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Curriculum

Empowering you to navigate the future of IT and business.

The Master of Science in Information Systems (MSIS) offers an innovative, AI-infused curriculum that covers emerging concepts and relevant technologies, preparing you to meet current industry needs and challenges. Our integrated core curriculum is designed to build both technical and IS/IT management skills across key knowledge areas in the Information Systems domain, with artificial intelligence embedded throughout the learning experience.

Our courses provide a deep dive into business analytics, artificial intelligence, machine learning, and cloud technologies, with AI integrated across coursework, projects, and practical applications. You will benefit from hands-on instruction incorporating the latest technologies, including Microsoft Project and Scrum Workbook, ERP, SAP, MySQL, SQL Server, UML, RapidMiner, Tableau, Python, R, blockchain and Solidity programming, machine learning and AI toolkits, Amazon Web Services, and more.

Place yourself at the intersection of IT, business, and AI to bridge critical gaps, drive innovation, and improve organizational efficiency.

Core Courses (18 credits)

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  • Project Management

    Introduces relevant project management body of knowledge that business and IS project managers are required to effectively plan and execute projects in contemporary organizations. Emphasizes the holistic and practical roles of structured and agile project management frameworks, approaches, techniques, and tools.

    Software: Traditional project mgmt. tools (e.g., MS Project) and agile project management and simulation tools.

  • Database Management

    Covers principles of designing and implementing transactional databases within a contemporary cloud environment, extracting valuable insights, monitoring resource usage, and optimizing performance.

    Software: Oracle Cloud with APEX, or MySQL Workbench, Snowflake/AWS with Streamlit and Snowsight.

  • Business Process Design

    Covers fundamentals concepts, principles, and techniques that can be used to improve business performance through the analysis, modeling and design of the as-is and the to be business processes.

    Software: Business process modeling and analytical simulation tools (e.g., Lucidchart).

  • Systems Analysis and Design

    Introduces students to the field of Systems Analysis and Design in general, and focuses in-depth on object-oriented concepts, methodologies, models, and skills, along with associated software tools.

    Software: UML Design tools (Lucid, Visual Paradigm), Python, IDEs for Python (Thonny, Visual Studio Code).

  • Information Security Management

    Focuses on the managerial aspects of information security including access control models, information security governance, and information security program assessment and metrics. Foundational and technical components of information security is included to reinforce key concepts.

    Software: Wireshark, Webgoat, Security Onion.

  • Information Systems Strategy and Governance

    Equips students to align information systems with organizational goals, focusing on strategic planning, governance, and leveraging IS for competitive advantage.

Business Analytics Track
16 months, starts in fall (August)

Provides advanced analytical skills and knowledge in big data and quantitative analysis. You will gain a unique combination of analytical and information systems management skills utilized to uncover trends and predict patterns specific to businesses. You will develop the skills and know-how to provide critical insights and recommend solutions on how businesses can increase their effectiveness through their processes, products, services, software, and technology systems.

Specialized Courses (18 Credits)

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  • Python Fundamentals for Business Analytics

    Provides a comprehensive introduction to Python programming, focusing on the essential concepts and libraries required for data science, AI and business analytics. Covers basic programming constructs, data manipulation, and visualization techniques using Python. Students learn how to leverage Python's powerful libraries, such as Pandas, NumPy, and Matplotlib, to analyze and visualize business data, enabling them to make data-driven decisions. Students develop the foundational skills necessary to apply Python in various business analytics scenarios.

    Software: Jupyter Notebook.

  • Quantitative Analytical Methods in Business

    Provides a practical introduction to the relevant quantitative techniques required for business analysis and decision-making, including hypothesis testing, decision models, statistics, and forecasting. Python and Excel will be used for quantitative analysis. This is a hands-on course in the use of quantitative methods for turning data into information and information into good business decisions for managers, researchers, and students in the field of business. Providing a framework for the development of sound judgement and the ability to utilize quantitative and qualitative approaches, this course introduces students to the important role that data plays in understanding business outcomes and improving business processes.

    Software: Jupyter Notebook, Google Colab, Microsoft Excel.

  • Machine Learning for Business Applications

    Provides students with an in-depth understanding of the core concepts and techniques of machine learning, tailored specifically for business contexts. Using Python, students learn how machine learning can be effectively integrated into various business sectors and understand the benefits and challenges of integrating machine learning models into business operations.

    Software: Jupyter Notebook, Spyder.

  • Business Data Exploration and Visualization

    Provides essential skills of business analytics: data exploration and visualization. It encompasses three main components: understanding data, formulating research questions, and utilizing data exploration and visualization tools. Students learn to explore and visualize various data types, enhancing communication with collaborators and target audiences. The curriculum covers identifying relevant data, addressing practical business research questions, and mastering tools such as Python, R, Tableau, and PowerBI to uncover meaningful patterns and insights.

    Software: Python, generative AI tools with Tableau and Power BI.

  • Cloud Data Warehousing

    Examines contemporary methodologies shaping data warehousing, with emphasis on cloud based solutions, ingesting semi-structured data from data lakes, and leveraging AI tools to streamline data flows.

    Software: Snowflake Cloud Services with connection to AWS, Tableau Prep Builder and Tableau Desktop, and Power BI.

  • Business Analytics Capstone (project-based)

    Offers practical experience in applying business analytics and artificial intelligence to solve complex, real-world business problems. Students explore predictive analytics, data visualization, and geospatial analysis while developing technical proficiency with tools like TensorFlow, PyTorch, and generative AI. Through collaborative projects, students design innovative solutions, conduct sentiment analysis, and refine strategies based on data-driven insights. The course culminates in a final presentation, integrating key findings into actionable recommendations that demonstrate the impact of analytics on business success.

    Software: Python, generative AI algorithms with Google Colab.

Artificial Intelligence Track
16 months, starts in fall (August) - 12 months, starts in spring (January)

Provides a deep understanding of how to leverage AI to effect digital transformation, value creation, and competitive advantage. Students will focus on developing AI skills and the ethical implementation of AI in business. Courses will cover AI technologies, their development, and business applications and strategies. With a strong emphasis on ethical considerations in AI, graduates are prepared to develop, evaluate, refine, and implement AI-related applications and technologies responsibly in various industries and pursue careers in information systems in both private and public sectors.

Specialized Courses (18 Credits)

Expand all
  • Python Fundamental for Business Analytics

    Provides a comprehensive introduction to Python programming, focusing on the essential concepts and libraries required for data science, AI and business analytics. Covers basic programming constructs, data manipulation, and visualization techniques using Python. Students learn how to leverage Python's powerful libraries, such as Pandas, NumPy, and Matplotlib, to analyze and visualize business data, enabling them to make data-driven decisions. Students develop the foundational skills necessary to apply Python in various business analytics scenarios.

    Software: Jupyter Notebook.

  • Quantitative Analytical Methods for Business

    Provides a practical introduction to the relevant quantitative techniques required for business analysis and decision-making, including hypothesis testing, decision models, statistics, and forecasting. Python and Excel will be used for quantitative analysis. This is a hands-on course in the use of quantitative methods for turning data into information and information into good business decisions for managers, researchers, and students in the field of business. Providing a framework for the development of sound judgement and the ability to utilize quantitative and qualitative approaches, this course introduces students to the important role that data plays in understanding business outcomes and improving business processes.

    Software: Jupyter Notebook, Google Colab, Microsoft Excel.

  • Machine Learning for Business Applications

    Provides students with an in-depth understanding of the core concepts and techniques of machine learning, tailored specifically for business contexts. Using Python, students learn how machine learning can be effectively integrated into various business sectors and understand the benefits and challenges of integrating machine learning models into business operations.

    Software: Jupyter Notebook, Spyder.

  • Artificial Intelligence Strategy

    Explores strategic implementation of AI in business, covering AI applications, value creation, ethical considerations, and organizational transformation. Focuses on developing AI strategies for competitive advantage across industries.

  • Business AI Applications

    Covers the implementation of Al methods in business problem-solving. As an interdisciplinary set of skills, artificial intelligence draws from a broad range of fields such as deep learning, natural language processing and cloud computing to effectively collect, store and process large amounts of data. This course will provide an understanding of fundamental artificial intelligence concepts and applications in today’s business environment.

  • Business AI Capstone (project–based)

    Equips students with the skills to develop, launch, and manage AI based software products. Focuses on the intersection of business, technology, and data, emphasizing the unique challenges and opportunities AI presents in product development.

Should you need an ADA accommodation to participate in a University event, program, or activity or need to request materials in an accessible format, please contact FIU's Office of Civil Rights (OCR) at 305-348-2785 or accommodations@fiu.edu. All requests for ADA accommodation or accessible materials for this event must be submitted to OCR at least seven (7) business days prior to the event or at the earliest possible opportunity.

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