All Courses
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FA22: CS-133 Sec 01 - Data Visualization
Topics in data analysis and visualization. This course will cover tools and techniques to efficiently analyze and visualize large volumes of data in meaningful ways to help solve complex problems in fields such as life sciences, business, and social sciences.
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FA22: CS-171 Sec 03 - Intro Machine Learn
The course is an in-depth exploration of the underlying mathematics as well as some practical applications in the field of machine learning. The course also focuses on designing algorithms that allow computers to learn and take actions in a probabilistic fashion using statistical inferences. Students will explore Probabilistic Reasoning, Belief Networks, Bayesian learning, Hidden Variable Learning, Supervised and Unsupervised Learning, Linear Modeling, Gaussian Processes, Mixture Models, Discrete State Markov Models. In addition, students will explore the fundamentals and various use cases in Deep Learning, Natural Language Processing and Reinforcement Learning using packages such as Scikit-Learn, Tensorflow, Keras, PyTorch, SpaCy, NLTK etc.