MS in Information Technology Management

Develop your skills as an IT leader and get ready to accelerate your career

The MS in IT Management is designed for working professionals in information technology (IT) who are looking to accelerate their careers. We created this new online degree program to meet the growing demand for IT leaders, developing a curriculum that will prepare students from both business and IT backgrounds to meet current market needs for CIOs and other tech visionaries. 

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Program start dates

  • Spring 2022: February 21, 2022
  • Fall 2022: August 22, 2022

Applications for Kelley programs offered via edX may be submitted on a rolling basis. Should you be admitted to the master’s program, you would begin courses through Indiana University in the next available spring or fall term, pending completion of your MicroMasters® courses via the edX platform.


Complete this 30 credit hour degree in 21 months to three years, and graduate prepared to:

  • Be knowledgeable about business processes and the integration between business functions and technology
  • Analyze, design, and develop IT systems
  • Lead IT management and strategy—both of people and systems
  • Use data and visualizations to support managerial decisions

If you have an undergraduate degree in business, computer science, informatics, information technology, or engineering, an MS in Information Technology Management can refine your focus as a specialist. If you have an MBA, this degree will help you develop more in-depth analytical expertise.

You’ll start with three MicroMasters® courses on the edX online learning platform. If accepted into the MS in IT Management program, your three courses will count towards the master’s degree. Once these first three courses are complete, admitted applicants will then start the master’s degree program and be considered an IU student.

Apply for MicroMasters®

 

Course descriptions

  • Understand the upstream management of data with focus on activities related to the modeling, storage, and retrieval of data, wrapped within concepts related to enterprise data management and data.
  • Become proficient with the use of a variety of tools related to data management. Practical, hands-on experience with tools such as SQL.
  • Part of MicroMasters® 

  • IT’s unique leadership challenges and evaluating the role of the CIO and issues related to skill and talent.
  • How the IT function operates in an organization. Learn how IT departments set priorities and provide financial justification for IT investments. Explore different project management approaches and strategies for handling at-risk projects.
  • IT’s impact on the organization and integration with other organizational functions, including security risks and crises that impact the entire organization. Discuss the need for senior-level support and cross-functional teams for success on large-scale projects.
  • Current and emergent technologies and learning about emerging technologies in the market. Assess the business value of pursuing these technologies versus finding new uses for existing tech. Explore the balance between standardization and innovation of technology within the organization.
  • Part of MicroMasters® 

  • System and infrastructure virtualization and building a cloud infrastructure.
  • Understand the changing role of the IT organization as companies migrate to the cloud architecture.
  • Explore security issues related to deploying cloud-based systems and services.
  • Study best practices of cloud deployment including consideration of risks, governance, and compliance related to cloud computing.
  • Explore future trends including software-defined data centers and warehouse-scale data centers.
  • Part of MicroMasters® 

High-quality information is the key to successful management of businesses. Despite the large quantity of data collected by organizations, managers struggle to obtain information that would help them in decision-making. Big data sets, which have a higher variance in format, a higher velocity in generation, and a much higher volume, require modern solutions for storage and management. This course focuses on understanding and realizing the business advantages and business potential of data stored in big data systems, through machine learning and exploring select big data technologies.

The second half of this course will be focused on machine learning techniques, which prepare students to effectively analyze data to improve prediction performance and robustness, and to distill useful information from a large amount of data to support managerial decision-making processes. We will apply machine learning to various business contexts. We will introduce various machine learning models and use Python-based machine learning packages to implement these models, making advanced machine learning tools accessible to business students.

  • Develop business capabilities for the digital future, which involves rethinking the current way of doing business in the context of understanding where the new frontiers of digital value may lie.
  • Focus on artificial intelligence (AI) and automation (especially robotics process automation and intelligent process automation), and their applications to both digital processes and digital products.
  • Examine the rise of AI and the forces propelling that rise: big data, algorithm advances, and increases in processing power.
  • Dive into the role of AI in modern organizations and the impacts that AI might bring to customers. Review how big data and algorithm advances affect the development of artificial intelligence, followed by a showcase of AI in the cybersecurity realm.
  • Discuss the impact of robotics process automation (RPA) and intelligent process automation (IPA) in business.
  • Examine smart cities, societal implications of AI, and the use of AI for good and for automation.

  • Learn ways to organize data
  • Use Excel’s Power Query add-in to Get and Transform data from external sources
  • Understand data types and the implications of data types on analytical techniques
  • Calculate basic statistical measures to describe distributions
  • Use simple charts and graphs to visualize patterns within data
  • Explore pivot tables, Excel tables, and advanced functions within Excel
  • Explore the Excel data model, KPIs, and Power BI tools in Excel
  • Learn about Power BI (Desktop/Cloud)

Organized into four modules, this course will provide students with an end-to-end introductory AI for cybersecurity education that includes a primer to fundamental cybersecurity concepts, terminology, and knowledge; a summary of prevailing cybersecurity data sources, characteristics, and data-generating processes; and an overview of state-of-the-art AI architectures such as RNN, CNN, GCN, and training and learning strategies such as deep Bayesian learning, adversarial learning, and transfer learning; and communicating AI for cybersecurity knowledge and insights to selected communities and audiences.

  • Enterprise platforms are the digital core of an organization. These are the technologies that digitize and enable enterprise processes, such as planning, procurement, production, sales and distribution, and customer/supplier relationships. Business and technology professionals should benefit from learning about enterprise platforms to enhance their knowledge of how these technologies enable and support business processes and help integrate various functional areas of a business.
  • A combination of conceptual and experiential pedagogical approaches will be used using industry-leading technologies to help students develop a practical understanding of how enterprise platforms and associated technologies support today’s digital enterprises. Students will develop an appreciation for tight integration and the need for close cooperation among business functions enabled by enterprise platforms.

  • Applications of digital innovations such as telematics, Industry 4.0, omnichannel, additive manufacturing, artificial intelligence, and augmented reality/virtual reality in operations management
  • Application of blockchain, Industry 4.0 in sourcing
  • Application of robotic process automation in designing operations processes

  • Understand unique database requirements of the Internet of Things (IoT); compare and contrast platforms such as Microsoft Azure, AWS, and other IoT platforms.
  • Edge Computing: vision and challenges; use Microsoft Azure to capture streaming sensor data.
  • Understand the decision process for data capture and aggregation of data. Use Microsoft Azure, IoT Hub, and Stream Analytics to analyze and visualize time series data.
  • Understand common forecasting techniques for IoT and time series data (including but not limited to ARIMA, Kalman filters, and Fourier transforms).
  • Case studies of the smart factory
  • Future trends of IoT

Academic calendar 2021-22

Kelley via edX observes an efficient four-term calendar designed for students who are also working professionals. You can complete the MS program in just over one year. The fall, winter, spring, and summer terms are 12 weeks long. The winter term includes a one-week break for the holidays.

TermsDatesBreaks
FallAug. 23–Nov. 11N/A
WinterNov. 15–Feb. 17Nov. 22–28, Dec. 25–Jan. 2, Jan. 17
SpringFeb. 21–May 12N/A
SummerMay 23–Aug. 11May 30, June 20, July 4

The live sessions are helpful and I’m really enjoying the program. The program is relevant and useful in my daily work.

Muhammad Butt, MSITM'20

Opportunity is waiting for you at Kelley