omscs - Bits & Bytes

CS-6515 Graduate Algorithms

This will likely be the final course you'll take in your OMSCS journey. It's a pre-requiste to gradate for all specializations and at least in 2023 you were most likely unable to register for the class until your final semester (unless you were very lucky and go an early waitlist

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-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

omscs

CS-6460 Educational Technology

Instructor(s): David Joyner Course Page: Link This class was simultaneously an introductory course about educational technology and an advanced, project-oriented class on designing or researching technology’s intersection with education. The course provides student's with information about a large number of topics within educational technology, including pedagogical strategies, research

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-6250: Computer Networks

Instructor(s): Maria Konte Course Page: Link As the name entails, CS-6250 is an introductory course to Computer Networking covering a wide range of topics from the evolution of the internet, basic routing algorithms, software-defined networking, internet security, CDNs and modern applications like VoIP video and IoT. Course HighlightsThe course

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