Curriculum Requirements
Master of Science in FinTech and Financial Data Analytics
Major Requirements
| Business Analytics | Credits: | |
| BUSA 601 | Data Storytelling and Communication | 3 |
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This course focuses on transforming analytical insights from data into compelling visual narratives that drive strategic decision-making. Students will master the principles of effective data visualization, interactive dashboard design for key industry metrics, and the art of crafting persuasive data stories tailored to diverse stakeholder audiences (e.g., investors, regulators, management). Using industry-standard tools like Tableau and Power BI, and potentially leveraging programming libraries, students will learn to communicate analytical findings in ways that are not only clear and accessible but also influential in industry contexts. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSA 602 | Programming for Data Analysis | 3 |
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This course introduces fundamental programming skills essential for data analytics using Python and SQL. Students learn data structures, manipulation techniques, and practical coding skills to clean, transform, and analyze business datasets. Topics include data cleaning, extraction, transformation, and loading (ETL) processes, and working with APIs. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSA 660 | Foundations of AI and Machine Learning | 3 |
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This course provides a foundational understanding of artificial intelligence and machine learning with applications across business domains. Students learn how to apply supervised and unsupervised machine learning algorithms, evaluation methods, implement, and deploy them. Ethical considerations for responsible AI use are also discussed in the course. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Finance | Credits: | |
| FINC 601 | Financial Management | 3 |
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Prerequisite: Prerequisite: FINC 501 or waiver This course uses data and information technology resources and AI tools to emphasize the development of a comprehensive framework for the theory and practice of financial decision-making. Topics covered span a broad spectrum of financial markets and corporate financial practices including capital budgeting, risk management and mergers and acquisitions. AI is utilized to extract data and enhance financial analysis. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FINC 671 | Blockchain Technology and Digital Assets | 3 |
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Prerequisite: Prerequisites: BUSA 602 and FINC 601 This course explores the architecture, economics, and governance of blockchain and distributed ledger technologies, with a focus on financial applications. Students examine consensus mechanisms, cryptographic foundations, and the structure of major platforms such as Bitcoin and Ethereum. Through hands-on projects and applied financial analysis, students will create digital assets, design and test smart contracts, evaluate decentralized finance (DeFi) protocols, and assess regulatory and cybersecurity risks. The course equips students to critically analyze blockchain innovations, understand their practical use cases, and navigate the evolving FinTech landscape. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FINC 672 | Algorithmic Trading and Quantitative Methods | 3 |
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Prerequisite: Prerequisites: BUSA 660 This course offers a comprehensive introduction to algorithmic trading and quantitative methods, with a strong emphasis on practical application. Students will analyze financial market microstructure, design and implement algorithmic trading strategies, and conduct rigorous back-testing using real-world data. The course delves into the execution, slippage, transaction costs, and post-trade analytics, along with risk management and regulatory considerations. This course bridges theory and industry practice, equipping students with the quantitative and coding skills required for careers in algorithmic trading and data-driven finance. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FINC 771 | AI Applications in Financial Services | 3 |
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Prerequisite: Prerequisites: FINC 601 and BUSA 660 This course provides an in-depth analysis and application of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), and examines how they reshape the financial services industry. Emphasis is placed on developing data-driven models using structured and unstructured data - including textual information - to solve real-world financial problems. Students will gain hands-on experience building and evaluating AI models for credit scoring, asset pricing, risk management, and textual analysis of financial disclosures. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| FINC 772 | Regulatory Technology and Financial Cybersecurity | 3 |
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Prerequisite: Prerequisites: BUSA 660 This course maps modern regulation concepts to technology and cybersecurity advances, providing students with comprehensive knowledge of how technology is used to achieve regulatory compliance in fintech systems. The curriculum integrates theoretical foundations with hands-on STEM applications to prepare students to tackle challenges in financial technology and cybersecurity regulations. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Quantitative Analysis | Credits: | |
| QANT 605 | Statistical Thinking and Problem Solving | 3 |
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Prerequisite: Prerequisites: QANT 501 Covers statistical foundations for business analytics and quantitative analysis, focusing on hypothesis testing, experimental design, and critical interpretation of results. Students learn to design analytical approaches to solve business problems and measure the impact of interventions. Students will also gain proficiency in using statistical functions within Excel and AI tools to collect and validate data from existing public or private organizations. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Capstone Course | Credits: | |
| FINC 773 | FinTech Innovation and Integration | 3 |
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Prerequisite: Prerequisites: BUSA 660 and FINC 672, or instructor approval Culminating capstone course in which students design, build, and pitch a functional FinTech solution that integrates real-time data, financial APIs, cloud-based architecture, embedded finance features, and regulatory controls. Teams work with an external sponsor or vetted industry case, progressing through agile sprints, architecture reviews, and investor-style demonstrations. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Total Required Credits = 30 |