artificial intelligence

CS-7650 Natural Language Processing

CS-7650 is the newest machine learning OMSCS course that delves into the intricacies of Natural Language Processing, offering a comprehensive exploration of both foundational concepts and contemporary techniques and a history of how we arrived at Large Language Models. I was lucky enough enroll in it's 2nd iteration for Fall

machine learning

CS-7643 Deep Learning

Instructor(s): Zsolt Kira Course Page: Link CS-7643 is a foundational course for the OMSCS Machine Learning specialization. It largely follows the curriculum of similar Deep Learning courses like CS231n from Stanford, going through the evolution of deep learning through Computer Vision lens. We cover Image Classification, Perceptrons, Backpropogation, Convolutional

artificial intelligence

Hugging Face Deep RL Course

Back in December, Hugging Face released an eight unit course covering the fundamentals of Deep Reinforcement Learning. The course covers fundamental theories of Deep RL, core libraries and gives you hands-on experience training your own agents in unique environments ranging from classical control problems all the way to video games

machine learning

CS-7642 Reinforcement Learning

Instructor(s): Charles Isbell / Michael Littman Course Page: Link CS-7641 is a core course for the OMSCS Machine Learning specialization. It serves as a introduction to reinforcement learning, and a continuation of CS-7641 Machine Learning At the time of writing, the course consists of 3 major written assignments, 6 homework

artificial intelligence

CS-7641: Machine Learning

Instructor(s): Charles Isbell / Michael Littman Course Page: Link CS-7641 is a core course for the OMSCS Machine Learning specialization. It serves as a introduction to three core fields of study in machine learning: Supervised LearningUnsupervised LearningReinforcement LearningProf. Isbell takes a nuanced approach with teaching this course, emphasizing synthesis over

artificial intelligence

CS-7646: Machine Learning for Trading

Instructor(s): Tucker Balch, Ph.D. / David Joyner Course Page: Link CS-7646 is another introductory course into machine learning-based trading strategies. The course is broken into 3 major components: Manipulating financial data with PandasFinance Fundamentals: CAPM, Techincal Analysis, Options, Modern Portfolio Theory & Mean-Variance AnalysisMachine Learning Techniques: Decision Trees, Reinforcement

artificial intelligence

CS-6476: Computer Vision

Instructor(s): Aaron Bobick/ Irfan Essa Course Page: Link This course provides a gentle introduction to computer vision covering a wide range of topics including: Feature Detection & Extraction: Hough Transforms, SIFT descriptors & RANSACCamera Models and Stereo GeometryMotion Models - Hierarchical Lucas and KanadeKalman and Particle Filters for Motion

omscs

CS-7638: Artificial Intelligence for Robotics

Instructor(s): Jay Summet / Sebastian Thrun Course Page: Link CS-7638 is an introductory course that covers basic techniques used in robotics. Throught its 16-week span, the instructors cover various techniques/algorithms used in the field of robotics such as: Bayes Filters: Histogram, Kalman & Particle FiltersPID (Proportional–Integral–Derivative) ControllersPath