Discover the Hidden Patterns
6 - 9 months
7654741
This Program is Perfect For
- Aspiring data professionals looking for a practical introduction to data science
- Learners seeking a flexible, stackable credential without long-term commitments
- Students who want to boost foundational skills while staying open to more advanced data pathways
Program review underway
As we evolve our programs to reflect today’s technology landscape, the specialization in Data Science is under review and is not currently open for new enrollment. If you are enrolled in this specialization and are finishing up your courses, please reach out to us at extension@ucsc.edu. We will help you plan your journey.
After reviewing the current market conditions and engaging with industry, we are now offering new short programs, that are flexible paths to get the skills you need fast. During this time, our specialization programs continue to be under review and we are committed to assisting all enrolled students to finish the specialization programs. To learn more, visit our Short Programs page.
Courses are open to everyone
You are invited to enroll in individual courses to build your knowledge and develop new skills.
Data Science—Discover the hidden patterns
Develop an understanding of data science by learning how to find, organize, manage, and process large volumes of real-world data. In this streamlined package of introductory data science courses, you’ll perform data manipulation and analysis using Python.
By leveraging your mathematical and statistical skills to find patterns, value, and insights, you’ll gain valuable insights and gain expertise in creating stunning visualizations and statistical models using R.
Learning outcomes
Students completing this program should be able to:
- Develop complex functions and scripts to perform complicated calculations to solve engineering, financial, mathematical, and scientific problems and visualize the results of these calculations.
- Install and configure Python and essential Python development tools and write programs to perform data analysis, statistical analysis, learning, and AI techniques.
- Manage and manipulate data, perform data type conversions, merge datasets, deal with missing values, and extract, delete, or transform subsets of data based on logical criteria.
- Discuss the importance of data analysis for data science, data visualization, and exploration.
Stackable skills
You can learn more in this field in the Data Engineering specialization or the more in-depth Data Science and Data Analysis certificate program.
Learn more about this career
Open Positions in the U.S.
Courses
Program Requirements
Total: 3 courses (9 quarter units)
- End with specialization completion review.
1. Required Course(s):
DBDA.X404
$960
You may enroll in this offering at any time.
Sep. 12 - Nov. 14, Sat, 9:00am - 12:00pm
- Live-Online Attend via Zoom at scheduled times.
DBDA.X404.(48)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Sat, 09-12-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 09-19-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 09-26-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 10-03-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 10-10-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 10-17-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 10-24-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 10-31-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 11-07-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 11-14-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
This class is offered in an online synchronous format. Students are expected to log into this course via Canvas at the start time of scheduled meetings and participate via Zoom, for the duration of each scheduled class meeting.
To see all meeting dates, click “Full Schedule” below.
You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.
Required Tools & Materials: R Studio for Mac/Windows, R-binary for Mac/Windows
Recommended Texts:
Data Analysis with Open Source Tools, Philipp J. Janert, O'Reilly Media, 2010. ISBN-10: 0596802358, ISBN-13: 978-0596802356.
R Cookbook, Paul Teetor, O'Reilly Media, 2011. ISBN-10: 0596809158, ISBN-13: 978-0596809157.
The Art of R Programming: A Tour of Statistical Software Design, Norman Matloff, No Starch Press, 2011. ISBN-10: 1593273843, ISBN-13: 978-1593273842.
R in a Nutshell: A Desktop Quick Reference, Joseph Adler, O' Reilly Media, 2012. ISBN-13: 978-1449312084 ISBN-10: 144931208X
Fall
DBDA.X420
$980
You may enroll in this offering at any time.
Jul. 25 - Sep. 26, Sat, 9:00am - 12:00pm
- Live-Online Attend via Zoom at scheduled times.
DBDA.X420.(36)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Sat, 07-25-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 08-01-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 08-08-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 08-15-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 08-22-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 08-29-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 09-05-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 09-12-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 09-19-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
| Sat, 09-26-2026 | 9:00am | 12:00pm | Live-Online | REMOTE |
This class is offered in an online synchronous format. Students are expected to log into this course via Canvas at the start time of scheduled meetings and participate via Zoom, for the duration of each scheduled class meeting.
To see all meeting dates, click "Full Schedule" below.
You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.
Required Tools & Materials:
Access to a computer with Python version 3.6 or higher and Jupyter Notebook is required. The recommended software to obtain the required tools for this course is Anaconda, free Individual Edition: https://www.anaconda.com/products/individual
Murach's Python for Data Science, Scott McCoy, Murach and Associates, 2024, ISBN: 9781943873173.
Recommended Tools & Materials:
Python for Data Analysis, Wes McKinney, O'Reilly Media, Inc., 2022-08-12, ISBN: 9781098103989.
You may enroll in this offering at any time.
Sep. 8 - Nov. 17, Tue, 6:00pm - 9:00pm
- Flexible Attend in person or via Zoom at scheduled times.
DBDA.X420.(37)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Tue, 09-08-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 09-15-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 09-22-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 10-06-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 10-13-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 10-20-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 10-27-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 11-03-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 11-10-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
| Tue, 11-17-2026 | 6:00pm | 9:00pm | Flexible | SANTA CLARA / REMOTE |
This class meets simultaneously in a classroom and remotely via Zoom. Students are expected to attend and participate in the course, either in-person or remotely, during the days and times that are specified on the course schedule. Students attending remotely are also strongly encouraged to have their cameras on to get the most out of the remote learning experience. Students attending the class in-person are expected to bring a laptop to each class meeting.
No meeting on September 29, 2026. To see all meeting dates, click "Full Schedule" below.
You will be granted access in Canvas to your course site and course materials approximately 24 hours prior to the published start date of the course.
Required Tools & Materials: Students are expected to have computers with Python 3.x, Jupyter Notebooks, libraries: Pandas, Matplotlib and Numpy installed. Installing the Anaconda distribution of Python, gives access to Jupyter Notebooks and all the required libraries. Instructions will be provided.
Murach's Python for Data Science, 2nd Edition, Scott McCoy, Mike Murach and Associates, 2024, ISBN: 978-1943873173.
Recommended Tools & Materials:
Python for Data Analysis, 3rd Edition,Wes McKinney, O'Reilly Media, Inc., 2022, ISBN: 9781098103989.
Fall
Summer
Currently no classes scheduled. Would you like to be notified when a class is available?
Summer
2. Completion Review
O-CE0529
$50
You may enroll in this offering at any time.
Schedule
Specialization in Data Science Completion Review Course
Establish Candidacy
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