Master of Computer Information Technology with Emphasis in Data Analytics

Northern Arizona University - Flagstaff Campus

USA,Arizona

 1 Shortlist

24 Months

Duration

CAD 26,479/year

Tuition Fee

CAD 65 FREE

Application Fee

Apply Date

USA, Arizona

Type: University

Location Type: Urban

Founded: 1899

Total Students: 29,569 +

Campus Detail

Main Campus Address

S San Francisco St, Flagstaff, AZ 86011, United States

Master of Computer Information Technology with Emphasis in Data Analytics

Program Overview

The CIT Master’s program prepares students to advance their careers in the information technology domain as technology supervisors and project managers, business analysts, lead coders and designers, and researchers.  Given the pervasiveness of technology worldwide, students outside the information technology domain may weave their prior industry experience with information technology theories, processes, and best practices to take on roles within the information technology industry.  Students who would benefit most from completing this degree include individuals pursuing career advancement in the computer information technology domain as well as individuals transitioning their careers from non-technical backgrounds to the computer information technology domain.

The program emphasizes skills related to the interplay between computer information technology and its supervision, the organizational and human impact of technology, technical innovations, the global reach of technology, and research and associated methods as applied to the computer information technology domain.  Theories and models associated with computer information technology, best practices, and current research and examples will provide students with learning experiences rooted in both theory and application of computer information technology concepts and methods to solve business problems.  Students will also develop skills associated with critical thinking and reading, reflection, research, analysis, problem solving, and technical and scholarly writing.

Data Analytics Emphasis

  • Analyze principal expectations of the multiple linear regression model, data classification techniques, and implement diagnostics to assess the validity of expectations.
  • Evaluate and apply different data analytic tools. Analyze random effects to statistical models and apply, assess, and decipher mixed models in R.
  • Apply imputation methods to missing data.
  • Utilize regression models for analyzing and evaluating predictions.
  • Evaluate issues with scaling multiple regression analysis to large datasets; implement methods for large data sets.
  • Demonstrate data analysis and evaluation of results. Create research questions, evaluate model assumptions and take applicable
  • corrective action; interpret the results and create reports.
  • Analyze principal expectations of the multiple linear regression model, data classification techniques, and implement diagnostics to assess the validity of expectations.
  • Evaluate and apply different data analytic tools. Analyze random effects to statistical models and apply, assess, and decipher mixed models in R.
  • Apply imputation methods to missing data.
  • Utilize regression models for analyzing and evaluating predictions.
  • Evaluate issues with scaling multiple regression analysis to large datasets; implement methods for large data sets.
  • Demonstrate data analysis and evaluation of results. Create research questions, evaluate model assumptions and take applicable
  • corrective action; interpret the results and create reports.
  • Categorize, evaluate, and demonstrate use of large-scale analytics tools. Analyze the effects of big data in organizational decision making. Evaluate and critique concepts and principles of Big Data Analytics and Management.
  • Analyze current trends and challenges faced by organizations in dealing with Big Data.
  • Evaluate data sets using Big Data Applications.