tools such as recurrences and probability theory

Receptive Software Development Designed to leverage modern software development principles, this course embraces the potential for strategic integration and appropriate use of AI tools to enhance operational efficiency of the development process without compromising quality or safety

Applied Data Science Course covers applied methods and techniques in Data Science, including data scraping, cleaning, and storage; technical issues when working with different types of data; basic topics in machine learning; parallel and distributed computing; cloud computing; data visualization; and ethical issues in Data Science

Database Management Systems Introduction to database/data communications concepts as related to the design of online information systems

Human-Centered AI The Human-Centered Artificial Intelligence course provides students with a holistic understanding of artificial intelligence design, human-centered computing, ethics, and societal impact

Data Mining Study of principles of data mining: concepts and techniques of data analysis including regression, clustering, classification, association, prediction, etc.; efficient data mining algorithms; data mining applications in various areas including market analysis and management, WWW mining, bioinformatics, etc

Deep Learning Covers the principles of recently developed algorithms in deep learning, such as convolutional neural networks, recursive neural networks, generative adversarial nets and deep reinforcement learning, self-attention, deep neural networks, auto encoders, and VAE