SDSU’s Data Science Post-Baccalaureate Certificate program is designed for data science professionals who want to acquire the advanced skills needed for a career transition or a graduate-level data science degree program. This post-baccalaureate program consists of four fully-online graduate-level courses that focus on a range of data science topics, including mathematical statistics, database management, machine learning, advanced analytics, and more. You’ll also learn how to use multiple various computer software packages throughout the courses.

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Prepare for a career in a rapidly-growing field by earning your Data Science Post-Baccalaureate Certificate from SDSU Global Campus.

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About the program

SDSU’s Advanced Certificate in Data Science program is designed for data science professionals who want to acquire the advanced skills needed for a career transition or a graduate-level data science degree program. This graduate program consists of four fully-online graduate-level courses that focus on a range of data science topics, including mathematical statistics, database management, machine learning, advanced analytics, and more. You’ll also learn how to use various computer software packages throughout the courses.

Estimated CostTotal Estimated Cost
$10,092
Completion Time Completion Time
10 Months
Course Format Course Format
Online

The program is fully online, which makes it ideal for working professionals and busy students who want to further their career without putting their professional life on hold. You’ll learn alongside data science professionals from diverse backgrounds and perspectives — which means that you’re joining a vibrant academic community where you can form meaningful professional connections and network across a range of career fields and organizations.

Whether your goal is career development or a graduate degree, earning your Advanced Certificate in Data Science from San Diego State University will help you get there.

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Is This Program Right for Me?

The rapid rise of Big Data and the data economy has created a job market for data scientists that’s projected to grow by nearly 20% over the next decade. San Diego State University has designed this graduate-level program to meet the growing demand for highly-educated data science professionals. The intensive online curriculum will give you the competitive edge you need to stand out in a rapidly-growing, highly-lucrative job market.

Data scientists can find employment with businesses and organizations throughout the private sector. Data science professionals help to compile datasets, conduct research and analyze data, and distill information that help businesses develop a deeper understanding of consumer and market trends. In the public sector, data scientists work with local, state, and federal government agencies to analyze data that will inform and influence policy-making decisions, including public health policies, budgets, climate science, and more.

This graduate-level data science program is made for working professionals and busy students who hold a bachelor’s degree in a quantitative field, as well as undergraduate students who have completed some upper division coursework in quantitative and/or upper division math and statistics.

The entire curriculum consists of graduate-level courses taught by expert SDSU faculty and lecturers, which means that you’ll be well-prepared for graduate studies in data science.

What can I learn?

SDSU’s Advanced Certificate in Data Science program has an industry-relevant curriculum that will prepare you for graduate school and career opportunities. You’ll develop graduate-level skills that will help you stand out in a crowded job market by focusing on statistical modeling, data management, machine learning, and data analysis. You’ll also focus on using different software packages — for example, you’ll use SAS SQL for database management, fit generalized linear and nonlinear models using R, and apply machine learning methods using R or Python.

Online course topics include:

  1. Probability concepts and models
  2. Sampling distributions
  3. Fitting probability distributions
  4. Properties of statistical estimators and inferences
  5. SQL
  6. Data visualization
  7. Regression analyses
  8. Nonlinear models
  9. Support vector machines
  10. Neural nets
  11. Data display/analysis using software packages such as SAS, R, and Python
  12. Time series
  13. Spatial models

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Career Outcomes

Labor Analysis
Data Scientist — Nationwide

Job Postings
Job Postings
Last 12 months
39,539

Projected Growth
Projected Growth
Over 10 years
+19%

Salary Range
Salary Range
Average
$84,000-$142,000


Source: BLS & Burning Glass Technologies, 2020

Job Postings

Professional, Scientific, and Technical Services

7,241

Finance and Insurance

5,167

Manufacturing

2,877

Information

2,709

CATEORY_TITLE

DATA_NUMBER

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Top Employers

  • IBM
  • Amazon
  • Humana
  • Anthem Blue Cross
  • Booz Allen Hamilton Inc.
  • Deloitte
  • Facebook
  • Capital One
  • Microsoft Corporation
  • Johnson & Johnson

With the rapid growth of data- and knowledge-driven economies across the globe, the employment outlook for data scientists is bright. Across the nation, there were nearly 40,000 job postings seeking data scientists in 2020. Those numbers are expected to grow by 19% over the next decade — 22% in California alone.

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Salaries for data science professionals can be significant. According to the Bureau of Labor Statistics, the median annual salary for data scientists is currently $119,000. For those with a bachelor’s degree, the average annual salary is $116,000; for data scientists with a master’s degree, the average annual salary is $123,000 per year. Data scientists with more than 6 years of experience can expect to earn an average annual salary of $127,000 per year; those with more than 9 years of experience earn an average salary of more than $130,000 per year.

Why Should You Choose Us?

Accessibility

All courses are 100% online and accessible from anywhere in the world. In just 10 months, you can earn a graduate-level certificate that will help you boost your résumé, prepare for graduate school, and help you become a stronger data science professional.

Timely Course Topics

As more industries join the Big Data Revolution, the field of data science continues to evolve to meet the challenges of a rapidly-growing industry. With the help of our highly-experienced faculty, we’ve developed timely online courses that focus on building the in-demand skills that employers are looking for.

Reputation

San Diego State University has a reputation for excellence in the academic world. As a top-100 public university, we’re proud of the achievements of our nearly 400,000+ alumni, who have helped us become recognized as the school with the No. 1 Graduate Rate Performance in the country, based on the U.S. News & World Report’s most recent college rankings.

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Start the Program This Summer!

Planning on applying for a fall 2022 start? You can take one course in summer 2022 before your first semester begins! Please contact us for more information.


In order to earn your Advanced Certificate in Data Science, you’ll need to complete the following four courses:

  • STAT 596: Mathematical Statistics for Data Science (3 Units)
    The Mathematical Statistics for Data Science course introduces core principles and mathematical underpinnings of statistical inference in data science applications. Topics discussed in this course include probability concepts, properties of probability models, sampling distributions, central limit theorems, fitting probability distributions, properties of statistical estimators and inferences, evaluating statistical models. Executives and decision-makers have access to more statistical data than ever before, but deriving meaning and actionable insights from that data requires specialized knowledge and expertise in data science.
  • STAT 656: Database Management and Predictions (3 Units)
    The Database Management and Predictions course introduces concepts like database creation and management for a constantly evolving data science world. Topics that are taught during this course include SQL, regression analyses, and classifications. This course provides students with the expertise needed to effectively manage databases in real-world applications in a number of related data science fields.
  • STAT 657: Statistical and Machine Learning Methods (3 Units)
    Machine learning is a branch of artificial intelligence and data science that teaches systems the ability to independently and continuously learn and improve from experience. Modern statistical and machine learning methods taught in this course will highlight the fundamentals of complex algorithms used for data mining. Topics presented in this machine learning course include model selection and regularization, generalized additive models, support vector machines, and neural nets.
  • STAT 658: Advanced Data Analytics (3 Units)
    The Advanced Data Analytics course gives students the skills needed to design predictive data models and make informed data-driven decisions in the data science field. Learn advanced methods and theory for data analysis techniques and applications that are useful in any industry. The technique areas include generalized linear models, nonlinear models for regression, time series, and spatial models.

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Out-of-State Applicants
While we welcome out-of-state students, SDSU Global Campus currently cannot accept applications from students residing in the specific states. Please check back often, as this list of approved states does change. View the list of authorized states here.

Admission Requirements

This program is open to all students who have completed a bachelor’s degree in data science or a related field. In addition, you should have completed Calculus II with a grade of C or better, as well as proficiency in English.

If you’re an undergraduate student who has completed some upper division coursework in quantitative and/or upper division math and statistics, you may register for courses on an individual basis. Please contact us for more information.

For more details on admission requirements, please fill out the interest form below. One of our Admission Advisors will contact you with more information.

Application Instructions

To apply for our program, please complete an application through Cal State Apply.

A $70 nonrefundable application fee is required of all applicants at the time of application. Admission decisions are initially based on self-reported information provided via Cal State Apply. You must provide complete and accurate information on your application. Any misreporting will jeopardize an admission offer.

Please do not send your official transcripts unless you are offered admission.

Electronic transcripts are highly encouraged. Please ensure that you indicate this preference when making your request. If you are required to provide an email address to send the secure online document to SDSU, please use transcriptsforsdsu@sdsu.edu.

For more detailed admission requirements and other application information, please consult our Transfer Admissions Information.

Financial Aid

This program is approved for financial aid. To begin the financial aid process, visit SDSU’s Financial Aid webpage. There, you'll be able to access the Free Application for Federal Student Aid (FAFSA).

If you have any questions regarding the financial aid process, please call the Office of Financial Aid and Scholarships on weekdays from 10 am–3 pm at (619) 594-6323.

We encourage you to apply for financial aid as soon as possible.

Program Cost

  Unit Cost Program Unit Range* Cost
Tuition $780 12 $9,360
Fees
Associated Students $19 12 $228
Technology $21 12 $252
Student Engagement $21 12 $252
Total Estimated Costs $841   $10,092

* Everyone is unique. Your admissions advisor will work with you to determine the right path that suits your needs.

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Contact Information

Courses

2022 Spring2022 Summer2022 Fall2023 Winter
STAT 0596 Mathematical Statistics for Data Science
The Mathematical Statistics for Data Science course introduces core principles and mathematical underpinnings of statistical inference in data science applications. Topics discussed in this course include probability concepts, properties of probability models, sampling distributions, limit theorems, fitting probability distributions, properties of statistical estimators and inferences, evaluating statistical models. Executives and decision-makers have access to more statistical data than ever before, but deriving meaning and actionable insights from that data requires specialized knowledge and expertise in data science.
Course Date(s)

Register
Instructors
Richard Levine
STAT 0656 Database Management and Predictions
Database management and predictions in data science. SQL, regression analyses and diagnostics, discriminant analyses and classifications, missing imputations.
Course Date(s)

Register
Instructors
Chi-Dean Lin