MS Big Data Analytics

Master of Science in Big Data Analytics

The MS in Big Data Analytics program, in the School of Science and Engineering, Miami, is developed to provide real-world experience in critical analytical skills that are needed in this fast-growing field. It focuses on preparing students to formulate strategies and make critical decisions based on real data.

The MS in Big Data Analytics (MSBDA) is built around the focus of providing graduates with an understanding of the technologies and methodologies necessary to create and manage big data storage infrastructure, large-scale dataset analytics, big data visualization, and big data applications in organizations.

 

 

 

Students will study:

  • Data Warehousing
  • Data Mining
  • Information Technology
  • Statistical Models
  • Predictive Analytics
  • Machine Learning
  • Application principles to sharpen their organizational and technical competencies to implement data gathering, cleansing, integration and modeling tasks and data asset analysis

 

The MSBDA is aimed at students who wish to become data scientists and analysts in various fields such as:

  • Biomedical Informatics Research
  • Social Network
  • Marketing
  • New Media
  • Finance
  • Other information intensive groups generating and consuming large amounts of data

The focus of the degree is on the scientific theories and engineering applications of data analytics for solving big data problems.

The unique features of this program that distinguishes its curriculum are: a.) a focus on offering contemporary and practical courses and projects in big data platform administration including data warehouse, data mining, data visualization and intelligence engineering management, b.) an emphasis on providing internship to cultivate the big data problem solving skills as data scientists or data engineers, and c.) an international perspective on big data technology and market services.

MS Big Data Analytics Degree Highlights

  • Gain valuable business intelligence and experience as you apply advanced scientific theories to solve complex Big Data problems.

  • Become an in-demand candidate for the many exciting roles in Data Analytics.

  • Learn the communication skills necessary to help businesses interpret data and make strategic decisions

Career Landscape

According to the State of Business Intelligence Software and Emerging Trends from A Forrester Research study showed that business analytics is the fastest growing category of global IT software expenditures, and approximately 69% of businesses are interested in using analytics.

  • Our graduates will be able to find jobs in businesses as Data Administrators and Data Scientists
  • The demand to hire Big Data Analytics graduates is increasing
  • 73% of organizations have already invested or plan to invest in big data by 2017

Featured Professors


Curriculum

MS in Big Data Analytics (BDA) at St. Thomas University (STU)

The curriculum for the MS in BDA at STU is listed below. (Every course is a 3-credit course)

 

Course Number

Course Name

Prerequisite

Semester

MAT 502

Statistical Methods

None

FL 1

CIS 541

Fundamentals of Big Data Analytics

None

FL 1

CIS 544

Data Mining and Machine Learning

CIS 541 or MAT 502

FL 2

CIS 543

Programming for Big Data Analytics

CIS 541 or Programming course

FL 2

MAT 602

Applied Machine Learning

CIS 544 and MAT 502

SP 1

CIS 545

Big Data Warehousing

CIS 541 or CIS 543 or approval

SP 1

CIS 546

Data Visualization

None (recommended: CIS 541)

SP 2

CIS 542

Internet Protocols and Network Security

None (recommended: CIS 543)

SP 2

CIS 626

Big Data Analytics Applications

MAT courses and CIS 5XX courses

SU 1

CIS 627

Big Data Analytics Capstone

CIS 626

SU 1

 

Suggested Degree Plan

The program can be completed in five 8-weeks terms with the following suggested/ideal course sequence:

 

1st Term          (Fall 1)                           CIS 541            MAT 502

2nd Term          (Fall 2)                          CIS 544            CIS 543

3rd Term          (Spring 1)                     CIS 545            MAT 602

4th Term          (Spring 2)                     CIS 546            CIS 542

5th Term          (Summer 1)                 CIS 626            CIS 627

 

Taking into account pre-requisites, the following is the suggested sequence of courses:

CIS 541                     -->        CIS 543           -->        CIS 545

MAT 502                     -->        CIS 544           -->        MAT 602

(If a student plans to take a different sequence, plan should be approved by program director)

CIS 546 and CIS 542 do not have a set pre-requisite (suggested: CIS 541 and CIS 543 if in the MS in Big Data Analytics Program). Both, CIS 546 and CIS 546 are generally scheduled in the Spring, unless there is a change in demand.

CIS 626 and CIS 627 are taken concurrently and any student planning to register in such courses must have completed the previous 8 courses. Both CIS 626 and CIS 627 are generally scheduled in the Summer.

Students in the MBA program that pursue a data analytics concentration, must take: CIS 541, CIS 544, CIS 545, CIS 546

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https://studatascience.github.io/welcome_page/index.html

https://www.stu.edu/DataAnalytics



Contact Graduate Adviser Dr. Sean Mondesire , Program Director, smondesire@stu.edu at 305-474-6075


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