On behalf of the Systems and Data Science faculty, we are very excited to announce that the name of the Systems Track is updated to Systems and Data Science (SDS) in the BS, MS, and PhD Electrical Engineering (EE) Programs. The effective date of the update is 10/29/2020.

Demand for data scientists continues its rapid rise!

Well-known job search websites such as LinkedIn and Glassdoor ranked data scientists as their No. 1 job. Furthermore, multiple data-science-related skills have been identified as those most in demand by companies. As a consequence, students will need data-science-related skills in their repertoire for a successful career over the next few decades.

Data science education @EE:

For over 25 years, the B.S., M.S., and Ph.D. EE Program has offered the Systems Track that develops a strong background and foundation in the theory and practice of communication, control systems, networks, information theory, and signal processing. In recent years, the topics have expanded to also include image data processing/analysis and machine learning, with an additional focus on computations and deep learning. The current SDS Track curricula include the following four data science course sequences:

• Image processing and computer vision (EE416, EE616)
• Machine learning with linear algebra (EE 345, EE 445, EE 645)
• Optimization (EE 417, EE 617)
• Probability, statistics, stochastic processes, and statistical inference (EE 342, EE 640, EE 642)

Many SDS courses such as EE345, EE 445, EE416, and EE616 provide several programming projects with data and widely-used data science libraries. These data science courses are also offered regularly (at least once a year in a predictable schedule). In conjunction with programming and algorithm course sequences teaching data structures (EE 160, EE 205, EE 367, EE 602), the current curricula design and degree requirements in the SDS Track are capable of training data scientists with both strong background/foundation and abundant practical experience in data science.

The SDS faculty in the EE department will keep improving data science education by incorporating up-to-date technologies into course materials, creating new EEx96 projects, and designing new data science courses.