Master of Science in Data Science & Artificial Intelligence

Program Overview

The Master of Science in Data Science & Artificial Intelligence from Florida International University offers various specialization tracks to equip graduates with the skills to analyze complex data, develop predictive models, and apply data-driven insights in fields such as healthcare, finance, and public policy. The program includes a capstone project, elective courses, and support from faculty mentors, preparing graduates for careers as data scientists, analysts, and policy experts.

Program Outline

Degree Overview:

• The Master of Science in Data Science & Artificial Intelligence program is offered by the Knight Foundation School of Computing and Information Sciences at Florida International University.
• Students are required to select a specialization track when applying: Computational Data Analytics, Business Analytics, Biostatistics Data Analytics, and Public Policy Analytics.
• The program aims to equip graduates with the knowledge and skills necessary to analyze and interpret complex data, develop predictive models, and apply data-driven insights to solve real-world problems.

Outline:

• Core Courses (12 credits):
• CAP 5768 Introduction to Data Science (3 credits): Foundations of databases, analytics, visualization, and data management.
Practical data analysis with applications. Introduction to Python, SQL, R, and other specialized data analysis toolkits. Prerequisites: STA 3164 or equivalent.
• CAP 5771 (or COP 5577) Principles of Data Mining (3 credits): Introduction to data mining concepts, knowledge representation, inferring rules, statistical modeling, decision trees, association rules, classification rules, clustering, predictive models, and instance-based learning.
Prerequisites: COP 4710 and STA 3033. Prerequisites: STA 3033, STA 4322, or STA 6327.
• CAP 5602 Introduction to Artificial Intelligence (3 credits): Presents the basic concepts of AI and their applications to game playing, problem solving, automated reasoning, natural language processing, and expert systems.
Prerequisite: COP 3530.
• For Biostatistics and Business Data Analytics students only:
• Replace STA 6244 with QMB 6357 Business Statistics Analysis (Business Data students) or PHC 6052 Biostatistics 1 (Biostatistics Data students).
• Capstone (3 credits):
• IDC 6940 Capstone Course in Data Science (3 credits): Projects course using Python, SQL, R, and/or other specialized analysis toolkits to synthesize concepts from data analytics and visualization as applied to industry-relevant projects.
Prerequisite: CAP 5768.
• ISM 6930 Special Topics in Management Information Systems (IS) (1-6 credits): To study the recent developments in the MIS field not otherwise offered in the curriculum, such as office automation, computer graphics, etc.
Prerequisites: Advanced standing and department chairman approval. (Business Analytics only)
• Specialization Tracks (15 credits):
• Computational Data Analytics:
• Choose 5 from a list of 19 elective courses in areas like Advanced Human-Computer Interaction, Bioinformatics, Machine Learning, Natural Language Processing, Data Visualization, Information Retrieval, Database Systems, Network Analysis, Security, and Algorithms.
• Artificial Intelligence:
• Choose 5 from a list of 12 elective courses in areas like Game Theory, Bioinformatics, Affective Intelligent Agents, Machine Learning, Neural Networks, Digital Image Processing, and Expert Systems.
• Business Data Analytics:
• Choose 5 from a list of 7 elective courses in areas like Business Analytics Applications, Database Management, Data Warehousing, Data Visualization, Data Analysis II, Advanced Topics in Data Mining, and High Dimension Data Analysis.
• Biostatistics Data Analytics:
• Choose 5 from a list of 10 elective courses in areas like Longitudinal Health Data Analysis, Survival Data Analysis, Applied Statistical Methods for Discrete Data, Probabilistic Graphical Models, SAS Computing, Introduction to Bayesian Inference, R Computing, Advanced Bayesian Inference, Multivariate Methods in Health Sciences Research, and Biostatistics 2.
• Public Policy Analytics:
• Choose 5 from a list of 6 elective courses in areas like Policy Analysis & Planning, Political, Social & Economic Context of Public Administration, Public Economics & Cost Benefit Analysis, Public Policy Analysis & Evaluation, Leadership & Decision-making, and Data Analysis II.

Assessment:

• Capstone: Students are evaluated by a committee of faculty members and assigned a letter grade.
The course will have a coordinator in addition to the mentors/supervisors for individual projects.

Teaching:

• Capstone: The class meets biweekly to learn from analysis case histories, monitor project progress, have class presentations, and evaluate project progress reports.

Careers:

• The program aims to prepare graduates for careers in various fields where data analysis and AI are critical.
• Potential career paths:
• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Business Analyst
• Biostatistician
• Public Policy Analyst
• Research Scientist
• Opportunities: The program highlights the growing demand for data professionals in various industries, including healthcare, finance, technology, and public sector.

Other:

• The program provides a list of faculty mentors for the Computational Data Analytics track.
Students in other tracks should contact the Specialization Track Coordinator associated with their track.
• Students are encouraged to identify an external mentor in addition to their project mentor from FIU.
• Sample projects can be found at data analysis challenge websites like Kaggle and Dream Challenges.

The estimated cost of a full-time spring or fall semester (9 credits) is $4,295.15 for Florida residents and $9,209.60 for non-Florida residents. The M.S. in Data Science consists of 30 credits. These estimates do not include online course fees. Tuition and fees are paid on a semester basis. Tuition, fees, and the above estimates are subject to change.