StudyQA — Master: Data Analytics

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Description Contents Requirements

Data analytics is one of the most in-demand career paths in todays marketplace for high-skill/high pay jobs.

Organizations across industries collect large amounts of data for a variety of reasons: to gain a competitive advantage, to improve the efficiency of operations, to reduce fraud/waste/abuse, to better understand customers better, among others.

Our program is designed to train students to acquire analytical skills and learn critical methodologies to manage and utilize large amounts of data.

Students with a variety of professional and academic backgrounds can apply to our Data Analytics graduate program. Prerequisite courses are available during the summer for students with a non-tech background.

Our 33-credit program is structured to fit one full academic year, including a sponsored capstone paid internship during summer.

As a graduate in our program in Data Analytics you will develop skill sets in these core areas:

Data Mining and Knowledge Discovery

Managing Big Data: Modeling, Retrieving, Transforming and Organization of Big Data

Data Visualization, Presentation and Interpretation

The 33 credits of the MS degree program consist of five three-credit core graduate courses, four three-credit graduate elective courses, and a six-credit capstone course based on a sponsored project work. The core courses are:

IA 510 - Database Modeling, Design and Implementation
IA 520 - Optimization Methods for Analytics
IA 530 - Probability and Statistics for Analytics
IA 640 - Information Visualization
IA 650 - Data Mining

Some of the core courses may be waived if the students can demonstrate that their previous undergraduate or graduate coursework contains equivalent material. In those cases, students will be required to take a greater number of elective courses to satisfy 33-credit program requirement.

Elective courses are offered in a variety of areas and they include but are not limited to the following:

IA 605 - Data Warehousing
IA 505 Tabular Data Analytics
IA 630 - Modeling for Insight (pre-requisite: Tabular Data Analytics)
IA 670 - Geospatial Systems
CS 549 - Computational/Machine Learning
CS 551 - Artificial Intelligence
CS 559 - Human Computer Interaction
EC 611- Econometrics
EE 501 - Digital Signal processing
ES 505 - Design of Experiments and Analysis of Data
EE 574 - Pattern Recognition
ME 529, Stochastic Processes for Engineers
OM 680 - Strategic Project Management
EC 611 - Econometrics
MK 696 Marketing Research Methods

IA690 - Capstone Project is a course centered on a sponsored data analytics projects with interdisciplinary teams. Capstone projects, depending on project parameters could consist of a 2 unit seminar w/4 unit project (consistent with engineering curriculum as currently offered) and/or be a mentored capstone of 6 total units. Depending on the nature of the capstone and its sponsorship, projects could be on-site fieldwork intensive.

A minimum of 30 credit hours, at least 20 of which must be earned in residence at Clarkson.A minimum of 18 credit hours of graduate coursework with an average grade of B or better. At least 12 hours of the coursework should be done with the Electrical and Computer Engineering Department.A minimum of 6 credit hours of thesis and two credit hours of seminar.A thesis must be submitted and defended orally before a committee of at least three Clarkson faculty members. Exceptions may be granted to outstanding students who decide to pursue Ph.D. work.Important Note to International Applicants: International students must be consistent in the manner in which they present their name on official documents. Be sure to show your name on the application in the same manner that you want it to be shown on your passport, immigration documents, transcripts and all other official documents. Family (surname) and first name are the only names listed on the I-20. There should be a clear understanding as to what are your given/first name, middle name, and family/surname.Complete the ApplicationA complete application file consists of the following items (click for more information):Application FormResume and Statement of PurposeLetters of Recommendation - 3 letters requiredOfficial TranscriptsTest Scores - GRE and TOEFL/IELTS (if applicable)Supplemental information may be submitted if desired; this could include any other information that may help us evaluate your application.