Data Science (DS) is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data. Data Science program focuses on the fundamentals of computer science, applied mathematics, probability, statistics, optimization, and machine learning while incorporating real-world examples. New computational and analytic approaches to a vast array of forms, scales, and sources of data are now critical to research, decision-making, and action.
The Palomar College AS in Data Science (DS) program is designed to give students a broad introduction to the field of data science, including mathematics and computational tools, to explore a broad range of data, and prepare them to transfer to a Bachelor of Science degree in DS program at a 4-year university.
Student Learning Outcomes
Apply computer science knowledge, concepts, and techniques to utilize programming languages, software tools to develop mathematical models, computational methods, and machine learning algorithms for exploring, analyzing, and making predictions from data.
Apply analytical concepts and techniques from calculus and linear algebra to analyze and solve problems in data science including but not limited to statistical inference, optimization, integration, and matrix operations.
Analyze real-world data sets to provide insights from both structured and unstructured data to ask appropriate questions about the data and interpret predictions based on their domain knowledge.
Demonstrate communication, teamwork, and project-based learning skills necessary to function effectively on teams to accomplish a common goal.
Students will address ethical issues arising in data science, including the moral obligations of preserving privacy; mitigating the risk of attach; avoiding bias in models and algorithms; maintaining data transparency to data subjects; among others.
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After completion of the AS in Data Science, students will be able to:
1. Apply current data science concepts, techniques, and practices to solve complex problems.
2. Analyze a given data science problem and formulate a solution in terms of the datasets needed, the techniques required or the technologies to be utilized.
3. Prepare students to transfer to a four-year school and earn a bachelor’s degree in data science.
4. Effectively communicate insights, analysis, conclusions, or solutions to a diverse audience.
Data Science is a high demand multidisciplinary program with strong projected employment opportunities in the future. Several universities now offer bachelor’s degrees in data science, including UCSD, UC Berkeley, UCI, and UC Riverside; CSUSM is currently developing a degree. The Data Science bachelor’s degree is established and ready to accept Data Science transfer students. Local feeder high schools, including San Marcos High School and Poway High School, offer Data Science Math classes. Palomar College is striving to be the first community college in San Diego County to offer an AS degree in Data Science to provide students with a needed transfer path.
The team of professors from both Math and Computer Science did a detailed examination of the four-year degrees offered in Data Science in California. From that a list of courses was developed to be a great fit for most bachelor’s degree programs in Data Science. Furthermore, no new courses were developed to create this degree. The courses are a set of STEM courses that are well established in several degree programs.
| Course | Title | Units | Year/Semester (Y1 or S1) |
|---|---|---|---|
| Math 140 | Calculus with Analytical Geometry, First Course | 5 | F1 |
| Math 141 | Calculus with Analytical Geometry, Second Course | 4 | S1 |
| Math 200 | Introduction to Linear Algebra | 3 | F1 |
| Domain Knowledge Electives | S2 | ||
| Biol 200 | Foundations of Biology I | 5 | |
| Biol 201 | Foundations of Biology II | 5 | |
| Econ 101 | Principles of Economics (Macro) | 3 | |
| Econ 102 | Principles of Economics (Micro) | 3 | |
| Soc 205/Psyc 205 | Statistics for the Behavioral Sciences | 4 | |
| Math 120 | Elementary Statistics | 4 | |
| Data Science Electives | |||
| CSIT 165 | R Programming | 3 | |
| CSIT 226 | Data Visualization | 3 | |
| CSIT 230 | Data Modeling | 3 | |
| CSIT 275 | Advanced Python Programming | 3 | |
| CSIT 250 | Introduction to Artificial Intelligence | 4 | |
| CSIT 290 | Introduction to Machine Learning | 4 | |
| Math Electives | |||
| Math 120 | Elementary Statistics | 4 | |
| Math 205 | Calculus with Analytic Geometry, Third Course | 4 | |
| Math 245 | Discrete Mathematics | 3 |
Dr. Javier Ayala · 10/18/23
GC supports.
Dr. Al Taccone · 10/18/23
MiraCosta College endorses.
Efrain Silva · 10/17/23
IVC supports new program.
Susan Wyche · 10/17/23
Palomar College supports this program.
Jennifer Lewis · 10/17/23
SWC supports Palomar's development of this new COA.
John Edwards · 10/06/23
Palomar College submitted the appropriate LMI from the COE. The COE recommends proceeding with caution when developing a new program because 1) there is a low number of similar programs that exist in the region; 2) entry-level wages are above the living wage; but 3) the typical entry-level education is a bachelor’s degree. Colleges should also note that the typical educational attainment of workers employed nationally in this occupation is a master’s degree or higher.
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