DATASC2:BS - Bachelor of Science in Data Science and Artificial Intelligence
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Academic Progression Requirements
Steady academic progression is expected by the College of Engineering and Computing. Students who are unsuccessful in passing common pre-requisites after two attempts will be advised to change their major into an area where they can be successful. Drops after the add/drop period, which result in a DR grade, are considered an attempt in the course and count as an unsuccessful enrollment.
Students must also meet the Math Progression standard of successfully completing Calculus 1 within three academic terms, not counting summers.
Students will be redirected to a different degree program when completion of the progression standards, including the applicable math progression standard by its stated semester, is no longer feasible.
Students may take any COP2XXX-X999 Computer Programming course at FIU in place of COP2047
Students may take any Natural Science Group 1 or Group 2 course with lab or BSC 2010/L.
Upper-Division Requirements
At least 50% of the upper division credits required for the BA in Data Science and Artificial Intelligence must be taken at FIU.
The Bachelor of Science in Data Science and Artificial Intelligence program will comprise 120 credit hours and will offer students the option to pursue one of the concentrations: Computational and Big Data Analytics, Artificial Intelligence and Robotics, and Statistical Modeling.
Students may broaden their expertise by selecting electives from the up-to-date list of elective courses maintained by the Knight Foundation School of Computing and Information Sciences. For more details and to view the lists of electives (and determine pre-requisites), please visit: KFSCIS's Electives Page for BS in DS & AI.
Students complete 4 courses within one concentration, or students complete 4 courses from any of the concentrations:
Computational and Big Data Analytics
Artificial Intelligence and Robotics
Statistical Modeling
Students must follow regular University admission procedures and upon admission declare their specific major as Data Science and Artificial Intelligence.
There are no majors associated with this program.
Concentration in Computational and Big Data Analytics
Strong emphasis on developing programming and analytical skills, as well as gaining a solid understanding of computer science principles, and encourages students to apply the latest technologies in data storage, manipulation, security, retrieval, mining, machine learning, AI, and cloud computing.
Concentration in Artificial Intelligence and Robotics
Developing algorithms and computational techniques to enable machines to learn, reason, and adapt, empowering them to solve complex problems and enhance decision-making processes.
Concentration in Statistical Modeling
Statistically driven decision making with emphasis on mathematical theory that underlies the models and programming.
*STA3164: Prerequisite course is STA3163.