Data Science, Certificate of Achievement (C)
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Program Overview
Data Science, Certificate of Achievement (C)
Overview
The Data Science Certificate of Achievement will prepare students for today’s data-driven world. The program is designed to enhance career opportunities in data science areas, including data and system analysis, data science research, business analytics, data engineering, database administration, statistical assistance, software engineering, and management. The core sequence covers data science foundational concepts, core programming practices, database management and an introduction to version control software. Skills mastered in this sequence of courses can be a first step toward a career in data science.
Requirements
Complete all Department Requirements for the Certificate of Achievement with a cumulative grade point average (GPA) of 2.0 or better. Candidates for a Certificate of Achievement are required to complete at least 20% of the department requirements through SBCC.
Course List
| Code | Title | Units |
|---|---|---|
| CIS 107 | Introduction to Database Systems | 2-4 |
| or CIS 117 | Introduction to SQL Programming | |
| CS 106 | Theory and Practice II | 3 |
| or CS 114 | Intermediate Python | |
| CS/MATH 118 | Data Science for All | 4 |
| CS 134 | Version Control with Git | 2.5 |
| Complete 3 courses from the following (not used to satisfy the Core Courses above) | 8-14 | |
| COMM 288 | Communication Research Methods | |
| CS 104 | Introduction to Programming | |
| CS 105 | Theory and Practice I | |
| CS 106 | Theory and Practice II | |
| CS 108 | Discrete Structures | |
| CS 114 | Intermediate Python | |
| CS 133 | Introduction to Programming for Engineers | |
| CS 137 | C Programming | |
| CS 140 | Object-Oriented Programming Using C++ | |
| ERTH/GEOG 171 | Introduction To Geographic Information Systems And Maps | |
| MATH 117 | Elementary Statistics | |
| or PSY 150 | Statistics for the Behavioral Sciences | |
| or SOC 125 | Introduction to Statistics in Sociology | |
| MATH 150 | Calculus with Analytic Geometry I | |
| MATH 160 | Calculus with Analytic Geometry II | |
| MATH 180 | Transition to Advanced Mathematics | |
| MATH 200 | Multivariable Calculus | |
| MATH 210 | Linear Algebra | |
| MATH 220 | Differential Equations | |
| PSY 200 | Research Methods and Experimental Design in Psychology | |
| SOC 115 | Introduction To Social Research | |
| Total Units | 19.50-27.50 |
Learning Outcomes
- Apply foundational data science concepts including computing summary statistics, creating data visualizations, simulating experiments, and probability concepts.
- Use foundational programming concepts to explore and analyze real-world datasets using problem decomposition, and code design strategies.
- Design, create, query, and manage databases for analytic processing using SQL.
- Understand and employ proper version-control configuration and operations using a version control system such as Git.
- Understand limitations and issues surrounding data analysis in terms of bias, ethics, establishing causality and privacy.
Recommended Sequence
Make an appointment with your SBCC academic counselor through Starfish to create a Student Education Plan that reflects a recommended course sequence for this program that is tailored to your individual needs.