Data for impact
9 - 12 months
6184569
This Program is Perfect For
- Aspiring data professionals and analysts aiming to drive business decisions through data
- Professionals seeking flexible, intensive upskilling with career and international appeal
- Learners aiming to build tangible data skills and credentials in high-demand areas
Learn the language of data
The Data Science and Data Analytics certificate program equips students with practical and analytical skills essential for success in today’s data-driven industries. The required coursework builds a solid foundation in database design and SQL programming, data analysis, and Big Data technologies. Students learn to handle and work with relational databases, manipulate, transform, and visualize data using R and Python, and design efficient data pipelines using modern frameworks such as Hadoop, Spark, Hive, and Kafka.
Courses introduce concepts in generative AI, highlighting its growing impact on data science.
Focus your studies
Learners can choose pathways in data science, artificial intelligence, or data engineering and focus their exploration on machine learning, deep learning, data visualization, or cloud-scale database systems.
Guided by Silicon Valley industry experts, the program emphasizes hands-on, project based learning and culminates in a professional portfolio that demonstrates readiness for data-focused roles across industries.
Certificate learning outcomes
- Design and implement data-driven functions to solve complex analytical problems and visualize insights for decision-making.
- Install and configure Python and key tools to build programs that apply data analysis, statistical methods, machine learning, and Artificial Intelligence techniques.
- Manage databases by converting, merging, cleaning, and transforming data.
- Explain and apply data analysis, visualization, and exploration to draw insights from real-world datasets.
Two specializations for the Data Science Data Analytics industry
Data Science (9 units)
Data Engineering (8 units)
Courses
Program Requirements
Total: 5 courses (15 quarter units).
- 3 required courses (9 quarter units)
- 2 elective courses (minimum 6 quarter units)
- End with certificate of completion review.
1. Required Course(s):
DBDA.X404
$910
You may enroll in this offering at any time.
Jun. 25 - Aug. 27, Thu, 6:30pm - 9:30pm
- Flexible Attend in person or via Zoom at scheduled times.
DBDA.X404.(47)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Thu, 06-25-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 07-02-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 07-09-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 07-16-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 07-23-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 07-30-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 08-06-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 08-13-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 08-20-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Thu, 08-27-2026 | 6:30pm | 9:30pm | 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.
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.
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
|| Skills Needed:
Prerequisites / Skills Needed
Spring
Summer
DBDA.X415
$910
You may enroll in this offering at any time.
Apr. 1 - Jul. 1, Wed, 12:01am - 11:59pm
- Online Self-Paced Work online at your own pace.
DBDA.X415.(861)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Wed, 04-01-2026 | 12:01am | 12:02am | Online Self-Paced | ONLINE |
| Wed, 07-01-2026 | 11:58pm | 11:59pm | Online Self-Paced | ONLINE |
Note: Based on the requirements for special programs, such as CMU, students may complete this course early and receive a letter grade before the official end date. Click here for details.
Online Self-Paced courses have a structured learning environment where students are allowed to complete the work at their own pace. Students may complete the coursework early or use the entire duration of the course. This course is largely self-study with instructor guidance and includes online learning modules, assignments, and/or quizzes. All course materials and assignments will be available at the beginning of the course on Canvas, our learning management system.
For this section, student access begins on April 1, but you may still enroll until May 13, 2026. All course work must be completed by 11:59 pm on July 1, 2026.
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: MySql
Students are required to have access to a computer with a 8GB of RAM preferred (4GB minimum) and the ability to install software. For further details, see https://www.mysql.com/support/supportedplatforms/workbench.html.
Recommended Texts:
Murach's MySQL, 3rd Edition, Joel Murach, Mike Murach & Associates, 2019, ISBN: 978-1943872367.
Teach Yourself SQL in 24 Hours, 5th Edition, Ryan Stephens, et al., Sams Publishing, ISBN: 978-0672335419.
|| Skills Needed:
Prerequisites / Skills Needed
Spring
Currently no classes scheduled. Would you like to be notified when a class is available?
Spring
2. Electives: Data Science
DBDA.X420
$980
You may enroll in this offering at any time.
Apr. 2 - Jun. 4, Thu, 6:00pm - 9:00pm
- Live-Online Attend via Zoom at scheduled times.
DBDA.X420.(35)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Thu, 04-02-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 04-09-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 04-16-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 04-23-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 04-30-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 05-07-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 05-14-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 05-21-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 05-28-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
| Thu, 06-04-2026 | 6:00pm | 9:00pm | Live-Online | REMOTE |
Students may still enroll if they missed the 1st class session. However, they need to communicate with the instructor via Canvas and catch up on all missed work prior to the 2nd class meeting.
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: 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.
|| Skills Needed:
Prerequisites / Skills Needed
You may enroll in this offering at any time.
Jul. 25 - Aug. 29, Sat, 9:00am - 2:00pm
- Flexible Attend in person or via Zoom at scheduled times.
DBDA.X420.(36)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Sat, 07-25-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-01-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-08-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-15-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-22-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-29-2026 | 9:00am | 2:00pm | 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.
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.
|| Skills Needed:
Prerequisites / Skills Needed
Spring
Summer
DBDA.X419
$980
You may enroll in this offering at any time.
Jun. 22 - Aug. 24, Mon, 6:30pm - 9:30pm
- Flexible Attend in person or via Zoom at scheduled times.
DBDA.X419.(17)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Mon, 06-22-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 06-29-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 07-06-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 07-13-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 07-20-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 07-27-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 08-03-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 08-10-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 08-17-2026 | 6:30pm | 9:30pm | Flexible | SANTA CLARA / REMOTE |
| Mon, 08-24-2026 | 6:30pm | 9:30pm | 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.
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: Tableau desktop for Mac/Windows - latest edition from Tableau.com
Recommended Text:
Data Visualization: A Practical Introduction, Kieran Healy, Princeton University Press, 2018. ISBN: 9780691185064
|| Skills Needed:
Prerequisites / Skills Needed
Summer
Currently no classes scheduled. Would you like to be notified when a class is available?
Spring
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter
3. Electives: Artificial Intelligence
AISV.X400
$980
You may enroll in this offering at any time.
Jul. 25 - Aug. 29, Sat, 9:00am - 2:00pm
- Flexible Attend in person or via Zoom at scheduled times.
AISV.X400.(46)
Schedule
| Date | Start Time | End Time | Meeting Type | Location |
|---|---|---|---|---|
| Sat, 07-25-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-01-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-08-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-15-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-22-2026 | 9:00am | 2:00pm | Flexible | SANTA CLARA / REMOTE |
| Sat, 08-29-2026 | 9:00am | 2:00pm | 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.
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.
Programming Tools: Current version of Python with ability to install packages as needed.
|| Prerequisites: Skills Needed:
Prerequisites / Skills Needed
Spring
Summer
Currently no classes scheduled. Would you like to be notified when a class is available?
Spring
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter
4. Electives: Data Engineering
Currently no classes scheduled. Would you like to be notified when a class is available?
Spring
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter
Currently no classes scheduled. Would you like to be notified when a class is available?
Fall
Currently no classes scheduled. Would you like to be notified when a class is available?
Spring
5. Completion Review:
O-CE0122
$95
You may enroll in this offering at any time.
Schedule
Please enroll in the Data Science and Data Analytics Certificate Completion Fee only when all of the certificate requirements have been met and your final grades are posted.
Recommended course sequence
The sequence may vary based on student background and professional interest. Choose one of the two specialized tracks—Track 1: Data Science or Track 2: Data Engineering
Substitutions | Shared credits
Some technology courses may be listed in more than one program. However, only one course may be shared between two certificate programs unless otherwise noted.
To receive your certificate
Upon completion of the course sequence, please request your Data Science and Data Analytics Certificate Completion Review.
Requisite knowledge
Please review the course descriptions to ensure that you have taken necessary prerequisites or meet the requirements through job experience or previous education. You can learn more about each course in the Syllabus Library.
Grade requirements
Please note that only letter grades of C or higher may be applied to a certificate, and in some programs, students may have more stringent requirements. Students in most employer- and government-sponsored payment programs, such as workforce development, as well as international students on F-1 visas, need to maintain a B average to meet their requirements.
See Grading and Credits Policy for further information.
Establish Candidacy
Instructors
Certificate Program Advisory Committee
PARTHASARATHY PADMANABHAN, M.B.A.
Principal Software Engineer
Instructor & Program Chair, Data Science and Data Analytics Advisory Board
PIYUSH BHARGAVA, MS
Senior Director in Data & Analytics, DocuSign
Former Distinguished Engineer, Cisco
CHING-FONG "CF" SU, PhD, MS
Vice President of Machine Learning, Hyperscience
LISE GETOOR, PhD, MS
Professor, Computer Science and Engineering Department | Center Director, D3 Data Science Research Center
University of California, Santa Cruz
ASHISH GUPTA, MS, BTech
Principal Engineer, NetsKope
HIEN LUU, MS, BSEE
Head of Machine Learning Infrastructure, Zoox
Chair AI Business Practices and Instructor, Data Science and Data Analysis Certificate Program
RAMA ORUGANTI, MCA
Senior Director of Data & Analytics, Cisco
ARMEN PISCHDOTCHIAN, MBA, MA, BA
Adjunct Professor | Wentworth Institute of Technology & University of the Cumberlands
RAQUEL PRADO, PhD
Professor, Statistics Department, University of California, Santa Cruz
Related Programs
