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DATA ANALYTICS – A.A.S.

Trocaire College’s Data Analytics A.A.S. degree program prepares graduates to assume entry and midlevel management roles that oversee the identification, analysis, and interpretation of volumes of data that are collected from a wide variety of sources. Graduates of the program are prepared to identify patterns and relationships in large data sets, to resolve business questions and make data-driven decisions, and effectively communicate informed tactical and strategic business objectives. Careers include data analyst, data scientist, database administrators, and statistical assistants.

Program Learning Outcomes

All students completing this program are expected to achieve the General Education outcomes described in the General Studies section of the catalog as well as the following learning objectives:

  • Describe the purpose, potential uses, and methods of data collection and analyses in a variety of industries.

  • Apply data mining methodologies.

  • Apply programming to the extract, transfer, and load (ETL) process.

  • Demonstrate competency with data science practices and methodologies using the Cross-Industry Standard Process for Data Mining (CRISP_DM).

  • Use common data analysis and management tools (e.g., SQL, DBMS applications, etc.) demonstrate proficiency designing, creating, querying and managing databases for analytic processing.

  • Validate patterns and relationships in large data sets using statistical tools.

  • Create and modify customizable tools for data analysis and visualization per the evaluation of characteristics of the data and the nature of the analysis.

  • Demonstrate ability to manage a project from the design stage to the final report.

  • Work collaboratively with team members in assembling, analyzing and reporting findings.

  • Produce clear, written reports of data findings.

Data Analytics – A.A.S. Curriculum

BIOEL Biology Elective - 3 credits
BU300 Project Management - 3 credits
DA101 Introduction to Data Science - 3 credits
DA102 Data Analysis - 3 credits
DA103 SQL for Data Analysis - 3 credits
DA104 Data Mining - 3 credits
DA105 Big Data Architecture - 3 credits
DA106 Problem Solving, Decision-Making, & Computer Application in Business - 3 credits
DA200 Statistical Methods in Data Science - 3 credits
DA201 Data Analysis with R - 3 credits
DA202 Data Visualization and Business Intelligence - 3 credits
DA203 Advanced Data Visualization - 3 credits
DA204 Capstone Experience in Data Science - 3 credits
EN101 English Composition - 3 credits
GS100 or GS102 College Seminar or College Success -  1 - 3 credits*
GS320 Research Methods and Designs - 3 credits
MA120 Statistics I - 3 credits
PH107 Logical Reasoning and Decision Making - 3 credits
PH206 Ethics in Data Science - 3 credits
PH215 Logic - 3 credits
PSY101 General Psychology - 3 credits
Total Program Credits  - 61

*GS100 College Seminar or GS102 College Success must be taken at the main campus

Additional Degree Requirements

A minimum grade of “C” in BU300, DA101, DA102, DA103, DA104, DA105, DA106, DA200, DA201, DA202, DA203, DA204, GS100 or GS102, GS320, MA120 and a Quality Point Average of 2.0.

BIO & BIOEL Course Descriptions
BU Course Descriptions
CNA Course Descriptions
DA Course Descriptions
EN Course Descriptions
GS Course Descriptions
MA Course Descriptions
PH Course Descriptions
PSY Course Descriptions