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.
data-science-data-analysis-badge-ucsc-220.png

Two specializations for the Data Science Data Analytics industry

Data_Science_Specialization: person's hands typing at a keyb
Data Science (9 units)
Data Engineering Specialization - A hand surrounded by image
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.

View Course Calendar

See the Syllabus Library
1. Required Course(s):
Title units Fall Spring Summer Winter
Data Analysis, Introduction 3.0 Flexible Flexible
Relational Database Design and SQL Programming 3.0 Online Self-paced
Big Data and Python for Performance 3.0 Flexible
2. Electives: Data Science
Title units Fall Spring Summer Winter
Python for Data Analysis 3.0 Live-Online Flexible
Dashboards and Data Visualization 3.0 Flexible
Business Intelligence Solutions 3.0 Flexible
Data Modeling, Introduction 3.0 Live-Online
3. Electives: Artificial Intelligence
Title units Fall Spring Summer Winter
Introduction to Machine Learning 3.0 Flexible, Live-Online Flexible
Deep Learning and Artificial Intelligence 3.0 Flexible, Live-Online
Python for Machine Learning 3.0 Flexible
4. Electives: Data Engineering
Title units Fall Spring Summer Winter
NoSQL Databases, Introduction 3.0 Flexible
Hands-On Data Engineering 3.0 Live-Online
MySQL and Oracle Database for Developers and Designers 2.0 Flexible
The Internet of Things: Big Data Processing and Analytics 3.0 Live-Online
5. Completion Review:
Title units Fall Spring Summer Winter
Data Science and Data Analytics Certificate Completion Fee

1. Required Course(s):

Data Analysis, Introduction
DBDA.X404
$910
You may enroll in this offering at any time.
Partha Padmanabhan, Instructor and Chair of the Data Science and Data Analysis Certificate Program
Parthasarathy Padmanabhan
Mar. 31 - Jun. 2, Tue, 6:00pm - 9:00pm
  • Flexible Attend in person or via Zoom at scheduled times.
DBDA.X404.(46)
Schedule
Date Start Time End Time Meeting Type Location
Tue, 03-31-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 04-07-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 04-14-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 04-21-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 04-28-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 05-05-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 05-12-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 05-19-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 05-26-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Tue, 06-02-2026 6:00pm 9:00pm Flexible SANTA CLARA / 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 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: 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

||

Prerequisites / Skills Needed

Skills Needed:

  • Some programming experience is recommended. (R will be covered in class and used in examples. Python experience can be helpful.) Basic knowledge of probability and statistics required, at the level of basic statistics textbooks (see example: www.stattrek.com).
You may enroll in this offering at any time.
Venkata Duvvuri
Venkata Duvvuri
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

||

Prerequisites / Skills Needed

Skills Needed:

  • Some programming experience is recommended. (R will be covered in class and used in examples. Python experience can be helpful.) Basic knowledge of probability and statistics required, at the level of basic statistics textbooks (see example: www.stattrek.com).
Spring
Summer
Relational Database Design and SQL Programming
DBDA.X415
$910
You may enroll in this offering at any time.
Ruth A Arthur-Asmah
Ruth Arthur-Asmah
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.

||

Prerequisites / Skills Needed

Skills Needed:

  • Familiarity with general database concepts and ability to install software or databases on a personal computer.
Spring
Big Data and Python for Performance
DBDA.X401
$910
You may enroll in this offering at any time.
Hemil N Patel
Hemil Patel
Apr. 1 - Jun. 3, Wed, 6:30pm - 9:30pm
  • Flexible Attend in person or via Zoom at scheduled times.
DBDA.X401.(35)
Schedule
Date Start Time End Time Meeting Type Location
Wed, 04-01-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-08-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-15-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-22-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-29-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-06-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-13-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-20-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-27-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 06-03-2026 6:30pm 9:30pm Flexible SANTA CLARA / 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 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.

||

Prerequisites / Skills Needed

Skills Needed:

  • Basic Python programming knowledge and familiarity with Python data analysis libraries such as pandas, or completion of a course such as DBDA.X420 - "Python for Data Analysis."
Spring

2. Electives: Data Science

Python for Data Analysis
DBDA.X420
$980
You may enroll in this offering at any time.
Sara Saatchi is an instructor for UCSC Extension Technology Courses.
Sara Saatchi
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.

||

Prerequisites / Skills Needed

Skills Needed:

  • Helpful, but not required, are a basic experience in any programming language and a rudimentary knowledge of statistics.
You may enroll in this offering at any time.
Partha Padmanabhan, Instructor and Chair of the Data Science and Data Analysis Certificate Program
Parthasarathy Padmanabhan
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.

||

Prerequisites / Skills Needed

Skills Needed:

  • Helpful, but not required, are a basic experience in any programming language and a rudimentary knowledge of statistics.
Spring
Summer
Dashboards and Data Visualization
DBDA.X419
$980
You may enroll in this offering at any time.
Partha Padmanabhan, Instructor and Chair of the Data Science and Data Analysis Certificate Program
Parthasarathy Padmanabhan
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

||

Prerequisites / Skills Needed

Skills Needed:

  • Knowledge of database concepts and any business experience related to decision-making.
Summer
Business Intelligence Solutions
DBDA.X402
$740
You may enroll in this offering at any time.
Partha Padmanabhan, Instructor and Chair of the Data Science and Data Analysis Certificate Program
Parthasarathy Padmanabhan
Apr. 4 - Jun. 13, Sat, 9:00am - 12:00pm
  • Flexible Attend in person or via Zoom at scheduled times.
DBDA.X402.(15)
Schedule
Date Start Time End Time Meeting Type Location
Sat, 04-04-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 04-11-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 04-18-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 04-25-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 05-02-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 05-09-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 05-16-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 05-30-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 06-06-2026 9:00am 12:00pm Flexible SANTA CLARA / REMOTE
Sat, 06-13-2026 9:00am 12:00pm 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 May 23, 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 Materials: Microsoft Power Suite
The course will be based in the following software applications: Microsoft Excel PowerPivot, Power Query and Microsoft Power BI Desktop. Each of these applications can be installed for free on a PC.  The University also supplies a platform to access the software for free for all enrolled students. Instructions for accessing the software will be part of the first Module. 

Recommended Texts:
Microsoft Business Intelligence Tools for Excel Analysts, Michael Alexander, et al. Publisher: Wiley, 2014 ISBN: ISBN-10: 1118821521; ISBN-13: 978-1118821527

Beginning Power BI: A Practical Guide to Self-Service Data Analytics Edition: 3rd Edition, Dan Clark Publisher: Apress Media, LLC, 2020 ISBN: ISBN-10: 1484256190; ISBN-13: 978-1484256190 

Power Pivot and Power BI: The Excel User's Guide to DAX, Power Query, Power BI &Power Pivot in Excel 2010-2016 Edition: Second Edition, Rob Collie and Avichal Singh Publisher: Holy Macro, 2016 ISBN: ISBN-10: 1615470395; ISBN-13:978-1615470395

Beginning Microsoft SQL Server 2012 Programming, Paul Atkinson, Robert Vieira Publisher: John Wiley & Sons, Inc., 2012 ISBN: ISBN-10:1118102282; ISBN-13: 978-1118102282

||

Prerequisites / Skills Needed

Prerequisites:

  • DBDA.X415: Relational Database Design and SQL Programming
Spring
Data Modeling, Introduction
DBDA.X421
$910 (Estimated Cost)
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter

3. Electives: Artificial Intelligence

Introduction to Machine Learning
AISV.X400
$980
You may enroll in this offering at any time.
Xi "Bill" Chen
Xi "Bill" Chen
Apr. 8 - Jun. 10, Wed, 6:00pm - 9:00pm
  • Flexible Attend in person or via Zoom at scheduled times.
AISV.X400.(45)
Schedule
Date Start Time End Time Meeting Type Location
Wed, 04-08-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 04-15-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 04-22-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 04-29-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 05-06-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 05-13-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 05-20-2026 6:00pm 9:00pm Flexible SANTA CLARA / REMOTE
Wed, 05-27-2026 6:00pm 9:00pm Live-Online REMOTE
Wed, 06-03-2026 6:00pm 9:00pm Live-Online REMOTE
Wed, 06-10-2026 6:00pm 9:00pm Live-Online REMOTE
 

3/16/26: Course format change for last three sessions. See full schedule for details.

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:

  • DBDA.X427: Python for Machine Learning

Skills Needed:

  • Familiarity with Google Colaboratory and Jupyter Notebooks
  • Reasonably good programming/debugging skills beyond the basic or beginner level
  • Familiarity with Python programming, NumPy, and Pandas
  • Comfortable with basic knowledge of algebra, calculus, probability and statistics
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:

  • DBDA.X427: Python for Machine Learning

Skills Needed:

  • Familiarity with Google Colaboratory and Jupyter Notebooks
  • Reasonably good programming/debugging skills beyond the basic or beginner level
  • Familiarity with Python programming, NumPy, and Pandas
  • Comfortable with basic knowledge of algebra, calculus, probability and statistics
Spring
Summer
Deep Learning and Artificial Intelligence
AISV.X401
$980
You may enroll in this offering at any time.
Xi "Bill" Chen
Xi "Bill" Chen
Apr. 6 - Jun. 15, Mon, 6:30pm - 9:30pm
  • Flexible Attend in person or via Zoom at scheduled times.
AISV.X401.(24)
Schedule
Date Start Time End Time Meeting Type Location
Mon, 04-06-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 04-13-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 04-20-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 04-27-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 05-04-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 05-11-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 05-18-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Mon, 06-01-2026 6:30pm 9:30pm Live-Online REMOTE
Mon, 06-08-2026 6:30pm 9:30pm Live-Online REMOTE
Mon, 06-15-2026 6:30pm 9:30pm Live-Online REMOTE
 

3/16/26: Course format change for last three sessions. See full schedule for details.

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 May 25, 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: Google Colab Notebook - https://research.google.com/colaboratory/faq.html

Recommended Text:
Deep Learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville, MIT Press 2016 ISBN# 978-0262035613. A free e-book is available at http://www.deeplearningbook.org (Links to an external site.)

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Prerequisites / Skills Needed

Prerequisites:

  • AISV.X400: Introduction to Machine Learning
  • DBDA.X427: Python for Machine Learning

Skills Needed:

  • Moderate level of computer programming ability in Python, comfortable with an editor, familiarity with command-line operations on a laptop, and a basic understanding of Machine Learning models.
Spring
Python for Machine Learning
DBDA.X427
$980 (Estimated Cost)
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter

4. Electives: Data Engineering

NoSQL Databases, Introduction
DBDA.X410
$910
You may enroll in this offering at any time.
Jeffrey S Miller
Jeffrey Miller
Apr. 8 - Jun. 24, Wed, 6:30pm - 9:30pm
  • Flexible Attend in person or via Zoom at scheduled times.
DBDA.X410.(22)
Schedule
Date Start Time End Time Meeting Type Location
Wed, 04-08-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-15-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-22-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 04-29-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-06-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-13-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-20-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 05-27-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 06-03-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 06-10-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 06-17-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
Wed, 06-24-2026 6:30pm 9:30pm Flexible SANTA CLARA / REMOTE
 

3/26/26: Course postponed by one week. See full schedule for details.

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.

Per the discretion of the instructor, 3-4 of the classes may be conducted fully remote TBA.

Two "no meetings" TBA. 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.

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Prerequisites / Skills Needed

Skills Needed:

  • You will need experience using a programming language such as Python, Ruby, or Java and the ability to set up open-source software, databases, tools, and development environments on personal computers.
Spring
Hands-On Data Engineering
DBDA.X424
$960 (Estimated Cost)
Currently no classes scheduled. Would you like to be notified when a class is available?
Winter
MySQL and Oracle Database for Developers and Designers
DBDA.X409
$740 (Estimated Cost)
Currently no classes scheduled. Would you like to be notified when a class is available?
Fall
The Internet of Things: Big Data Processing and Analytics
EMBD.X412
$910 (Estimated Cost)
Currently no classes scheduled. Would you like to be notified when a class is available?
Spring

5. Completion Review:

Data Science and Data Analytics Certificate Completion Fee
O-CE0122
$95
You may enroll in this offering at any time.
Apr. 1, , All Day
O-CE0122.(018)
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

You may take one elective outside the certificate curriculum, if you receive prior approval from the Academic Services Department.

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.

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Establish Candidacy

1. Complete a Course

Complete at least one course in your selected program.

2. Declare Candidacy

Declaring candidacy is free. Click “Enroll” and follow the steps to submit your application online.

3. Complete Requirements

You must establish candidacy in the certificate program before enrolling in the Certificate Completion Review.

Instructors

Hemil N Patel
Hemil Patel
Principal Engineer, CDK Global
Hinkmond Wong
Hinkmond Wong
Principal Software Engineer
Jeffrey S Miller
Jeffrey Miller
Cloud Developer (AWS), Lead Programmer, Stealth Mode Startup
Michelle C Rosenaur
Michelle Rosenaur
Technology Trainer
Partha Padmanabhan, Instructor and Chair of the Data Science and Data Analysis Certificate Program
Parthasarathy Padmanabhan
Principal Software Engineer, New Relic | Program Chair
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Ravikumar Nandagopalan
Enterprise Data Architect/Senior Consultant, Cisco
Ruth A Arthur-Asmah
Ruth Arthur-Asmah
Director of Analytics and Data Services, American University
Sara Saatchi is an instructor for UCSC Extension Technology Courses.
Sara Saatchi
Professor
Shashidhar Sathyanarayana
Shashidhar Sathyanarayana
Founder and CEO, Numeric Insight | Machine Learning Specialist
Sivakumar Mallari
Sivakumar Mallari
Principle Data Architect, Infoblox
Venkat R Mavram
Venkat Mavram
Director of Engineering
Venkata Duvvuri
Venkata Duvvuri
Principal Cloud AI Architect, IBM Corp.
Xi "Bill" Chen
Xi "Bill" Chen
Senior Software Engineer, Meta
Zara Hajihashemi
Zara Hajihashemi
Founder and CEO, Cybele Health

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

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