Data Analytics - Tools and Techniques, Associate of Applied Business

Curriculum Code #6650

Effective May 2019

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 Scientists.  The courses are in partnership with the IBM Academy and leverage IBM and open source applications.  Each student will have access to the IBM Cloud for hands-on lab activities.  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 130 ETHICAL AND LEGAL FRAMEWORK OF BIG DATA 1 3
ENGL 161 COLLEGE COMPOSITION I 3
MTHM 168 STATISTICS 3
SDEV 101 COLLEGE 101 2 1
 Hours13
Spring Semester
CISS 143 DATABASE DESIGN AND IMPLEMENTATION 1 3
CISS 212 SPREADSHEET APPLICATIONS 3
PHLY 171 INTRODUCTION TO LOGIC 3
PSYH 151 INTRODUCTION TO PSYCHOLOGY 3
DATA 220 LINUX ADMINISTRATION FOR BIG DATA 1 3
 Hours15
Second Year
Fall Semester
CYBR 220 PYTHON SCRIPTING AND PROGRAM CONCEPTS 3
DATA 200 DATA MANAGEMENT IN BIG DATA 1 3
PHLY 174 CRITICAL THINKING 3
Science Elective 3 4
SOCY 151G INTRODUCTION TO SOCIOLOGY 3
 Hours16
Spring Semester
CMMC 151 ORAL COMMUNICATION 3
DATA 210 BIG DATA MANAGEMENT TECHNOLOGIES 1 3
DATA 230 PREDICTIVE AND VISUAL ANALYTICS 1 3
DATA 240 DATA ANALYTICS WITH WATSON STUDIO 1 4
DATA 247 BIG DATA PROJECTS 1 3
 Hours16
 Total Hours60

Students will need to obtain IBM Cloud accounts.

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.

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.