Masters in USA from Clark University

Masters of Science in Data Analytics

Upto 3 years STEM OPT VISA

97% Placement Rate

Eligible for Internships at top companies

Application Closes 15^th May 2024

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Scholarships Available till 15^th May 2024

Why choose this Master’s in Data Analytics Program?

Study On-campus in USA
Learn with students from 80+ Countries
Alumni network of 40,000 members
9:1 Student-to-faculty Ratio
Save upto USD 25,301 compared
to full-time Master’s
Dedicated Program Manager

#38 Best Value Schools
Top 5 National Universities

with ~3,000 enrollments
AACSB International Accredited
Best Value College

Best Northeastern
Ranked a QS Top University

World University Rankings

Skills you will learn

Data Science
Data Analytics
Machine Learning
advanced statistical analysis
data mining
data warehousing

About MS in Data Analytics in USA

Clark University's MS Data Analytics is a comprehensive program. It offers a holistic approach to data science and covers essential concepts. This program is in collaboration with Great Learning and allows you to study in the US without GRE/GMAT. The program follows a hybrid format that integrates online and in-person learning. You will engage in hands-on projects and receive mentorship sessions. This will be a rewarding learning journey as you earn a degree from Clark University and up to a 3 Years Post-Study Work/OPT visa in the USA.

What is Data Analytics?

Data Analytics refers to the process of converting raw data into meaningful information. This information helps in making efficient business decisions. Data analytics techniques reveal trends, patterns, and metrics that otherwise seem impossible. For example, an e-commerce company uses data analytics to do targeted advertising.

Data analytics is, thus, a valuable skill in today's world. Most industries worldwide use it to increase their efficiency and output.

What are the applications of Data Analytics?

Nowadays, almost every industry uses data analytics to enhance business efficiency. Whether retail, manufacturing, healthcare, or business, data analytics have impactful applications. Even the government and legal entities apply business analytics to revolutionize their decision-making.

What is a Data Analytics Masters Program?

This is an MS in Data Analytics in the USA without GRE/GMAT. This course provides comprehensive learning about the field. It helps you learn the foundations of data analytics and in-demand skills and boosts your career prospects.

What modules will I study after joining Clark University's Data Analytics Program?

The program follows a Hybrid format with 8 months of online and 12 months of on-campus learning. You will study these modules:

Online Modules

Business Statistics
Python Programming for Data Science
Business Intelligence, Data Visualization, and Data Management using SQL
Machine Learning

On-Campus (Includes mandatory and elective courses)

Core Courses (Mandatory)
Mathematical Statistics
Linear Regression and Time Series
Python Programming*
Data Management for Information Technology
Fundamentals of Data Engineering
Data Mining With Splunk
Applied Machine Learning*
Data Visualization and Storytelling

Elective Courses (Choose any 2)

Research and Marketing Analytics
IoT: Securing Communication Technologies through Data Analysis
Applied Deep Learning
Health Data and Record Systems
Special Topics: Data Analytics (Fall 2023 - Deep Learning, Spring 2024 - Applied Natural Language Processing)
Health Informatics
Independent Study
Capstone Practicum

Note- *Please note that these courses are waived off The curriculum is indicative

Program Curriculum

Clark University and Great Lakes Executive Learning offer a comprehensive curriculum. The course begins with online modules. You will then study core and elective courses in the US. This curriculum will give you deep insights into the latest analytics techniques. Applicants should score a minimum of 3.0 GPA in each course and in aggregate in the online program in order to progress to the on-campus program. Learners also need to complete an approved non-credit Internship to graduate. The below curriculum is tentative and subject to change.

Unit 1

ONLINE- 8 months

Business Statistics
Learn to apply statistical methods in a business context to address business problems. The course includes probability and inferential statistics. It will help you analyze data distributions and apply hypothesis tests in different scenarios. This will help you make evidence-based decisions in business.
Python Programming for Data Science
Become familiar with the fundamentals of Python programming, its libraries, and packages. Python is a widely used programming language for data science. In this course, you will be able to use data to read, manipulate, analyze, and solve business problems. Learn different techniques to make computations, manipulate, and visualize data.
Business Intelligence, Data Visualization and Data Management using SQL
Acquire skills to write complex, efficient queries that fetch data using SQL. Learn to communicate the insights by visual storytelling using Tableau. By the end of this course, you will be able to create visually appealing storyboards. You will use these storyboards to convey insights from data.
Machine Learning
Grasp the basics of ML and apply Machine Learning models to solve business problems. In this course, you will learn to process data for modeling and use it to identify patterns. You will also learn to use tuning algorithms to gain business insights

Unit 2

ON-CAMPUS - 12 months

Core Courses (Mandatory)

Mathematical Statistics
In this module, get an introduction to fundamental statistical analysis. You will get access to on-campus lectures and practical problem-solving sessions.
Linear Regression and Time Series
Build an overview of linear regression and time series analysis. This course will help you understand data analysis and its interpretation.
Learn the relationships between dependent and independent variables. You will also study time series analysis to see changes in data over time. It helps predict future trends.
Python Programming*
This is an elective course that helps you enhance your knowledge of Python. Python is one of the most prevalent languages and is beneficial for IT professionals. In this course, you will learn about Python principles and their practical applications.
This course benefits those seeking data management and IT/cyber data analysis careers. It includes case studies. These case studies focus on using Python learning to extract and analyze data.
Data Management for Information Technology
In this course, you will learn about the principles of data management, visualization, data mining, and AIML. You can apply these principles to enterprise intelligence. This will end up improving business performance and bring competitive advantage.
Fundamentals of Data Engineering
This module provides an in-depth knowledge of data warehouse principles and concepts. Hands-on exercises will teach you to build prototypes, structures, and tables using the ETL process. ETL stands for Extract, Transform, and Load.
In this course, you will learn to use SQL. You will also learn use of Business Intelligence (BI) tools to find patterns in data. Get a brief introduction to cloud data platforms and the modern data management ecosystem.
Data Mining With Splunk
Become familiar with the key concepts of business intelligence and Splunk Enterprise architecture. Work on hands-on sessions to learn it better. The course includes mining machine data, identifying data patterns, and creating Splunk reports.
Splunk Enterprise is a platform that can harness and leverage valuable machine data. It helps enterprises with valuable business, operational, and security intelligence.
Applied Machine Learning*
This course investigates the fundamental technical aspects and practices of Machine Learning. You will receive lectures, lab sessions, written assignments, and programming projects. These will help you apply ML to practical problems in Data Science using Python. You will also receive an introduction to some fundamental theories of ML.
Data Visualization and Storytelling
Learn how organizations make frequent and quick business decisions. In this course, you will understand the critical role of business intelligence in processing large amounts of data. You will also gain hands-on experience with Tableau to visualize data and derive meaningful insights.

*These courses are waived off.

Elective Courses (Choose any 2)

Research and Marketing Analytics
Explore marketing research, a tool that helps make sound marketing decisions for the business. Learn to make these decisions after gathering and analyzing the data. This course will cover topics like segmentation, targeting, positioning, pricing decisions, and more.
IoT: Securing Communication Technologies through Data Analysis
In this module, learn about design considerations, communication and networking technologies. You will also become familiar with the data analytics platforms. Know about IoT and its role in industries.
Understand the security issues that come with the rapid growth of IoT technology. Equip knowledge and skills to secure IoT systems by learning to use data analytics to improve their security.
Applied Deep Learning
Get a comprehensive education experience on deep learning applications in domains like image recognition, NLP, and sequential data analysis. Learn to leverage deep learning techniques in data analytics through hands-on applications. By completing this course, you will become proficient in practical coding skills. You will be able to use strategies for data-driven decision-making and complex problem-solving.
Health Data and Record Systems
Get an overview of the healthcare data landscape. Get aware of the history of the digital healthcare industry, and IT infrastructure. Learn about the opportunities in the health sector. Understand the usage of data sources with big data methods that impact healthcare positively.
Special Topics: Data Analytics
Special topics are the current topics in data analytics. These topics can vary from semester to semester. You might also get the same course for credit if they are different.

Fall 2023 - Deep Learning- This course covers modern artificial intelligence algorithms based on deep neural networks. Starting with the basics of statistics and mathematics, it follows with in-depth knowledge. You will study different types of neural network architectures and their training algorithms. The course introduces the basic concepts of NLP and its usage in deep neural architectures. You will have access to several recent research papers and a comprehensive research project in the lectures.

Spring 2024 - Applied Natural Language Processing- This course will introduce you to Natural language processing (NLP). NLP is a rapidly advancing domain. Its applications are notable across various domains, such as academia, government, and industries.You will understand the generative and non-generative models in NLP, their strengths, weaknesses, and use cases. Also, learn how these models function, their mechanisms, and their practical implications. The course highlights NLP's core issues and resolutions. It provides an understanding of computers' methodologies for interpreting and producing human language. This will be an interactive lecture series, and active student involvement is important.

Note: You should do weekly prescribed readings to help you with lectures. All course content will be accessible via the online learning management system (LMS).
Health Informatics
Learn to approach practical health informatics applications within the healthcare industry. This might include physicians, hospitals, insurers, government agencies, research institutions, pharma, and more. In this course, you will understand how to conduct research and identify trends in health records. You will also learn to evaluate healthcare operations and measure healthcare financial performance.
Independent Study
To pursue independent study, you must contact your advisor before registration begins. The advisor will work with you to discuss and develop a substantive proposal. The proposal will include a short synopsis of the proposed study, assignments, a bibliography, and a description of the deliverables.
The advisor approves the final version of the completed Independent Study form. It is then attached to a proposal. You must also add a detailed syllabus to the proposal. Forward the independent study form to the Assistant Dean for review and approval.
The Registrar's Office will email you the CRN (course registration number). You are responsible for registering for online independent study. You can only submit these proposals for independent study during the first week of registration.
Capstone Practicum
This is the practical section of the course. It integrates the coursework of the MSDA program into a practical application. Under the supervision of a faculty instructor, you will address an actual challenge. This actual challenge can be the real challenge that an organization faces.
You need to study the issues, review the industry and trends, and research the problem. You will also make recommendations to the organization's key members. In the end, you will have to make a formal written presentation. The faculty and organization professionals will review the final version of the presentation.

Degree from Clark University

Masters of Science in Data Analytics

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

* Image for illustration only. Certificate subject to change.

#38 Best Value Schools
Top 5 National Universities

with ~3,000 enrollments
AACSB International Accredited

Industry relevant syllabus

Learn top in-demand tools

Master these in-demand skills used by professionals worldwide to land your dream job.

NumPy
Scikit-learn
Pandas
TensorFlow
Matplotlib
Keras
Seaborn
Tableau
Splunk

Learner Testimonials*

*Testimonials from learners of Clark University

Apoorva Arbooj

One reason I chose Clark University is that all the professors are also practitioners. They combine textbook learning and years of research with first-hand experience working in the industry. They helped me bridge the gap between academics and industry.
Ali Murtuza

My prior industry expertise was strong, but I realized the importance of refining my technical understanding. The program at Clark offered precisely the foundational knowledge I needed to excel in my field.
Praveen Zirali

My Capstone project gave me hands-on experience with Data Analytics tools used in the real world.

Meet the Faculty

Meet the experienced and world-class faculty who will teach you the core concepts of Data Analytics

Richard Aroian

Richard Aroian is a Part-time Instructor and Assistant Dean at SPS. Additionally, he holds the role of Executive Director of Corporate Outreach, where he focuses on STEM programs. With a passion for connecting academia and industry, he spearheads initiatives that bridge the gap between education and real-world applications, ensuring impactful and relevant learning experiences.

Read more
Laura Myers

Laura Myers is a dedicated part-time instructor at SPS, known for fostering dynamic learning environments. With a passion for innovative teaching methods, she consistently engages students to enhance their learning experience and practical skillset.

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Dean Cascione

Dean Cascione serves as a part-time instructor at the School of Management, where he brings a wealth of practical insights to the classroom. With a focus on enriching students' understanding, Dean ensures that theoretical concepts are grounded in real-world application, preparing students for success in their careers.

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Siu Ming Luie

Siu Ming Luie holds the roles of part-time instructor and Associate Dean at SPS, focusing on faculty affairs. Committed to academic excellence, Siu Ming Luie strives to enhance faculty development while imparting valuable knowledge to students, fostering a supportive and engaging academic community.

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Julie Frechette

Julie Frechette is a part-time instructor and Program Lead for the MS Communication program at SPS. With a dedication to shaping the communication professionals of tomorrow, Julie combines academic rigor with practical relevance, preparing students for diverse career paths in the field of communication.

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David Jordan

David Jordan serves as both a part-time instructor and Interim Dean at the School of Management. Through his dual roles, David blends teaching with leadership to provide students with a comprehensive education. By bridging theory and practice, he ensures that students are well-prepared for the challenges of the business world.

Read more
David Hofstetter

David Hofstetter is a part-time instructor at SPS, focusing on equipping students with practical skills and industry relevance. With a commitment to empowering students for success in the competitive job market, David fosters a supportive learning environment where students can thrive and excel.

Read more
Kerry Morris

Kerry Morris is a dedicated part-time instructor at SPS, known for enriching students' learning with real-world insights. With a focus on fostering a supportive environment, Kerry empowers students to excel academically and professionally, preparing them for future success in their chosen fields.

Read more

Note: The above faculty list is indicative

Get The Clark University Advantage

Get access to a wealth of career resources and programs using your Clark University email to enhance your professional pursuits.

ClarkCONNECT - Connecting 6,000+ students, alumni & faculty
Forage - Bridge between education & career success offering job simulations
Handshake - Career management platform to connect with employers
Big Interview - Online platform to aid interview preparation.
In-person and virtual coaching
Personalized guidance
Resume and interview preparations
Over 3,000 students representing 80+ Countries

Get the Great Learning Advantage

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.
Application assistance

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

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

Program Fees

The program fee constitutes of two parts:

8 month Online FeeUSD 5000

12 months On-campus fee (in US)USD 17,052

Apply Now

Benefits of learning with us

Upto 3 years STEM OPT VISA in the US
Save upto USD 25,301
Globally recognised hybrid mode of learning (first 8-months online, second year on-campus in the US)
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.

1. Apply Online

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

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

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

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

Limited seats available

Apply today and become a Data Analytics Expert

Batch Start Date

Hybrid · September 2024

Admission closing soon

Apply Now

Frequently asked questions

Frequently Asked Questions

What is this MS in data analytics program all about?

Clark University offers this Master of Science in Data Analytics. The program is in collaboration with Great Learning. The program is in a hybrid format and focuses on the advanced application of Data Analytics.

What is the total duration of the program? What format is it?

The total duration of the program is 20 months. The program is in a hybrid format.

Who would be teaching me this program?

Top faculty and leading industry practitioners will be teaching you this program. This faculty has expertise in different fields. They will help you gain knowledge and practical insights.

What prerequisites do I have to follow for admission to the program?

These are the prerequisites you need to get admission into this program:

Clear an English Proficiency Test (EPT) (IELTS or TOEFL or Duolingo or PTE Tests).
Score a minimum of 3.0 GPA in each course and in aggregate in the online part of the program.
Applicants with a 4-year bachelor's degree need to have a minimum of 66% marks. The maximum backlogs (ATKTs) accepted will be 6.
Applicants with a 3-year bachelor's degree need to have a minimum of 60% marks. The maximum backlogs (ATKTs) accepted will be 4.

Note: The awarding University must be NAAC A or A+ (2019/2020/2021). The applicant should be from a Science background i.e. BCA/B.Sc/BIT. He or she should have substantial work experience in relevant areas.

What fees will I have to pay for the program? Can I get any scholarships or financial aid options?

The total program fee is USD 22,052. Yes, Scholarships and financial aid are available. You should reach out to program advisors for details.

What admission process do I have to follow? Can I apply online for this program?

Yes, you can apply online for the program. Here is the process of the admission:

1: Apply online: Fill out a fast and easy online application form.

2: Pre-screening: Our team will call you to confirm whether you are eligible for the program.

3: Application Assessment: The admissions team will assess your application. After that, they will provide a timely response.

4: Join the program: You will receive an acceptance letter if the team selects you for the program. You will also get instructions on how to pay and join the program

What kind of job opportunities can I expect after completing this program?

After completing this program, you can expect job opportunities such as:

Data Analyst,
Data Scientist,
Business Analyst,
Financial Analyst, and more.

Salaries vary based on location, company, experience, and specific job roles.

What is the visa application process for this program?

Great Learning assists students in securing their Financial Guarantee documents. They also help students apply for their I-20 from the university. Additionally, we support scheduling Visa appointments and preparing for Visa interviews.*

*Please note: Once Clark University accepts your candidature, advisors will coordinate and facilitate your fee financing, I-20, and Visa application process in the 1st year.

For more details on the visa process, please contact the admissions team.

Is this MS in DA course a STEM course?

Yes. Data Analytics is a STEM course in the USA. The graduates qualify for up to 3 years of OPT (Optional Practical Training) visa in the USA. This is a benefit generally present with STEM courses.

Contact the program advisor for more information and clarity.

Do I need coding skills for Data Analytics?

It's good to have coding skills if you are a data analyst, but it depends on your role, too. Some entry-level jobs and positions do not require coding. But most roles do.

Having coding knowledge increases your job opportunities. You become more competitive in the field.

What if my question is not here?

If you don't find your answer to these questions, please speak to a Program Advisor at 08069474542. You can also email us at clark.msda@mygreatlearning.com