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Data Science Certification

Data science is a multidisciplinary field that depends heavily on material from diverse areas, mostly computer science and statistics. As such, data science is an integral component of every field and application in industry, government, and education.

The Data Science Undergraduate Certificate complements many UL Lafayette majors. By completing this program you will obtain a certificate attesting to your mastery of advanced real-world job skills that are highly valued in every career area.

The objective of the Undergraduate Certificate in Data Science is to enhance your preparation for a career in data science, data analytics, statistics, or a related field. You will obtain this preparation as you work toward your bachelor's degree. This goal will be achieved by completing foundational course work in computer science, probability and statistics, applied and computational mathematics, data modeling, machine learning, and visual analytics.

Specific Learning Outcomes

  • Foundational knowledge in computer programming;
  • Foundational knowledge in computational mathematics;
  • Foundational knowledge in statistics;
  • The ability to use ideas and methods from applied and computational mathematics, statistics and computer science to tackle real world problems related to data science and machine learning;
  • Mastery of critical thinking and problem solving skills;
  • Mastery of oral and written ability in technical communications.

Course Work

Required Courses (18 Credit Hours)

Basic Level

  1. CMPS 260 Introduction to Data Structures and Software Design
  2. CMPS 261 Advanced Data Structures and Software Engineering
  3. MATH 362 Elementary Linear Algebra or MATH 462(G) Linear Algebra
  4. STAT 427(G) Statistical Methods for Researchers I

Advanced Level

  1. CMPS 320: Introduction to Artificial Intelligence and Machine Learning or CMPS 422(G) Machine Learning or MATH 487(G) Computational Mathematics
  2. CMPS 498: Special Projects or MATH 497 Special Projects

Suggested Additional Courses

  • CMPS 315 Introduction to Cyber Security
  • CMPS 340 Design and Analysis of Algorithms
  • CMPS 411(G) System Simulation
  • CMPS 420(G) Artificial Intelligence
  • CMPS 460(G) Database Management Systems
  • INFX 320 Information Assurance and Security
  • INFX 330 Information Management
  • INFX 412 Visual Analytics
  • MATH 455(G) Numerical Methods
  • MATH 483(G) Applied Graph Theory
  • QMET 420 Visual Analytics
  • QMET 430 Data Analytics II
  • STAT 325 Introduction to Probability and Statistics
  • STAT 425 Introduction to Probability Theory
  • STAT 426(G) Introduction to Statistics Theory
  • STAT 428(G) Statistical Methods for Researchers II
  • STAT 454(G) Operations Research I