What is the course all about?
MS Data Analytics is a theory and application-based programme that provides comprehensive knowledge of digital data management, data analysis, data acquisitions, and statistical tools. A well-designed programme imparts the analytical skills required for data analysis and data mining. It teaches the approaches of applying statistical techniques and computation methods for achieving proficiency in the process of data analytics.
  • This is a 33 credit hours program.

  • Intake
    Start Date
    Application Deadline
    I-20 Request Deadline
    Begin Course Registration
     Fall 1, 2019
     August 19, 2019
     June 7, 2019
     June 21, 2019
     April 8, 2019
     Fall 2, 2019
     October 21, 2019
     August 9, 2019
     August 23, 2019
     April 8, 2019
     Spring 1, 2020
     January 6, 2020
     October 25, 2019
     November 8, 2019
     October 28, 2019
     Spring 2, 2020 
     March 16, 2020
     January 8, 2020
     January 17, 2019
     October 28, 2019
     Summer 2020
     May 25, 2020
     March 16, 2020
     March 30, 2020
     March 5, 2020
  • 1. Undergraduate degree
    2. Baccalaureate degree from a U.S. accredited institution
    3. Online Application with USD 50 application fee
    4. Official transcripts
    5. Certificate of Finance
    6. Passport
    7. Undergraduate cumulative grade point average of 2.5 or above
     
    English Proficiency Test: The acceptable English Proficiency test scores are mentioned below
    English Test
    Minimum Score Required
    IELTS
    Minimum 6.5
    TOEFL
    iBT 80 or PBT 575
    Pearson Treat of English Academic
    Minimum 53
    Cambridge Academic English
    176
  • Teaching methodology used during the course of this programme equips the students with fundamental concepts as well as with the technologies that are used in the process of data analysis in the competitive business environment. Professionals who have extensive and varied knowledge and have gained experience by working in the industry teach this innovative programme. This makes the learning process very interactive as students get practical exposure.

    Based on the student’s performance, Grade Point Average is calculated for the purpose of assessment. It also considers the work taken at the university.
  • This full time programme is taught on campus only.

  • M.S Data Analytics syllabus encompasses a wide range of subjects and technologies to understand analyzing of business data, the transformation of information and generation of data reports. The students are required to complete 33 credit hours, which include introductory, reinforcement, proficiency and subject-specific courses.

  • Estimated Costs for the 2019-2020 Academic Year for Graduate International Students
    Location
    Tuition
    Living Expenses
    Health Insurance
    Total
     St. Louis
     $24,750
     $16,030
     $2,475
     $43,255
     
    * We also offer scholarships *
    Living Expenses include estimates for housing, food, personal care, entertainment, and books.
    Health Insurance is mandatory for all international students unless they have a government-sponsored health insurance.

Why study this course?

Data Analysis is becoming very important day by day and for that, candidates are required in the leadership positions for analyzing and assessing the data. M.S Data Analytics in the US focusses on developing and executing key data analytics skills in order to deal with large amounts of data in businesses. It lays a strong foundation by integrating all the data related concepts and practices.

 

Is it worth doing M.S Data Analytics?

This master’s level programme balances theory and practical applications that help to progress long-term career. It teaches fundamental concepts and methods of data problem solving. M.S Data Analytics careers are accelerating at a fast pace as students learn and develop a systematic understanding of the issues and practices concerned with the field of data analytics.

 

Who is this course for?

This course is an appropriate choice for all the students who want to enhance their expertise and proficiency in the current developing domains of data analysis, statistics and machine learning. With the need to store and analyze every type of business transaction, M.S Data Analytics jobs are increasing rapidly because data analysts can take better business decisions and can comprehend the data in an effective manner.

 

What is the scope and future of M.S Data Analytics?

Students who learn the advanced techniques and systems of data analysis are capable of holding leadership and executive positions as they get an array of opportunities in the data analytics field. The career options available for the students are a data analyst, data administrator, data engineer, Business Intelligence Analyst, Advanced Analytics Expert, and many others. M.S Data Analytics salaries offered to the professionals are very lucrative and rewarding.

 

Job Options

1. Data Analyst

2. Project Manager

3. Program Manager

4. Business Intelligence professional, etc

 

Do I need work experience to pursue this course?

It is not mandatory for a professional to have a prior work experience to pursue MS Data Analytics

 

What are the learning outcomes?

M.S Data Analytics eligibility provides the students with the following learning outcomes:

  1. Execute requisite methods and techniques for analyzing, presenting and utilizing business data

  2. Describe and convert information to develop relationships and insights into complex data sets

  3. Formulate data models using formal tools and methodologies that can be used to solve real-world data problems

 

FAQs

1. Is any kind of financial aid available?

Webster University provides the option of financial aid in the form of loans and grants to provide supplementary help to the students in order to cover their educational expenses.

2. What are the key subjects included in this course?

Some of the key subjects taught are Business Finance for Managers, Applied Business Statistics, Social and Ethical issues in Analytics, Databases and Data Warehouses and others specified in the curriculum.