Past LDA requirements

The below requirements apply to students having declared the Certificate prior to Fall 2017.

The certificate requires 21 credits from the courses listed below depending on the area of interest.

  • Prerequisites: (not counted as certificate courses)

                 ◦  CS:1210 or equivalent Computer Science I: Fundamentals (or ENGR:2730)

                 ◦  MATH:1850 or equivalent Calculus I

                 ◦  MATH:1860 or equivalent Calculus II

                 ◦  MATH:2700 Introduction to Linear Algebra

  • Level I (6 s.h.)

                 ◦  MATH:3800/CS:3700 Elementary Numerical Analysis

                 ◦  STAT:2010 Statistical Methods and Computing

                    (this class is open to non-Statistics majors the day after Early Registration ends.)

  • Level II (9 s.h.)

        This course: STAT:3200 Applied Linear Regression

        Two of the following:

                 ◦  MSCI:3200 Database Management

                 ◦  CS:4700/MATH:4860 High Performance and Parallel Computing

                 ◦  MATH:4820/CS:4720 Optimization Techniques

                 ◦  CS:4980 Topics in Computer Science II (consult advisor for section approval)

                 ◦  STAT:5400 Computing in Statistics

                 ◦  CS:5430 Machine Learning

                 ◦  CS:5630 Cloud Computing Technology

           ➥ STAT:5810/BIOS:5310 Research Data Management may be substituted for STAT:5400 with advisor approval.

           ➥ Related courses such as Topological Data Analysis, Big Data Analytics, and selected Topics in CS (e.g. Information Visualization or Internet Measurements and Analytics) may be accepted under Level II.

  • Level III (6 s.h.)
    • CS/MATH/STAT:4740 Large Data Analysis (capstone course)
    • MSCI:4480/CS:4480 Knowledge Discovery (Known as MSCI:6421/CS:6421 prior to Fall 2016)