Data Analytics
A.S. Degree Computer Information Systems · Laney College · 2026-2027 Catalog
The Data Analytics AS degree is an expansion on the CIS department Data Science Fundamentals Certificate of Achievement and prepares students for careers as data analyst, data scientist, machine learning engineers, business analyst, computer systems analyst, logistics analyst, marketing analyst, and database managers. The multidisciplinary program provides the analytical, methodological, and programming skills required in data processing, information technology, business, and computing. The certificate will also serve as a foundation for continued education at four-year institutions
Career Opportunities
Data analyst, data scientist, machine learning engineers, business analyst, computer systems analyst, logistics analyst, marketing analyst, and database managers.
Program Learning Outcomes
Upon completion of this program a student will be able to:
- Demonstrate the ability to apply statistical analysis of real world data using multiple representations such as graphs, text, or tables, being mindful of concerns around data bias and privacy.
- Use programming and data analytics tools to make statistical inference on data and data sets using computational techniques.
- Write computer scripts and programs to organize, produce visualizations, and numerical summaries of data and data sets.
| Course | Title | Units |
|---|---|---|
| Relational Databases Core Courses (8 units): | 8 | |
| CIS 98 | Database Programming with SQL | 4 |
| BUS 43B | Introduction to Microsoft Excel for Business Applications | 4 |
| Introduction to Programming (4-5 units): | 4-5 | |
| CIS 6 | Introduction to Computer Programming | 5 |
| orCIS 116 | Introduction to Computational Thinking with Data | 4 |
| orMATH 116 | Introduction to Computational Thinking with Data | 4 |
| Introduction to Computer Science (3-5 units): | 3-5 | |
| CIS 5 | Introduction to Computer Science | 5 |
| orCIS 20 | Microcomputer Assembly Language | 4 |
| orCIS 96F | Introduction to Artificial Intelligence and Machine Learning | 3 |
| Foundations in Object Oriented Programming (4 units): | 4 | |
| CIS 25 | Object Oriented Programming Using C++ | 4 |
| orCIS 36A | Java Programming Language I | 4 |
| Data Structures and Algorithms (4-5 units): | 4-5 | |
| CIS 27 | Data Structures and Algorithms | 4 |
| orCIS 61 | Structure and Interpretation of Computer Programs | 5 |
| Foundations of Data Science and Statistics (4-5 units): | 4 | |
| MATH 118 | Foundations in Data Science | 4 |
| orSTAT C1000 | Introduction to Statistics | 4 |
| Total Major Units: | 27-31 | |
| General Education Requirements: | 21 | |
| Electives to meet 60 units | ||
| Total Units: | 60 | |