Data Analytics - Tools and Techniques Intermediate, One-Year Technical Certificate
Curriculum Code #6652
Effective May 2025
This one year technical certificate 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.
| First Year | ||
|---|---|---|
| Fall Semester | Hours | |
| CISS 121 | MICROCOMPUTER APPLICATIONS I | 3 |
| DATA 110 | INTRODUCTION TO DATA ANALYTICS | 4 |
| DATA 130 | ETHICAL AND LEGAL FRAMEWORK OF BIG DATA 2 | 3 |
| ENGL 161 | COLLEGE COMPOSITION I | 3 |
| MTHM 168 | STATISTICS | 3 |
| SDEV 101 | INTRODUCTION TO THE LCCC COMMUNITY 3 | 1 |
| Hours | 17 | |
| Spring Semester | ||
| CISS 143 | DATABASE DESIGN AND IMPLEMENTATION 1 | 3 |
| CISS 212 | SPREADSHEET APPLICATIONS 1 | 3 |
| CYBR 220 | PYTHON SCRIPTING AND PROGRAM CONCEPTS | 3 |
| PHLY 171 | INTRODUCTION TO LOGIC | 3 |
| PSYH 151 | INTRODUCTION TO PSYCHOLOGY | 3 |
| Hours | 15 | |
| Total Hours | 32 | |
- 1
Indicates that this course needs to be taken concurrently with another course.
- 2
Indicates that this course requires a prerequisite.
- 3
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 12 or more credit hours.
Students will need to obtain InfoSec accounts for some courses.
Program Contact(s):
George Taylor
440-366-7014
gtaylor@lorainccc.edu
For information about admissions, enrollment, transfer, graduation and other general questions, please contact your advising team.
Credit for Prior Learning (PLA) options may be available for your program. For more information, please visit our website: www.lorainccc.edu/PLA
Program Learning Outcomes
1. Understand the benefits and privacy issues with using Big Data.
2. Identify the industry-standard tools used to mine large data sets for relationships and other insights.
3. Interpret visualization techniques to discover useful information within large data sets.
4. Understand the purpose of machine learning and related artificial intelligence algorithms in analyzing large data sets.