Masters in Digital Innovation
In today’s technology-driven environment, business leaders need to complement their management skills with technical acumen to create value.
Alumni Mae Keefe
At Bentley, she found that the “staff and faculty seem to make it their mission to provide opportunities and pave the way for student success.”
- Designed to hone your expertise in such areas as digital strategy, artificial intelligence, application development and data architecture, transforming your career and providing immediate value to your organization.
- Provides a wide range of industry-tested skills and knowledge in analytics and business intelligence, data management, project management and communication.
- Learn advanced technologies (AI, cloud computing, cybersecurity, and Agile methods) and programming languages (Python, Java, SQL/No-SQL), and gain hands-on experience with integrating those technologies into organizational systems to enable innovative business practices.
- Hone your skills in solving real business problems.
The Bentley MSDI prepares you for a wide range of careers, no matter the industry you are interested in. See below for a partial list of employers and job titles our alumni have achieved over the past year.
|Company Name||Alumni Title|
|Barton Associates||Business Analyst|
|Deloitte||Business Technology Analyst|
|Epsilon||Senior Business Systems Analyst|
|EY||Advisory Consultant Program Staff|
|Fidelity Investments||IT Audit Analyst|
|HCL Technologies Limited||General Manager|
|Juniper Networks||Software Engineer|
|MITRE Corporation||SharePoint Service Manager & Web Development Team Lead|
The CIS Sandbox, Bentley’s technology social learning space, offers informal learning and networking opportunities for MSDI students. Here, you’ll learn to use cutting-edge tools and technologies across analytics and IT platforms and applications, including Python, Java, cloud-based software, mobile application development, artificial intelligence applications, SQL and source control.
Average Starting Salary for IT professionals
Average age of students in this program
Million Tech-Related Jobs in the U.S.
Industry Growth Rate
Top Employers Hiring Our Graduates
Pre Program Foundation Courses
All applicants will be evaluated for foundation waivers.
This course covers basic statistical techniques in a managerial setting, and features case studies and conceptual exercises. Statistical topics include effective use of numerical and graphical summaries, estimation and confidence intervals, hypothesis testing and regression. More advanced topics such as data mining, the Bayesian paradigm and principles of model building, may be encountered during projects.
Python is an easy to learn, widely versatile programming language whose extensive collection of external libraries makes it a popular choice for business analytics and visualization, data science, artificial intelligence, scientific and numeric computing, and many other applications. Its compatibility with leading analytics tools that are widely used in enterprises also places it in high demand. Students in this course will first learn the fundamentals of programming that are common to all programming languages. They will then work with Python libraries to perform common analytics tasks. No prior programming experience is required.
Note: Students who have completed comparable coursework may be eligible to waive CS 602.
This course teaches foundational data management,retrieval, and manipulation skills with an emphasis on enabling the students to form astrong foundation for analytical processes. It builds a foundation for understandingvarious domains of practice with conceptual data modeling and demonstrates how thesame conceptual needs can be served with different data management technologies. Thecourse covers relational technologies for both operational databases and data warehousesand non-relational data management infrastructures for analytics. The course will help the students develop strong skills in the use of the SQL language for database definition anddata manipulation.
This course provides a technical focus on information, computer and network security, which together form the basis for securing enterprise systems and services. It introduces what cybersecurity means, both in the abstract and in the context of business information systems. Students learn relevant cybersecurity issues, technologies and approaches found in the contemporary enterprise. Students recognize and understand threats to privacy, confidentiality, integrity and service availability as well as best practices to defend both digital and physical assets against such threats.
This course explores the design, selection, implementation and management of enterprise IT solutions. The focus is on applications and infrastructure and their fit with the business. Students learn frameworks and strategies for infrastructure management, system administration, content management, distributed computing, middleware, legacy system integration, system consolidation, software selection, total cost of ownership calculation, IT investment analysis, and emerging technologies. These topics are addressed both within and beyond the organization, with attention paid to managing risk and security within audit and compliance standards. Students also read current vendor and analyst publications and hone their ability to communicate technology architecture strategies concisely to a general business audience.
This course provides the technical knowledge and skills for successfully managing and executing globally distributed software projects in agile and hybrid environments. Topics covered include proposal and contract management, requirements management, modeling, user experience, project planning, effort estimation, staffing, automation, status, and quality assurance. Students will learn the methods and tools that support these processes, develop a toolkit for creating a project plan for a distributed application, and engage in a project to improve these capabilities.
The course will provide a business-focused perspective on analytics in organizations, with emphasis on business fundamentals for analytics professionals (including how businesses are structured, functional areas, core business processes and associated performance metrics, and types of business decisions), the value of analytics in organizations (including organizational-level perspectives on value, managing with analytics, and constraints and consequences of analytics processes such as information security, privacy and ethics), and the practice of analytics (understanding and framing ill-defined business problems in various functional business areas, exploring and visualizing problem-related data, identifying actionable insights, and communicating the results at different organizational levels). The course will feature hands-on exercises with real-world data and analytics applications.
This course provides students with an in-depth coverage of simple and multiple linear regression methods and, as time permits, an introduction to the analysis of time series data. Simple and multiple linear regression techniques are covered, including the use of transformations such as squares and logarithms, the modeling of interactions, and how to handle problems resulting from heteroscedasticy and multicollinearity. Issues surrounding outlying and influential observations are also covered. The art and science of model building are demonstrated with the help of cases. Autocorrelation is then considered, and an introduction to the ARIMA modeling of times series is provided. Thi course makes use of statistical packages such as SAS, JMP, R or SPSS.
Two of the elective courses must be chosen from CS courses and two are unrestricted. Below are a sample of CS classes available:
This course teaches programming using the Java language, which is widely used in business. By focusing on algorithm development, data structures, logical reasoning skills, and sound programming practices, students learn to analyze and tackle business programs with software solutions. Emphasis is placed on the importance of writing and thoroughly testing code that is well structured and runs efficiently. Students first gain a solid understanding of programming fundamentals before delving into higher-order concepts, including abstract data types. Practical hands-on exercises and assignments using a well-known, integrated development environment reinforce algorithmic thinking, programming, and debugging skills. No prior programming experience is required.
This course provides a hands-on introduction to several cloud based technologies and automation tools that are commonly utilized to develop enterprise applications. The course also considers the impact of these technologies in a business context. Students learn how to develop dynamic, data-driven enterprise applications that are continuously integrated and continuously delivered. These applications enable businesses to interact with their customers, employees, and suppliers, and provide online access to information that supports decision-making. Students enrolled in this course are expected to have basic proficiency in a programming language (Java or Python) and relational databases.
The architecture of modern database systems for data analytics with big data are examined. This course provides a hands-on introduction to several architectures and approaches for data for analytics, including data from operational transactions, sensor data, web logs and social media sites. It explores the different types of data that make up the big data space, and applies capture and storage technologies appropriate for relational and non-relational models, such as clickstreams and user navigation of web sites. Data will be explored using Python-based tools for analytics and visualization. Students enrolled in this course are expected to have basic proficiency in the Python programming language and relational databases.
This course is an introduction to developing mobile applications, beginning with mobile operating system capabilities and application architecture and extending to major components, such as activities, services, broadcast receivers and others. Students learn how to develop interactive applications using widget libraries, web-based services, animation, an SQL database engine, and multithreading. Students in this course are expected to have proficiency in Java, website development an SQL queries.
This course will survey a range of new and evolving digital technologies, their applications and issues surrounding their use. This discussion-based course will be co-taught by several faculty members, who will lead class meetings, followed by discussions examining issues surrounding the use of the presented technologies in practice. The choice of topics will depend on the contributing faculty and vary from one semester to another. Assignments will include extensive readings and reflections on the topics under study, written summaries and group presentations on specific technologies, and the development of forward-looking ideas on applications of technologies of interest to students and faculty members.
This course introduces students to the foundations of artificial intelligence (AI) and its use in automation. Fundamental concepts and techniques behind software agents, automated reasoning, machine learning and robotics are introduced and illustrated with applications in various domains. Students will learn how these techniques can be integrated into business operations and functions to increase productivity and to support strategic decision making in organizations. Students will have opportunities to explore AI-based software and tools and discuss the ethical issues related to the development and use of AI.
This course extends students' knowledge and skills gained in database management courses and looks further at business intelligence and data science concepts and techniques. The course explores the data management and analytics architecture and technologies required for solving complex problems facing modern enterprises and organizations. Case studies of organizations using these technologies to support business intelligence gathering and decision making are examined. This course also provides hands-on experience with state-of-the-art data warehousing, analysis, mining, and visualization methods and tools.
This course offers a structured opportunity for exploring new business applications of emerging hardware or software technologies. It requires active student participation in developing and presenting course materials.
This course provides an opportunity for advanced MSDI students to exercise theory, knowledge and skills developed through the program, by serving as an information systems professional in a real employment environment. Through the internship coordinator, students solicit and respond to internship offers from commercial, governmental and nonprofit employers. Students maintain contact with the internship coordinator and critically analyze their work experience in a formal paper. Students have the option of making a presentation to the CIS community upon completing the internship, which normally spans one academic term.