Description

2171 & 2181 - (30113-2171 & 28349-2181) Cloud Computing
The course introduces the fundamental concepts and building blocks of Cloud Computing and provides an in-depth study of its enabling technologies and tools. The main topics of the course include cloud computing design issues, software and services, data centers architecture and design, virtualization and cloud computational models, cloud programming models, large-scale data processing models, and storage technologies and services. Students gain hands-on experience by solving data- and compute-intensive problems using a variety of cloud computing software and tools.

2161 - (25773) Introduction to Computer Vision
In this class, students will learn the basics of modern computer vision. The first major part of the course will cover fundamental concepts such as image formation, color perception, image filtering, edge detection, texture description, feature extraction and matching, and grouping and fitting. A crash course in Machine Learning will follow, in preparation for the second course chapter on visual recognition. We will study state of the art approaches in object and scene recognition, activity recognition and first-person video, attribute-based description, image retrieval, unsupervised learning, and learning from big data. Finally, we will discuss a few newly introduced topics from the most recent computer vision conferences.

2154 - (29493) Fundamentals of Data Science
The Fundamentals of Data Science special topics course aims to expose students to different data management, data manipulation, and data analysis techniques. The class will cover all the major data management paradigms (Relational/SQL, XML/XQuery, RDF/SPARQL) including NoSQL and Data Stream Processing approaches. Going beyond traditional data management techniques, the class will expose students to information retrieval, data mining, data warehousing, network analysis, and other data analysis topics. Time-permitting, the class will include Big Data processing techniques, such as the map/reduce framework.

2154 - (27096) Software Testing
This course provides students with a broad understanding of modern software testing and quality assurance. Although it will cover testing theory, the emphasis is on providing practical skills in software testing currently used in industry. To that end, it will cover: manual and automated tests, test-driven and behavior-driven development, performance testing, and understanding and developing a testing process.

2151 - (27762) Networks, Crowds & Markets
Networks, Crowds, and Markets combines different scientific perspectives in its approach to understanding networks and behavior. Drawing on ideas from economics, sociology, computing and information science, and applied mathematics, it describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.

2151 - (27763) Software Testing
This course provides students with a broad understanding of modern software testing and quality assurance. Although it will cover testing theory, the emphasis is on providing practical skills in software testing currently used in industry. To that end, it will cover: manual and automated tests, test-driven and behavior-driven development, performance testing, and understanding and developing a testing process.
  • Credits: 3
  • Frequency: Infrequently

Prerequisites

  • 2181 - 28349 - CS/COE 1550. Department Consent required.
    2171 - 30113 - CS/COE 1550. Department Consent required.
    2161 - 25773 - CS/COE 1501 and CS 1502. Some experience with linear algebra is recommended.
    2154 - 29493 - CS 0441 and 0445. Statistics helpful but not required.
    2154 - 27096 - CS 0445
    2151 - 27762 - Permission of the instructor
    2151 - 27763 - CS 0445

Requirements and Grading

Grading Information is course/instructor specific. Each topic can only be taken once for credit.