Online MS in Innovation & Entrepreneurship, Technology

At a Glance

Completion Time

8–16

Months

Credits Required

Tuition

$25,452–$27,204

Part-Time*

*Based on 2025–2026 Boston University tuition and fees. Merit scholarship may reduce cost.

Harness Emerging Technologies to Drive Business Innovation and Growth

The online MS in Innovation & Entrepreneurship concentration in Technology develops the technical expertise and analytical skills needed to fuel technology-driven innovation and data-informed decision-making. Through hands-on training in business analytics, Python programming, and SQL, you’ll develop the tools needed to launch and grow ventures in today’s rapidly evolving tech landscape.

Customize your learning by exploring cutting-edge topics such as blockchain finance, AI-powered business analytics, web and data mining, and enterprise risk analytics. BU MET’s Innovation & Entrepreneurship master’s concentration in Technology prepares you to leverage advanced technologies and venture financing strategies that support sustainable business expansion and ongoing innovation across industries.

The MS in Innovation & Entrepreneurship, Technology concentration is also available on campus in Boston. Learn more.

Curriculum

A total of 32 units is required.

Students are required to finish four core courses and the Technology concentration requirements.

Core Courses

(Four courses/16 units)

MET AD 514 The Innovation Process: Developing New Products and Services

4 credits.

Addresses the specifics of new product and service development and fostering innovation and technology to increase performance. Topics include generating and screening initial ideas; assessing user needs and interests; forecasting results; launching, and improving products and programs; and overall bringing innovation from ideation to commercialization.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Lopez	Independent	M	06:00:00 PM–08:45:00 PM	SHA 202

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Park	Independent	T	06:00:00 PM–08:45:00 PM	PSY B51

Section A3, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Lopez	Independent	W	06:00:00 PM–08:45:00 PM	HAR 210

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Park	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 667 Innovation, Global Competitiveness, and National Economic Development

4 credits. Fall and Spring

Examines various approaches to developing high tech innovation based economies as a route to self sufficiency and growth. Factors studied include both structural reforms in the political, legal and economic areas, and government sponsored initiatives in higher education, basic research, private venture capital, grants to support new product development by promising ventures, and the creation of science and technology parks and incubators. Students independently research, write, and present studies of the strategies of various countries. This will be augmented by case studies, reading, and guest speakers on strategies being employed in such countries as Taiwan, Thailand, and Brazil.

MET AD 740 Planning and Operating New Ventures

4 credits. Fall and Spring

Graduate Prerequisites: MET AD741 - Includes opportunity assessment and feasibility analysis, concept development, budgeting and financial operations, financial and human resource management, legal and organizational issues analysis, and comprehension and determination of the roles of boards and external advisors, all leading into the planning and operating of new ventures.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Park	Independent	M	06:00:00 PM–08:45:00 PM	COM 217

Concentration Requirements

(Four courses/16 units)

MET AD 571 Business Analytics Foundations

4 credits. Fall and Spring

Prerequisite: METAD100 Pre-Analytics Laboratory. This course presents fundamental knowledge and skills for applying business analytics to managerial decision-making in corporate environments. Topics include descriptive analytics (techniques for categorizing, characterizing, consolidating, and classifying data for conversion into useful information for the purposes of understanding and analyzing business performance), predictive analytics (techniques for detection of hidden patterns in large quantities of data to segment and group data into coherent sets in order to predict behavior and trends), prescriptive analytics (techniques for identification of best alternatives for maximizing or minimizing business objectives). Students will learn how to use data effectively to drive rapid, precise, and profitable analytics-based decisions. The framework of using interlinked data inputs, analytics models, and decision-support tools will be applied within a proprietary business analytics shell and demonstrated with examples from different functional areas of the enterprise. R, SQL, and Power BI software are used in this course.

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Padalkar	Independent	M	06:00:00 PM–08:45:00 PM	CAS 324

Section A5, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Parzen	Independent	W	02:30:00 PM–05:15:00 PM	CDS 262

Section A6, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Ritt	Independent	W	02:30:00 PM–05:15:00 PM	MET 101

Section A7, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Page	Independent	R	06:00:00 PM–08:45:00 PM	PSY B53

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Rabinovich	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 599 Python and SQL for Business Analytics

4 credits. Fall and Spring

Prerequisites: AD100 - Python is a modern, high-level programming language. One of the most popular programming languages, its use has steadily increased across a large number of industries. This course introduces students to the Python environment and teaches a solid foundation in the basic syntax and structure. Structured Query Language (SQL) is the most common language globally for interacting with relational databases. Employers have indicated that knowledge of SQL is one of the most important skills for new graduates entering the workforce. Even with advances in database technologies and languages for handling heterogeneous data types, SQL remains the core skill for interacting with data. This course introduces both languages to equip students pursuing an analytics education with the skills necessary to succeed in the analytics and data visualization field. The outcome of this course will be a focused survey of Python and SQL topics designed to equip analytics professionals rather than a deep focus on technical programming topics.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Valath Bhuan Das	Independent	M	06:00:00 PM–08:45:00 PM	MET 101

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Valath Bhuan Das	Independent	W	06:00:00 PM–08:45:00 PM	CAS 214

Section A3, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Yu	Independent	M	06:00:00 PM–08:45:00 PM	EPC 206

And one of the following:

MET AD 561 Financial Analytics

4 credits. Fall and Spring

This course presents financial algorithms used in applications of computer science in financial decision analysis, risk management, data mining and market analysis, and other modern business processes. The course covers theoretical background on probabilistic methods used for financial decision making and their application in number of fields such as financial modeling, venture capital decision making, operational risk measurement and investment science. Number of financial applications and algorithms are being presented for portfolio risk analysis, modeling real options, venture capital decision making, etc. The course concludes with algorithms for financial risk assessment and presents the security concepts and challenges of financial information systems.

MET AD 616 Enterprise Risk Analytics

4 credits. Fall and Spring

Prerequisite: MET AD 571. - The course offers an overview of the key current and emerging enterprise risk analytical approaches used by corporations and governmental institutions and is focused on understanding and implementing the enterprise risk management framework on how to leverage the opportunities around a firm to increase firm value. The major risk categories of the enterprise risk management such as financial risk, strategic risk, and operational risk will be discussed and risk analytics approaches for each of these risks will be covered. Students will learn how to use interlinked data inputs, analytics models, business statistics, optimization techniques, simulation, and decision-support tools. An integrated enterprise risk analytics approach will be demonstrated with examples from different functional areas of the enterprise. Python, R, SQL, and Power BI software are used in this course.

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Yu	Independent	T	06:00:00 PM–08:45:00 PM	PHO 203

Section A3, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Yu	Independent	R	12:30:00 PM–03:15:00 PM	FLR 121

Section O2, FALL 2025 Oct 28th to Dec 15th
Instructor	Type	Days	Times	Location
Yu	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 685 Quantitative Methods for Finance

4 credits. Fall and Spring

Finance is a highly competitive and dynamic industry that demands quantitative oriented professionals. This course will equip students with the empirical techniques which are used in the analysis of financial markets with a strong focus on financial applications using actual data. The goal of this course is to provide students with a number of econometric techniques which are used in the analysis of financial markets based on asset pricing and corporate finance models. In particular, the emphasis will be on classical linear regression models, time series analysis, and limited dependent variable models applied to the following topics: predictability of asset returns; event study analysis; econometric tests of the CAPM and multifactor models; volatility modelling, etc.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Julio	Independent	M	06:00:00 PM–08:45:00 PM	PSY B51

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Page	Independent	T	06:00:00 PM–08:45:00 PM	EPC 207

Section A4, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Julio	Independent	W	06:00:00 PM–08:45:00 PM	STH 113

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Julio	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 688 Cloud Analytics for Business

4 credits. Fall and Spring

Prerequisites: AD571. - Explore web analytics, text mining, web mining, and practical application domains. The web analytics part of the course studies the metrics of websites, their content, user behavior, and reporting. The Google Analytics tool is used for the collection of website data and doing the analysis. The text mining module covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems. The web mining module presents how web crawlers process and index the content of websites, how search works, and how results are ranked. Application areas mining the social web and game metrics will be extensively investigated. R, SQL, and Power BI software are used in this course.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Padalkar	Independent	M	02:30:00 PM–05:15:00 PM	EPC 208

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Padalkar	Independent	ARR	12:00:00 AM–12:00:00 AM

MET AD 699 Data Mining for Business Analytics

4 credits. Fall and Spring

Prerequisites: AD571 Enterprises, organizations, and individuals are creating, collecting, and using a massive amount of structured and unstructured data with the goal of converting the information into knowledge, improving the quality and the efficiency of their decision-making process, and better positioning themselves in the highly competitive marketplace. Data mining is the process of finding, extracting, visualizing, and reporting useful information and insights from both small and large datasets with the help of sophisticated data analysis methods. It is part of business analytics, which refers to the process of leveraging different forms of analytical techniques to achieve desired business outcomes through requiring business relevancy, actionable insight, performance management, and value management. The students in this course will study the fundamental principles and techniques of data mining. They will learn how to apply advanced models and software applications for data mining. Finally, students will learn how to examine the overall business process of an organization or a project with the goal of understanding (i) the business context where hidden internal and external value is to be identified and captured, and (ii) exactly what the selected data mining method does. Python, R, SQL, and Power BI software are used in this course.

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Athaide	Independent	R	06:00:00 PM–08:45:00 PM	PSY B55

Section O2, FALL 2025 Oct 28th to Dec 15th
Instructor	Type	Days	Times	Location
Athaide	Independent	ARR	12:00:00 AM–12:00:00 AM

MET CS 688 Web Mining and Graph Analytics

4 credits. Fall and Spring

Prerequisites: MET CS 544, or MET CS 555 or equivalent knowledge, or instructor's consent. - The Web Mining and Graph Analytics course covers the areas of web mining, machine learning fundamentals, text mining, clustering, and graph analytics. This includes learning fundamentals of machine learning algorithms, how to evaluate algorithm performance, feature engineering, content extraction, sentiment analysis, distance metrics, fundamentals of clustering algorithms, how to evaluate clustering performance, and fundamentals of graph analysis algorithms, link analysis and community detection based on graphs. Laboratory Course.

Section A1, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Hajiyani	Independent	T	06:00:00 PM–08:45:00 PM	CAS B06A

Section A2, FALL 2025 Sep 2nd to Dec 10th
Instructor	Type	Days	Times	Location
Vasilkoski	Independent	R	06:00:00 PM–08:45:00 PM	SHA 206

Section O1, FALL 2025 Sep 2nd to Oct 20th
Instructor	Type	Days	Times	Location
Rawassizadeh	Independent	ARR	12:00:00 AM–12:00:00 AM

Master’s Thesis Option

Dates & Deadlines

View BU MET’s academic calendar for online programs, including important dates and deadlines.

Application Requirements

Learn about application requirements for BU MET graduate degree and certificate programs.

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How You Benefit from a
Boston University Education

A BU credential can help lay the foundation for career advancement and personal success.

Benefit from an average 24:1 student-to-instructor ratio.
Work closely with highly qualified faculty who draw from active research and substantial professional achievements in areas such as business innovation, business analytics, market research, finance, project management, enterprise risk management, ecommerce, international business, economic development, sustainability entrepreneurship, and many others.
Focus on practical, hands-on lessons that you can apply on the job. A research thesis option is available for those interested in a deeper pursuit of academic research.
Two levels of free, self-paced analytics laboratories offer access to advanced tools and provide opportunities to hone analytics skills using cases that are populated with realistic data.
Gain access to BU resources and Innovate@BU programs such as Innovation Pathway, Summer Accelerator, and New Venture Competition—among others—provide complementary pitch and professional skills development.

All graduate students are automatically considered for merit scholarships during the application process and nominated based on eligibility. Learn more.

Graduate with Entrepreneurial Expertise

Students who complete the Innovation & Entrepreneurship master’s degree concentration in Technology will be able to:

Apply business analytics, Python, and SQL to extract insights, evaluate market trends, and support data-driven decision-making in technology-driven ventures.
Develop financial and risk assessment models to analyze investment opportunities and optimize funding strategies for technology-based startups and enterprises.
Use emerging technologies such as blockchain, AI, and web analytics to enhance business operations, improve efficiency, and drive innovation.
Integrate advanced data mining and quantitative methods to identify patterns, forecast trends, and create competitive advantages in entrepreneurial and corporate technology initiatives.

Advance Your Career

BU MET’s Innovation & Entrepreneurship master’s with a concentration in Technology prepares you for roles that generally involve driving technology adoption and innovation, managing data and analytics projects, developing tech products or ventures, and leading digital transformation initiatives across industries including FinTech, software, healthcare, and more. Typical job titles might include technology innovation manager, business intelligence analyst, product manager (technology focus), data analyst, technology consultant, venture capital analyst (tech startups), digital transformation specialist, innovation project manager, enterprise risk analyst, blockchain analyst/developer, AI solutions architect, tech startup founder/entrepreneur, IT strategy consultant, analytics manager, and software product owner, among others.

Take Advantage of Career Resources at BU MET

You will find the support you need in reaching your career goals through MET’s Career Development office, which offers a variety of job-hunting resources, including one-on-one career counseling by appointment for online students. You can also take advantage of tools and resources available online through BU’s Center for Career Development.

Innovation & Entrepreneurship Faculty

Kathleen Park

Assistant Professor, Administrative Sciences

Coordinator, Innovation

Marcus Goncalves

Associate Professor of the Practice

Coordinator, Global Marketing Management

Associate Chair, Administrative Sciences

Esteban Lopez

Lecturer, Administrative Sciences

Megan M Trainor

Senior Lecturer, Administrative Sciences

View All Faculty

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Online Master of Science in Innovation & Entrepreneurship, Technology Concentration

At a Glance

Harness Emerging Technologies to Drive Business Innovation and Growth