Computer Information Systems

Data Analytics - CCL

Major: 
5884
Effective term: 
2019 Spring
Final term: 
9999
Award: 
CCL
Total credits required: 
18
Description

The Certificate of Completion (CCL) in Data Analytics program is designed to prepare students to model, synthesize, analyze, and present large data sets for business decision making. Courses will focus on the techniques and computer software used in industry to extract data from various data sources, model and integrate that data, and then visualize this data for business decision making and intelligence gathering.

Suggested Course Plan Sequenced by Semester

Program notes

Students must earn a grade of C or better in all courses within the program.

++ indicates any suffixed courses. Effective Spring 2019, the Computer Information System (CIS) courses required by this program are not applicable if taken more than eight (8) years prior to the completion of the program of study. Consult with an Academic Advisor for complete information.

Admission criteria

Students must have satisfactory score on the District math placement test.

Requirements
Credits:18
CIS114DEExcel Spreadsheet 3
CIS117DMMicrosoft Access: Database Management 3
CIS214DEAdvanced Excel Spreadsheet: Level II 3
 
CIS217AMAdvanced Microsoft Access: Database Management (3) OR
CIS276++Any Database Management Systems courses (3) 3
 
GBS151Introduction to Business 3
 
GBS220Quantitative Methods in Business (3) OR
GBS221Business Statistics (3) 3
Competencies
  1. Use a computer spreadsheet program to create, store, modify, and print electronic spreadsheets. (CIS114DE, CIS214DE)
  2. Demonstrate the skills needed to set up, maintain, and use a database management program. (CIS117DM)
  3. Design and create database structures to store, retrieve, update, and display data in a relational database using SQL. (CIS217AM, CIS276++)
  4. Identify the fundamental characteristics and functions of modern business, including business principles, marketing, labor relations, and business risk. (GBS151)
  5. Solve probability applications. (GBS220)
  6. Distinguish between continuous and discrete variables. (GBS220)
  7. Find probabilities for normal random variables by using the standard normal distribution. (GBS220)
  8. Describe the normal distribution and its characteristics. (GBS220)
  9. Calculate and interpret the measures of central tendency for either raw or grouped data. (GBS221)
  10. Use statistical inference techniques and confidence levels for decision making when testing hypotheses. (GBS221)
  11. Use regression and correlation analysis, and interpret the results of the analysis. (GBS221)