Data Science Pathway

Data  science is a new field that “focuses on the processes and systems that enable the extraction of knowledge or insights from data in various forms, either structured or unstructured”[1]. In practice, it is about taking digital data, analyzing it automatically or semi-automatically, and producing insights that can drive business or policy decisions, or that can advance scientific discovery. While data science is always an inter-disciplinary effort, it relies on software and hardware technology and hence is deeply connected to Computer Science.

Careers in data science have been hailed as “the sexiest job of the 21st century”[2]! Data science jobs are growing and projected to increase over the next several years [3]. Typical skills expected of a data scientist are: programming, data management, data engineering, data analysis, statistics, data mining, machine learning, visualization, communications.

The Department of Information & Computer Sciences offers a suite of courses that equip the undergraduate student with essential data science skills.

Data management : data cleaning, extraction, transformation, migration, manipulation, big data techniques.

  • ICS 421 Database Systems II   
  • ICS 432 Concurrent and High-Performance Programming

Data analysis: data mining, network science & machine learning

  • ICS 422 Network Science Methodology
  • ICS 435 Machine Learning Fundamentals
  • ICS 461 Artificial Intelligence
  • ICS 471 Probability, Statistics, and Queuing
  • ICS 475 Introduction to Bioinformatics Sequences and Genomes Analysis
  • ICS 476 Bioinformatics Algorithms and Tool Development

Data visualization: presenting and communicating data science results

  • ICS 484 Data Visualization

Note that these courses may have additional prerequisites at the 100-300 level.

[1] https://www.nsf.gov/cise/ac-data-science-report/CISEACDataScienceReport1.19.17.pdf

[2] https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century

[3] http://www.bls.gov/careeroutlook/2013/fall/art01.pdf