Dec 06, 2023
This degree is designed for transfer to a four-year institution in numerous fields. Students develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software.
Type of Credential
Associate of Science (A.S.)
Contacts and Additional Information
443-840-4879 or email@example.com
CCBC Catonsville, Melissa Akhimiemona
443-840-5156 or firstname.lastname@example.org
CCBC Essex/Dundalk, James Braman
443-840-1727 or email@example.com
This is a suggested full-time schedule for a student who has completed any developmental course work and has no transfer credits. Refer to the College catalog for specific requirements in selecting General Education Courses .
Courses Needed for This Program*
General Education Requirements and Electives - 29 Credits
General Education Requirements:
Program Requirements - 31 Credits
Total Number of Credits Required for Degree: 60*
*Credit students who are new to college (no successfully completed transferable college credits from other institutions) are required to take ACDV 101 - Academic Development: Transitioning to College . This 1-credit course is designed to be taken in the first semester at CCBC. Students must provide an official transcript(s) from an accredited institution to document successful completion of college coursework for the ACDV 101 requirement to be waived.
This degree is designed for transfer to a four-year institution in numerous fields. Students develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Students apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets.
Upon successful completion of this degree, students will be able to:
- Transfer to a four-year institution for a degree in Data Science or related field.
- Develop and design well-written code to manipulate data for analysis.
- Design and implement solutions in the context of the discipline.
- Apply fundamental data science concepts and algorithms to preform modeling and exploratory data analysis.
- Explain the Data Analytic Life Cycle in the development of computer programs.
- Demonstrate the ability to critically examine, interpret, organize, and describe multiple forms of data.
- Demonstrate appropriate ethical and professional conduct related to technology and data science practices.
- Demonstrate statistical reasoning in everyday life using real world data.
- Construct a solution to real world problems using problem solving methods.