Master of Science in Business Analytics and Artificial Intelligence

1 Year On Campus Bachelors Program

Johns Hopkins University

Program Overview

The Master of Science in Business Analytics and Artificial Intelligence at Johns Hopkins University's Carey Business School prepares students to transform complex business data into actionable insights using advanced analytics, artificial intelligence, and machine learning. Designed for recent graduates and early-career professionals, the program combines technical analytical skills with business leadership, enabling students to solve organizational challenges and support strategic decision-making across industries.

Curriculum Structure:

The 36-credit full-time curriculum specified in the supplied academic catalogue is completed over three semesters (Fall, Spring, and Summer). It combines business foundations, functional analytics courses, STEM-focused subjects, and quantitative electives.

Year 1 – Business Foundations and Analytical Skills

Students begin by developing essential business knowledge and quantitative capabilities through courses such as Business Communication, Business Leadership and Human Values, and Statistical Analysis. They also study Business Analytics, Data Analytics, Data Visualization, and Operations Management, learning to interpret business data, identify patterns, and communicate analytical findings to support organizational decisions.

Advanced Study – Artificial Intelligence and Business Applications

Students advance their technical expertise through AI-Driven Sequential Decision Making, Practical Machine Learning, Python for Data Analysis, and the Analytics Consulting Project. They can further specialize through electives such as Generative AI, Data Science and Business Intelligence, Customer Analytics, Advanced Database Management, and Forecasting Models for Business Intelligence, developing the ability to apply advanced analytical techniques to practical business challenges.

Focus Areas: Business analytics, artificial intelligence, machine learning, Python programming, statistical analysis, data visualization, predictive analytics, generative AI, business intelligence, decision modelling, customer analytics, database management, and operations analytics.

Learning Outcomes: Develop proficiency in business data analysis, apply machine learning and AI methodologies, use Python for analytical applications, create effective data visualizations, evaluate business performance, interpret complex datasets, apply quantitative decision-making techniques, and communicate data-driven recommendations to business leaders.

Professional Alignment (Accreditation): The program is STEM-designated, allowing eligible international graduates in F-1 status to potentially qualify for the 24-month STEM OPT extension following their initial 12-month OPT period, subject to immigration requirements. Johns Hopkins Carey Business School is accredited by the Association to Advance Collegiate Schools of Business (AACSB), an internationally recognized accreditation body for business education.

Reputation (Employability Rankings): Johns Hopkins University is internationally recognized for its research and academic excellence, while Carey Business School strengthens the program through its industry-focused business education and specialist faculty. The program offers access to professional networks and career development opportunities in Washington, D.C. A specific QS or Guardian ranking and program-specific graduate employment statistics are not stated in the official sources reviewed.

Experiential Learning (Research, Projects, Internships etc.)

The MS in Business Analytics and Artificial Intelligence emphasizes practical learning through industry consulting projects, case competitions, analytical assignments, and professional conferences. Students apply AI and machine learning methodologies to real business challenges, gaining experience in problem definition, data preparation, analytical modelling, and communicating actionable recommendations. The program also encourages students to present their work at professional analytics conferences and pursue industry-recognized certifications.

Students gain practical experience through the following opportunities:

Python Programming: BU.510.615 – Python for Data Analysis develops programming and data analysis skills for business applications.
Machine Learning: BU.520.775 – Practical Machine Learning introduces applied machine learning techniques for solving business problems.
Generative AI: Students can explore generative AI technologies and their business applications through the Generative AI elective.
Data Visualization: BU.520.650 – Data Visualization develops the ability to present complex information through clear visual representations.
Analytics Consulting Project: Students work on a real-world business problem presented by an industry client, gaining experience in project scoping, methodology selection, data preparation, analysis, and developing actionable insights.
AI-Powered Decision Analytics: Students explore AI-driven sequential decision-making and practical machine learning applications to improve business decisions.
Case Competitions: Students participate in business analytics case competitions to solve practical problems and demonstrate their analytical capabilities.
INFORMS Analytics Conference: Students are encouraged to present their work at the conference, interact with business leaders, and build professional connections.
Professional Certification: Students can pursue the Associate Certified Analytics Professional (aCAP) certification to strengthen their professional credentials.
Industry Exposure: Carey provides opportunities to interact with industry professionals through employer events, networking sessions, and career-related activities.

Progression & Future Opportunities

Graduates of the MS in Business Analytics and Artificial Intelligence can pursue opportunities across technology, financial services, consulting, healthcare, retail, and other data-driven industries. The program develops the technical and managerial expertise needed to transform business information into strategic insights, improve organizational performance, and support AI-driven innovation.

Potential career paths include Business Analytics Consultant, Data Analyst, Business Intelligence Analyst, AI Business Analyst, Machine Learning Analyst, and Predictive Analytics Specialist.

Career Development and Employment Opportunities:

Career & Life Design Team: Carey provides dedicated career coaching, peer advising, and professional development support throughout the program and beyond graduation.
Resume and Interview Preparation: Peer Career Advisors assist students with resume writing, cover letters, LinkedIn profiles, networking, and interview preparation.
Career Training Bootcamps: Students participate in career workshops covering professional branding, job-search strategies, networking, and interview techniques.
Carey Career Exchange (CCx): Provides access to internship and job postings, employer information, and career development resources.
Industry Networking: Students can attend weekly industry insider sessions, employer information sessions, and the annual MS Alumni Connect event.
Professional Events: Johns Hopkins Future Fest, career fairs, industry treks, and employer site visits provide opportunities to connect with organizations and professionals.
Employer Connections: Carey graduates have secured opportunities across organizations including Deloitte, Microsoft, AstraZeneca, Morgan Stanley, Hershey, Johns Hopkins Hospital, and the World Bank. These are examples of employers of Carey graduates, not guaranteed recruiters for this particular program.
Employment Statistics and Salaries: Carey publishes employment statistics for its graduate programs, with data collected up to six months after graduation. However, a separate placement rate and average salary specifically for the MS in Business Analytics and Artificial Intelligence are not stated in the official information reviewed.
Graduation Outcomes: Graduates can apply their expertise to business intelligence, AI-supported decision-making, predictive analytics, financial analysis, data science, and business consulting.

Further Academic Progression: After completing the master's degree, graduates interested in advanced research, teaching, or academic leadership can consider doctoral studies such as a PhD in Management, Business Administration, Information Systems, or related quantitative disciplines. They may also pursue specialized graduate certificates and professional certifications in artificial intelligence, data science, machine learning, business intelligence, and advanced analytics to strengthen their technical and managerial expertise.