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MS in Business Analytics from Clark University

MS in Business Analytics from Clark University

Earn an MS in Business Analytics Degree from Clark University

Scholarships Available till 5th Nov 2024

  • Program Overview
  • Curriculum
  • Career Support
  • Certificate
  • Success Stories
  • Faculty
  • Fees

Why choose this Master’s in Business Analytics Program

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    Hybrid program: 8 months online + 12 months on-campus in USA

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    Learn from top faculty & get practical insights from industry experts

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    Quick application with no GRE/GMAT/TOEFL required

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    Save up to INR 45 Lakhs compared to a full-time program

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    Up to 3 years post-study work/OPT Visa

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    Join an alumni network of 40,000 members

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    Choose to specialize in Financial Analytics or Marketing Analytics

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    9:1 Student-to-faculty Ratio

  • AACSB International Accredited

    AACSB International Accredited

  • National Universities

    National Universities

    with ~3,000 enrollments

  • Best Value Schools

    Best Value Schools

    U.S. News & World Report

Skills you will learn

  • Business Statistics
  • Machine Learning
  • Database Management
  • Data Analysis
  • Business Intelligence
  • Analytics Programming

Our alumni work at top companies

About MS in Business Analytics Program

The MS in Business Analytics program by Clark University, in collaboration with Great Lakes Executive Learning, is designed to provide essential business principles and advanced analytics knowledge. It uses a hybrid format, blending online and on-campus learning. Practical skills are developed through hands-on projects and real-world applications, with personalized mentorship provided to enhance the learning experience. This approach ensures you are well-prepared for data-driven roles and equipped to make strategic decisions in the evolving analytics field.

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Why enroll in a business analytics course?

Enrolling in Clark’s MS in Business Analytics program will be pivotal for you to thrive in today’s data-driven world. The program equips you with critical data mining, predictive analytics, and Machine Learning skills. These technical proficiencies and the ability to interpret and communicate data-driven insights make you invaluable across the finance, healthcare, and retail industries. Additionally, with an MSBA degree, you can command higher salaries than those without this specialized degree.

Who is this program for?

The MS in Business in USA is for:

  • Early-career professionals aspiring to build a career in Business Analytics in USA and gain expertise in data-driven decision-making.

  • Mid and senior-level professionals aiming to stay competitive in the rapidly evolving data landscape and enhance their analytical skills for leadership roles.

  • Professionals seeking to transition into a high-growth field like Business Analytics, equipped with industry-relevant knowledge and technical expertise.

What is the format of this Business Analytics Program?

The hybrid business analytics program will be delivered in the below-given format:

  • 8 months: Delivered in a fully online format by Great Lakes Executive Learning

  • 12 months: Complete your MS in Business Analytics on-campus in USA with Clark University

What are the key highlights of the MSBA?

The key highlights of Masters in Business Analytics in USA are: 

  • 20 Months Program

  • Up to 3 years post-study Work/OPT Visa

  • Learn from top faculty and leading industry practitioners

  • Quick application with no GRE/GMAT/TOEFL

  • Alum status from Clark University

  • Save up to INR 45 Lakhs compared to a full-time program

  • Practical insights from industry experts

  • Choose to specialize in either Financial Analytics or Marketing Analytics


What are the eligibility criteria for enrolling in this program?

  • Applicants need to have a minimum of 3.2 GPA (65% score) in their undergraduate or 3 years of work experience.

  • Applicants with a 3-year bachelor's degree need to be from an awarding university which must be NAAC A or A+ (in the year 2019/2020/2021) accredited.

  • No GRE/GMAT test scores are required.

  • English Proficiency Test Score required (IELTS or TOEFL or Duolingo or PTE).


Student life at Clark University
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Diversity in Worcester
A city in Massachusetts and regional hub of government, industry and transportation. Affordable with a diverse community.

Key benefits of studying in USA

Study abroad in a top American university and experience its unique culture

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    Global university excellence

    Learn from world-famous universities in research and teaching methods

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    Connect with renowned faculty

    Interact with faculty of world-class universities in leading innovation hubs

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    Get up to 3 year post-study STEM work visa

    Work in USA with up to 3 year post-study work visa

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    Interact with a global community

    Expand your global cultural network with a diverse groups of learners

Program Curriculum

Online (8 Months)

Python Programming for Data Science

This course provides participants the knowledge of the fundamental constructs of Python programming and enables them to read, manipulate, analyze, and solve business problems using data. Participants will be introduced to the fundamentals of Python programming and learn the different techniques to perform computations, manipulate data, visualize data, and conduct exploratory data analysis using the most widely used Python libraries and packages (including but not limited to numpy, pandas, matplotlib, and seaborn).

Business Statistics

This course focuses on applying statistical methods in a business context to help address key business questions and make evidence-based decisions. The course provides the participants the knowledge of probability and inferential statistics to analyze data distributions, make business estimates using confidence intervals, and apply a wide range of hypothesis tests across different scenarios to validate business hypotheses.

Machine Learning

This course provides participants with the necessary knowledge to build, assess, and apply machine learning (ML) models using historical data to solve business problems. Participants will learn how to process the data to make it ready for modeling, build models (including but not limited to linear regression, logistic regression, decision trees, k-means clustering, and ensemble models) to capture the relationships between input variables and known outcomes (continuous or categorical in nature), identify patterns and groups in unlabelled data, check the statistical validity of models, combine the decisions from multiple models to make better predictions, use tuning algorithms to optimize model performance, and gain business insights from the model and its outputs.

Business Intelligence, Data Visualization and Data Management using SQL

This course will enable participants to write complex, efficient queries to fetch and analyze data using SQL and effectively communicate insights via visual storytelling using Tableau. Participants will learn how to store, fetch, aggregate, and manipulate data using SQL queries, use advanced SQL techniques for analytical deep dives, create different visualizations to convey insights from data, and utilize advanced dashboarding features to create informative and visually appealing storyboards.

On-campus (12 Months)

Core Courses (Mandatory)

STAT 4450 - Managerial Statistics

This foundation course is designed to review or introduce the basic concepts of statistics and probability. Learners will learn how to collect data, calculate statistics to describe the data, and interpret the data to conclude.  In the course, the students will learn descriptive statistics, characteristics of discrete and continuous probability distributions, sampling distributions, confidence intervals, and hypothesis testing.  The course will also cover linear regression and correlation.  Students will perform tasks in MS Excel, and this course will serve as a primer for the Big Data Statistics courses.

  

BAN 4500 - Information Systems for Analytics

This course intends to provide students with a business orientation on analytics in organizations. It provides a comprehensive understanding of the organizational context, information systems infrastructure, and management applications that drive and support Business Analytics. The objectives of this course are to ensure that the students can identify ways to improve strategic positioning through deploying technologies and associated organizational changes; understand the technological infrastructure components such as hardware, software, cloud, database, and networking technologies; identify core business function areas and key performance metrics for analytics applications; and plan for and manage the acquisition and maintenance of the information resources.  In addition, students will also learn how to improve security, lower risks, and deal with issues such as information privacy and ethics. The course utilizes business case analysis and hands-on exercises to explore, analyze, and visualize business data, develop actionable solutions to business problems, and communicate key results to stakeholders.


BAN 4550 - Analytics Programming

This course provides a general introduction to computer programming for analytics. Python will be used as the primary language. Specific topics include the programming environment, programming language elements, basic data types, conditionals, functions, and reading and writing files. Upon completing this course, students are expected to have a good understanding of programming and will be able to design and develop programs for scientific computing and basic analytics. While this course doesn’t require a background in programming, students are asked to complete an online course in Python before the start of the class.


STAT 4600 - Intermediary Statistical Modeling for Analytics

Intermediary Statistical Modeling for Analytics emphasizes understanding descriptive, diagnostic, and predictive analytics to identify critical aspects of a business question, from data collection to formulating and testing hypotheses. As such, this course is a data science course emphasizing statistical methodologies. At the same time, the course emphasizes the practical aspects of Business Analytics  by embedding the methodologies in applications and underlining the general objective of improving the speed, reliability, and quality of decisions. Topics covered include sampling, inferential statistics, and linear regression. The course uses real-life datasets as illustrations and R to build answers to business questions.


BAN 5501 - Database Management and SQL for Analytics

This course serves as an introduction and overview of the Database Management Body of Knowledge (DMBOK) from a managerial perspective. The learning objectives will be to acquire a comprehensive understanding of the basic concepts of database design and usage and develop practical skills for utilizing databases to their fullest extent. Correct database design will be emphasized both as a theoretical foundation and a practical necessity. 


 The following topics are the focus of the course:

•    High-level, general database concepts and design 

•    Design, create, and manipulate an individual, relational database, including the utilization of SQL as a fundamental tool

•    Interpret and apply client database needs

•    Discuss and apply best practices of User Interface Design to database applications

•    Identify and discuss new developments and trends in databases, including data warehouses, data lakes and hubs, and X analytics.


STAT 4650 - Machine Learning

Machine Learning and Intermediary Statistical Modeling for Analytics provide an overview of techniques drawn from machine learning, data mining, and statistics. These two courses aim to prepare students with an intellectual framework for problem-solving.


This course emphasizes using mathematical modeling and scenario optimization to reach optimal business decisions. As such, this course is a data science course with an emphasis on statistical methodologies. At the same time, the course emphasizes the practical aspects of Business Analytics  by embedding the methods in applications and by underlining the general objective of improving the speed, reliability, and quality of decisions. Topics include logistic regression, cross-validation, model selection, nonlinear methods, decision trees, dimension reduction, and clustering. If time allows, support vector machines and time series forecasting are also discussed. The course uses real-life data sets as illustrations, and R and Python to build answers to business questions.


BAN 5573 - Visual Analytics and Business Intelligence

By leveraging enterprise information assets, business intelligence tools and technologies can help businesses become more efficient and effective in their operations. Business Intelligence utilizes technology, expertise, knowledge, statistics, and creative thinking to identify problems and provide solutions to them. The focus of this class is to learn about enterprise approaches to business intelligence through case studies, decision support systems (DSS), development methodologies, and enabling technologies. This course will provide students with the experience to conduct an analytic project from gathering the data to interpretation in the business intelligence technologies such as Tableau, KNIME, frontline solver, LINGO, and others.

The analytics content is divided into three parts: descriptive, predictive, and prescriptive analytics. The first four to five weeks will be spent learning descriptive analytics and will be performed in Tableau. The next four to five weeks will be spent learning predictive analytics methods using KNIME software. The remaining weeks will be utilized to learn linear programming and other prescriptive analytics methods using Excel Frontline Software, and LINGO. This course also involves a project in the form of a creative component. The details are given later in the syllabus.

By the end of the course students will develop an understanding of the role of computer-based information systems in direct support of managerial decision making."


BAN 5650 Applied Business Analytics  

The goal of this course is to cultivate students’ capability to apply data analytics and decision support modeling to industry decision problems characterized by complex market and regulatory environments and competing demands for resources. Students will learn a framework for quantitative decision making and effective resource allocation under uncertainty that is applied today in many Business Analytics  and decision making contexts. The course will focus on (1) identification and collection of relevant data for analysis; (2) identification and application of the appropriate models and techniques (e.g., capital budgeting, cost benefit analysis, optimization, and Monte-Carlo simulation); and (3) structuring the decision problem in terms of strategic alignment, feasibility, cost effectiveness, and risk. By the end of the semester, students will understand how to assess the business context and apply Business Analytics  skills to the managerial decision problem; structure and implement a complex decision analysis; select appropriate data and analytical methods and build spreadsheet models; apply project management principles and tools to the completion of complex analysis; and present and defend an analysis and recommended investment program


BAN 5600 - Advanced Big Data Computing and Programming

The astounding growth of data in all aspects of life in the form of emails, weblogs, tweets, sensors, videos, and text has necessitated the use of Big Data and advanced analytics techniques to support large-scale data analytics. The goal of this course is to enable students to design and build Big Data applications through highly scalable systems capable of collecting, processing, storing, and analyzing large volumes of structured and unstructured data.

By extending the Cross-Industry Standard Process for Data Mining (CRISP-DM) to build Big Data applications using distributed and parallel computing architecture, this course brings together key Big Data tools on Hadoop Ecosystem (such as Pig, Hive, Flume, Sqoop, and Spark). Students will learn how to efficiently manage and analyze data with three main characteristics: high volume, high velocity, and high variety.

Topics include the Hadoop Ecosystem platforms such as Hortonworks Sandbox, Amazon AWS, and Databricks; and advanced analytics techniques such as Visualization, Natural Language Processing, and streaming analytics.

Concentration(Choose 1)

Marketing Analytics Concentration:

MKT 5401 Marketing Research and Analysis (second semester)

This course examines the basic concepts and techniques used in marketing research as a problem-solving aid in decision making in marketing. Problem definition, research design, types of information and measurement scales, evaluation and utilization of secondary (structured and unstructured) data with emphasis on electronic access are discussed. Students are trained in the basic methods of primary data collection, including survey, depth interviews, focus groups, and projective methods. Practical and intensive applications on sample size selection, questionnaire design, data analyses, and interpretation are emphasized. Discussions of advanced analytical techniques (multiple linear regression analysis, logistic regression, t-test, chi-square, predictive analysis, etc.) for analyzing and interpreting data using SPSS statistical package are also covered.


MKT 5495 Digital Marketing Analytics (third semester)

This course will cover the what, why, and how of major digital marketing approaches, including search engine optimization, search and display ads, mobile and web analytics, and social listening/monitoring. The course will also cover the metrics, key performance indicators, and basic tools (e.g., Google Analytics 4 and online experiments) used to evaluate the effectiveness of digital marketing campaigns. This course provides a quantitative and qualitative approach to understanding and harnessing tools in digital marketing analytics to meet business objectives. The course is designed to get students to think like a digital marketing professional, and to give students experience with industry-relevant hands-on assignments, exercises, and certifications.


Financial Analytics Concentration:

FIN 5401 Investments

This course provides an introduction to the financial market, investment theory, and security valuation. The topics covered include equity and bond pricing, portfolio analysis, capital asset pricing model, option pricing, and ethics in investment management. Emerging topics such as ESG (Environmental, Social and Governance) investing, FinTech, and Cryptocurrency, will be briefly discussed. The lectures and examinations will focus both on conceptual and quantitative foundations.


Elective (Choose 1):

  • FIN 5200 Corporate Finance - This course serves as an introduction to the principles of corporate finance and its applications. The objective is to provide the framework, concepts, and tools to make sound financial decisions based on fundamental principles of modern financial theory. It will examine topics such as financial analysis, asset valuation, capital budgeting, capital structure, dividend policy, and the cost of capital. It will explain the procedures, practices, and policies by which financial managers contribute to the successful performance of an organization.

  • FIN 5216 Options, Futures, and Other Derivatives - Modern-day finance is rife with computationally intensive problems and solutions from pricing derivative instruments to complex portfolio building using optimization techniques. This course supplies students with the intuitions for the underlying mathematical concepts behind common financial applications. Furthermore, students learn the skills to develop their own solutions to variants of these applications with emphasis put on the generalizability of the results reviewed. Starting with binomial models as a stepping-stone, this course discusses the main tools applied to derivative valuation and their extension to continuous time pricing. It also considers common numerical methods utilized in financial engineering such as Monte Carlo simulation. The course ends with a review of common optimization tools and their application to portfolio building under constraints.

  • BAN 5700 Blockchain and Cryptocurrency - This course presents some fundamental concepts and hands-on experiences for learning blockchain technology. The hands-on experiences focus on design and development of blockchain through programming, then business applications of blockchain. The business applications include development of blockchain, coins, and NFTs. Examples of topics include, but are not limited to, hash functions, cryptocurrency, transactions, marketing, trading, cryptocurrency creation, and NFTs. The major blockchain and cryptocurrency programming will be through Python. 


Notes

  • 3 courses shall be waived off for Great Learning learners
  • Completion of an approved non-credit internship is required.
  • The above curriculum is tentative and subject to change.
  • Applicants should score a minimum of 3.0/4 GPA in each course and in aggregate in the online program in order to progress to the on-campus program.


Masters of Science in Business Analytics Degree from Clark University

Upon successful completion of the course, the university will reward you with an MS in Business Analytics degree.

Clark MSCS Certificate

* Image for illustration only. Certificate subject to change.

  • #38 Best Value Schools

    #38 Best Value Schools

  • Top 5 National Universities

    Top 5 National Universities

    with ~3,000 enrollments

  • AACSB International Accredited

    AACSB International Accredited

Meet the Faculty

Learn core concepts from world-class Clark University faculty

  • David Jordan - Faculty Director

    David Jordan

    Dean, School of Business

  • Jing Zhang  - Faculty Director

    Jing Zhang

    Professor, School of Business

  • Alan Eisner  - Faculty Director

    Alan Eisner

    Professor, School of Business

  • John Dobson  - Faculty Director

    John Dobson

    Professor of Practice, School of Business

  • Thomas Murphy  - Faculty Director

    Thomas Murphy

    Professor of Practice, School of Business

  • Will O' Brien  - Faculty Director

    Will O' Brien

    Professor of Practice, School of Business

  • Sitikantha Parida  - Faculty Director

    Sitikantha Parida

    Associate Professor, School of Business

  • Atefeh Yazdanparast Ardestani  - Faculty Director

    Atefeh Yazdanparast Ardestani

    Associate Professor, School of Business

Note: This is an indicative list and is subject to change based on the availability of faculty and mentors

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    Sessions with industry experts

    Great Learning’s program team conducts additional doubt-clearing sessions with industry experts to provide learners with practical and in-depth knowledge.

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    Our counselors schedule video calls with learners and assist them in filling out the application accurately.

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    Statement of purpose review

    We provide students with sample SOP formats to guide them in crafting a compelling SOP.

Program Fees

The program fee is divided into 2 parts:

8 months online ₹ 4,98,000 (Incl. GST)

+

12 months on-campus (in USA)*USD 21,400

*The tuition fee is subject to change based on the university's regulations

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Benefits of learning with us

  • Up to 3 years STEM OPT VISA in USA
  • Save upto INR 45 Lakhs
  • Globally recognised hybrid mode of learning (first 8 months online, 2nd year on-campus in USA)
  • Quick application with no GRE/GMAT requirement
  • Get alumni status from Clark University

Application process

Our admissions close once the requisite number of participants enroll for the upcoming batch . Apply early to secure your seats.

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    1. Apply Online

    Fill out a fast and easy online application form. No additional tests or prerequisites are needed.

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    2. Pre-Screening

    Our team will make contact with you by phone to confirm your eligibility for the program.

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    3. Application Assessment

    If selected, you will receive an offer for the upcoming cohort. Secure your seat by paying the fee.

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    4. Join the program

    If selected, you will receive an acceptance letter with instructions on how to pay and join the program.

Batch Start Date

Still have queries? Let’s Connect

Get in touch with our Program Advisors & get your queries clarified.

Speak with our expert +91 79-7117-0994 or email to clark.msba@mygreatlearning.com

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