Undergraduate Programs


Data Science

  • DSCI-D 321 Data Representation (3 cr.) P: CSCI-A 310 or C 343. This course covers a wide variety of data representations and data processes that are core parts of the data/information ecosystem. The focus is on essential aspects and mechanisms of data engineering to prepare data for data science and machine learning problems and applications.
  • DSCI-D 351 Big Data Analytics (3 cr.) P: CSCI-C 200 or C 211 This course introduces the fundamentals of data science and big data analysis by focusing on: theoretical aspects, such as their philosophical grounds and implications, and methodological aspects, such as large-scale data processing, statistical analysis and machine learning, data retrieval and recommendation, data representation and semantics, along with several case studies.
  • DSCI-D 390 Undergraduate Independent Study (1-3 cr.) Department Approval. Independent research based on existing literature or original work. A report, in the style of a department technical report, is required. May be repeated for a maximum of 6 credit hours.
  • DSCI-D 498 Data Science Capstone I (3 cr.) P: DSCI-D 321, DSCI-D 351, INFO-I 123, and STAT-S 352. This first course of two introduces students to a real-world, group project that includes statement of work, requirements gathering, data science system design and implementation, product delivery, and assessment of work. The first course is devoted to identifying team projects, understanding the customers' needs and preliminary tasks for the project.
  • DSCI-D 499 Data Science Capstone II (3 cr.) P: DSCI-D 498. This second course of two completes a team-based, real-world project that solves a data science problem. The students develop a project plan, milestones, design and implement solutions, and give a product including a write-up, code base, and interpretation of results. Students also learn additional elements of data science e.g., ROC.

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