B.S. in Data Science and Artificial Intelligence New

The bachelor of science in data science and artificial intelligence combines computer science, statistics, and mathematics to equip students with advanced techniques and tools for data-driven decision-making across various sectors. Graduates can expect a wide range of career opportunities, including roles as data scientists, data analysts, data engineers, and specialized positions in fields such as biology and business.

There are three tracks available for the B.S. in Data Science and Artificial Intelligence program;

• Computational and Big Data Analytics,
• Artificial Intelligence and Robotics,
• Statistical Modeling.

The B.S. in Data Science and Artificial Intelligence program should be followed by the student who intends to pursue a career in data science.

• The job market outlook for data scientists is rich. According to the Bureau of Labor Statistics, the employment rate for data scientists will grow by 35% through 2032. According to the 2019 Burtch Works Study, the starting salary for a Data Scientist is $95,000.

DS Prerequisites
Students should be Calculus-ready prior to enrolling in the major.

DS Core Courses

• CAP2757 Introduction to Data Science
• CAP3764 Advanced Data Science
• CAP4612 Introduction to Machine Learning
• CAP4630 Introduction to Artificial Intelligence
• CGS3095 Technology in the Global Arena
• CIS3950 Capstone 1
• CIS4951 Capstone 2
• COP3045 Python Programming II
• COP3410 Computational Thinking
• COP3465 Data Structures for IT
• COT3100 Discrete Structures or MAD2104 Discrete Math
• COT3510 Applied Linear Structures or MAS3105 Linear Algebra or MAC2313 Multivariate Calculus
• CTS1500 Emerging Topics in Digital Life
• ENC3249 Professional and Technical Writing
• STA3163 Statistical Methods I OR STA3111 Statistics I OR STA2023 Statistics for Business and Economics

DS Elective Courses (4 Courses)

• Choose four courses either from a chosen concentration, or four courses from any of the concentrations.

Computational and big data analytics

• CAI4203 Introduction to Deep Learning
• CAP4770 Introduction to Data Mining
• CEN4083 Intro to Cloud Computing
• COP4534 Algorithm Techniques
• COP4703 Information Storage and Retrieval Concepts
• COT4431 Applied Parallel Computing

Artificial intelligence and robotics

• CAI4203 Introduction to Deep Learning
• CAP4453 Introduction to Robot Vision
• CAP4506 Introduction to Game Theory
• CAP4641 Natural Language Processing
• CAP4770 Introduction to Data Mining
• CDA4625 Introduction to Mobile Robotics

Statistical modeling

• CAP4770 Introduction to Data Mining
• CAP4830 Fundamentals of Modeling and Simulations
• MAD3310 Graph Theory
• MAD3401 Numerical Analysis
• STA3164  Statistical Methods II (Prereq: STA 3163)
• STA4234  Introduction to Regression Analysis