Advanced Topics in Computer Science Master's Project: Advanced research project in Computer Science.

Advanced Topics in Computer Science Master's Project: Advanced research project in Computer Science.

This course examines sociotechnical problems with existing modes of social media and works towards building new, affirmative visions for social media through technical and policy means. Students will examine interventions to address problems with contemporary social media and design and develop possible interventions.

The goal of this course is to provide Professional Masters students with industry mentorship and real-world data science training. Beyond-classroom educational opportunities are an excellent way to gain practical experience on a substantial project, to learn advanced skills, to collaborate with a professional PhD researcher, to form a connection to a data science company, and to work in a team with other graduate students. Industry partners propose semester-long data science projects.

Not available at this time

Over the last few years, a wave of excitement about machine learning (ML) and deep learning has proliferated from academia to industry, transforming prototypes in research labs to valid solutions to real-world problems. Using ML entails developing end-to-end pipelines to collect data, clean it, and run learning and inference algorithms in a scalable manner. This results in computationally intense workloads and complex software pipelines. Systems for ML help users organize their data and scale these computationally intense problems to larger and larger datasets.

Over the last few years, a wave of excitement about machine learning (ML) and deep learning has proliferated from academia to industry, transforming prototypes in research labs to valid solutions to real-world problems. Using ML entails developing end-to-end pipelines to collect data, clean it, and run learning and inference algorithms in a scalable manner. This results in computationally intense workloads and complex software pipelines. Systems for ML help users organize their data and scale these computationally intense problems to larger and larger datasets.

Conversational AI is a graduate level seminar intended to cover recent research progress on chat bots, task-oriented dialogue systems, conversational search and recommender systems, conversational question answering, multi-modal conversational systems, and related topics. Students are expected to read, present, and discuss research papers related to conversational AI systems. They will also get familiar with state-of-the-art tools and techniques for developing conversational systems.

Conversational AI is a graduate level seminar intended to cover recent research progress on chat bots, task-oriented dialogue systems, conversational search and recommender systems, conversational question answering, multi-modal conversational systems, and related topics. Students are expected to read, present, and discuss research papers related to conversational AI systems. They will also get familiar with state-of-the-art tools and techniques for developing conversational systems.

Artificial Intelligence will radically change education. Through machine learning, data mining, analytics, robotics, and user models, AI will replace false learning boundaries (e.g., learning places, time, level of study); personalize learning; make learning instantly available to everyone; connect learners with partners; provide multi-media; and augment human learning ability. This seminar examines recent work in explanatory and tutoring systems, presents theories about digital teaching and learning, and describes how to deliver personalized teaching in online systems.