MS-AIM Courses
Credit Hours
Analytics and Information Management* 3.0
Information Systems Ecosystem 3.0
Data Querying* 3.0
Data Sourcing and Quality 3.0
Data Analytics with Artificial Intelligence* 3.0
Data Structures  3.0
Behavioral Analytics with Visualization* 3.0
Project, Process, & Persuasive Communication 3.0
Application of Data Analytics* 3.0
Business Analytics Capstone 3.0
30 Credits

* Included in Certificate Program

Analytics and Information Management *
Statistical and technical understanding are essential for the AIM professional. This course focuses on creating a solid foundation of technical skills, which will be applied in downstream courses. Topics will include programming concepts and logic, descriptive, predictive and prescriptive statistics, and data storage techniques. Prerequisites: None

Information Systems Ecosystem 
Within the context of data analytics, this course teaches students to manage information as a strategic asset with the potential to create significant business value. Students will be exposed to various approaches to managing the capture, retention and disposition of information. Special emphasis will be placed on the legal/regulatory, ethical, risk management and cybersecurity requirements of managing information.  Topics include the role of information systems in an organization, information systems governance (which is designed to ensure that IT investments create organizational value), data governance (which seeks to ensure that organizational data meet the standards for quality data), and strategies for identifying measurable sources of ROI. Prerequisites: None

Data Querying *
Modern organizations use database management systems to store their critical business data. In this course, students learn to answer business questions using various data retrieval, manipulation and transformation tools.  For instance, data retrieval for most data-driven business applications relies on Structured Query Language (SQL) - the international standard language for data manipulation and retrieval.  To source the data required by analytics projects, students will learn to utilize SQL along with other data-related concepts and languages. Prerequisites: None

Data Sourcing and Quality
Increasing amounts of data are available from both internal and external sources for use in organizational decision-making. This course covers the objectives, methods and skills for sourcing data from internal and external databases as well as sourcing data directly from primary data sources. Techniques will include programming with APIs, web scraping, and surveys. Students will also learn a variety of methods for examining and enhancing the quality of acquired data. Prerequisites: None

Data Analytics with Artificial Intelligence *
Artificial Intelligence (AI) technologies are widely adopted and applied in various contexts. Applications of AI include financial services, cyber security, web search, targeted product recommendations, self-driving cars, personal assistants, robotic manufacturing, machine translation, and video games. Such applications use AI techniques to interpret information from a wide variety of sources to enable intelligent, goal-directed behavior. Companies are increasingly applying these AI technologies and techniques to uncover new business insights and assist managers with making better informed and timely decisions. This course will cover concepts and algorithms in artificial intelligence with an emphasis on machine learning. Fundamental concepts and base knowledge for understanding AI, such as basic search algorithms for problem solving, knowledge representation and reasoning, pattern recognition, fuzzy logic, and neural networks, will be introduced. Prerequisites: ISYS 610 Analytics and Information Management

Data Structures
Organizations have more opportunities than ever before to collect, organize and store internally- and externally-generated data. Such data are used to support organizational operations, managerial decision-making, and strategic planning. This course will examine multiple types and sources of data, including how it is collected and stored in relational and non-relational databases.  The focus is on understanding the structure of the data and designing structures appropriate for various organizational needs. Prerequisites: ISYS 612 Data Querying

Behavioral Analytics with Visualization *
E-commerce and social media have experienced rapid growth during the past decade. Billions of users have been generating and sharing a variety of social content including text, images, videos, and related metadata. Social media can be viewed as an indicator reflecting different aspects of the society, and organizations can combine this with their existing data to support organizational decision-making. In this course, students will learn how to analyze behavioral data and apply the analyses to answer business questions. Advanced regression techniques, network concepts, and social theories will be covered throughout the course. Prerequisites: ISYS 610 Analytics and Information Management

Project, Process, and Persuasive Communication
Two foundational attributes of an outstanding data analyst are: 1) a fundamental ability to ask insightful business questions using a purposeful, scientific approach, and 2) to be able to tell a ‘story' regarding how the results of the analytical process can be turned into operational assets for different stakeholders.  Industry leaders find that being able to build and present a storyboard using the data are becoming even more critical than the data extraction skills alone.  As such, a focus of this course is building Socratic questioning and storytelling abilities within the analytics ecosystem. Other course topics will include project management methodologies, decision-making models, persuasive presentation techniques, and business process documentation. Prerequisites: None

Applications of Data Analytics *
The 21st century has been called by many ‘The Century of Data.' The explosion of social media and the digitization of many aspects of social and economic activity have resulted in the creation of large amounts of data in a variety of formats. At the same time, computers are becoming more powerful, and storage is becoming less expensive. This combination of factors has resulted in the availability of much richer data. By applying advanced analytical techniques to these data, organizations hope to uncover hidden insights that will yield competitive advantages. The key objective of this course is to equip students with knowledge about how organizations are applying analytical techniques in various business situations, as well as the associated technical, conceptual and ethical challenges associated with the application of such techniques. Prerequisites: ISYS 620 Data Analytics with Artificial Intelligence, ISYS 622 Behavioral Analytics with Visualization, ISYS 612 Data Querying

Business Analytics Capstone
In this course, student teams work with a real company to develop a data analytics-based recommendation for advancing the business.  The project is the program's capstone experience designed to provide students the opportunity to utilize the methods, skills and techniques acquired throughout the program to solve a real-world business challenge.  In doing so, students will experience what it is like to make high-stakes and impactful recommendations to top management under time-pressure and with high expectations for quality and analysis. Prerequisites: ISYS 620 Data Analytics with Artificial Intelligence, ISYS 622 Behavioral Analytics with Visualization, ISYS 612 Data Querying, ISYS 623 Project Management and Communication, ISYS 613 Data Sourcing and Quality