Data Analytics - Tools and Techniques, Associate of Applied Business

Curriculum Code #6650

Effective May 2022

Division of Engineering, Business and Information Technologies

This program prepares students to apply the tools and techniques used in data analytics and assist a data scientist.  The process of data analysis is taught in the context of data from manufacturing (IoT), marketing, finance and other sources. Lorain County Community College has articulation agreements with colleges and universities including programs offered by the Lorain County Community College's University Partnership.  

Plan of Study Grid
First Year
Fall SemesterHours
CISS 121 MICROCOMPUTER APPLICATIONS I 3
DATA 101 INTRODUCTION TO DATA ANALYTICS 3
DATA 130 ETHICAL AND LEGAL FRAMEWORK OF BIG DATA 1 3
ENGL 161 COLLEGE COMPOSITION I 3
MTHM 168 STATISTICS 3
SDEV 101 INTRODUCTION TO THE LCCC COMMUNITY 2 1
 Hours16
Spring Semester
CISS 143 DATABASE DESIGN AND IMPLEMENTATION 1 3
DATA 150 DATA ANALYSIS WITH LINUX TOOLS 3
CISS 212 SPREADSHEET APPLICATIONS 3
PHLY 171 INTRODUCTION TO LOGIC 3
PSYH 151 INTRODUCTION TO PSYCHOLOGY 3
 Hours15
Second Year
Fall Semester
DATA 205 MANAGING DATA FOR ANALYTICS 3
DATA 221 MODELING & ANALYSIS WITH R & PYTHON FOR DATA PROFESSIONALS 1 3
DATA 287 WORK-BASED LEARNING I - DATA 1
PHLY 174 CRITICAL THINKING 3
SOCY 151G INTRODUCTION TO SOCIOLOGY 3
Science Elective 3 4
 Hours17
Spring Semester
CMMC 151 ORAL COMMUNICATION 3
DATA 230 PREDICTIVE AND VISUAL ANALYTICS 1 3
DATA 222 BUILDING ANALYTICAL MODELS AND MACHINE LEARNING ALGORITHMS 1 3
DATA 248 DATA ANALYTICS CAPSTONE PROJECT 1 4
DATA 288 WORK-BASED LEARNING II - DATA 1
 Hours14
 Total Hours62
1

Indicates that this course requires a prerequisite or may be taken concurrently.

2

A student must register for the orientation course when enrolling for more than six credit hours per semester or any course that would result in an accumulation of 13 or more credit hours.

3

Science elective from Ohio Transfer 36 (with lab if required by accepting institution).

4

​The data analytic core courses in this program may be earned through a competency-based education option.  See your advisor for more information.  

Program Contact(s):

Douglas Huber
440-366-4785
dhuber@lorainccc.edu

For information about admissions, enrollment, transfer, graduation and other general questions, please contact your advising team.

Program Learning Outcomes

1. Understand the benefits and privacy issues with using Big Data.

2. Utilize the industry common tools to mine large data sets for relationships and other insights.

3. Utilize visualization techniques to discover useful information within large data sets and communicate them to an appropriate audience.

4. Understand the purpose of machine learning and related artificial intelligence algorithms in analyzing large data sets.