A poll from Gallup for the Business-Higher Education Forum shows that by 2021, 69 percent of employers expect to give preference to candidates with data science and analytics skills. However, the same report also revealed that only 23 percent of colleges and universities expect to graduate students with those skills in the next few years. That gap may eventually close, but it will take time that businesses don’t have. They’re eager to hire now so they can capitalize on data, with postings for data science positions expected to reach 2.72 million in 2020.
You don’t need to enroll in a four-year college to take advantage of the market for data science skills. Certificate programs can help get you up to speed on the latest data science concepts, techniques and tools. Other programs are designed for seasoned professionals who already have experience or degrees but want to stay on top of industry trends.
Here are 15 professional development certificate programs that can help launch or boost your data science career.
The Advanced Data Science certificate program from Northwestern’s Professional Studies school offers courses that come directly from the school’s master of science in Data Science program. These include analytics management, analytics and modeling, data engineering and artificial intelligence. This is a course designed for those who already have a graduate degree in data science or a similar field and who want to get up to speed on new technologies or trends in the industry.
Prerequisites: A graduate degree in data science, predictive analytics or a similar field. Complete two fundamental courses through Northwestern or have equivalent knowledge and skills.
Tuition: $3,015 per course
Duration: Two to four months on average
The Big Data Certification offered through UC San Diego’s Extension School offers online and in-person courses, workshops and bootcamps. Courses focus on data mining, analyzing special data with GIS, building predictive models, and using machine-learning algorithms. You can opt for a more specialized data certification with the Data Mining for Advanced Analytics or Machine Learning Methods certificates. Others include Python Programming, Business Intelligence Analysis and data science certificates focusing on specific tools and skills like SAS, R and TensorFlow.
Prerequisites: Varies by certification and course
Duration: At least one year; one year and three months is average
Georgetown’s Certificate in Data Science will teach you everything you need to know to collect, clean, model and present data. Students use the Python programming language and get hands-on experience creating and presenting visualizations, predictive models and analytics, which will prepare you for working with data in a business setting. By the end of this program, Georgetown says students will be able to apply the data science pipeline to analytical workflows, use effective programming practices, utilize and query relational and NoSQL databases, find deeper insights in data, create predictive models and create effective visualizations.
Prerequisites: Basic programming experience
Tuition: $7,496 estimated total cost
Location: On campus
Duration: Eight courses over six months
Columbia University offers a certification of professional achievement in data sciences, which is a non-degree part-time program. However, if you complete this certification program, the credits can apply towards a master of science from Columbia. The courses focus on the foundations of data science, including algorithms, probability and statistics, exploratory data analysis and visualization and machine learning. Each course also has its own prerequisites regarding programming, math and science skills, so be sure to check that you have the right background for each individual course.
Prerequisites: Undergraduate degree, prior quantitative and introductory programming coursework
Tuition: $1,936 per credit
Location: Online or on-campus
Duration: 12 credits; most students complete the program within one year and it must be completed within five
The Certificate Program in Data Science from UC Berkeley Extension requires one core course, one programming course, one machine learning course and up to four electives. UC Berkeley Extension promises to help you “gain the skills to perform advanced data wrangling, data mining, statistical modeling and machine learning on data sets that may be very large and complex.” Courses cover the fundamentals of data science, programming with R and Python, data analysis and scientific computing, machine learning with tools like TensorFlow, Spark and R, among other subjects.
Tuition: $5,100 (estimated cost not including course materials or registration fees)
Duration: 10 semester units, about 150 hours of instruction; must be completed within three years
The Stanford Center for Professional Development offers a Data Mining and Applications graduate certificate program. The three-course program covers using statistical methods to extract meaning from large datasets, developing and using predictive models and analytics and how to use strategic decision-making applications. It’s best suited for data scientist, strategy managers, scientific researchers, medical researchers, social sciences researchers, data analysts and consultants and advertising and marketing professionals.
Prerequisites: You’ll need a conferred bachelor’s degree with an undergraduate GPA of 3.5 or better and introductory courses in statistics or probability, linear algebra and computer programming
Tuition: $11,340 – $12,600 (9-10 units)
Duration: One to two years on average; program must be completed within three years
If you prefer to teach yourself on your own time, or if you want to test the waters before investing thousands in tuition, you might be interested in the Data Science A-Z class offered through Udemy. Students get access to step-by-step instructions through data mining, modeling, tableau visualizations and more. It includes 21 hours of on-demand videos, lifetime access to the content and a certificate of completion; there’s also a 30-day money back guarantee if you aren’t satisfied.
Tuition: $199, but currently on sale for $10.99
To earn a data science certificate from the Harvard Extension School, you’ll need to complete and earn at least a B grade in four certification courses within three years. You will choose two electives from a select group, one required data science course from another select group and both an entry-level and advanced-level statistics course. This certification is best for those who already have knowledge of programming — specifically Python — and those looking to pursue graduate credits.
Prerequisites: Prior knowledge in statistics and basic programming, including prior knowledge of Python
Tuition: $11,000 total, on average
Location: Online and in person
Duration: Must be completed within three years
Cornell University offers multiple data science certificates through eCornell, which is the university’s online education department. You can choose from tailored certificates that include business analytics, business statistics, machine learning, data analytics, data analytics 360 and data-driven marketing. Each program has different requirements, but you can take a free pretest for each certification program to see if you have the right experience and background.
Prerequisites: No prerequisites but you can take a pretest for each certification to see if you’re qualified
Tuition: $1,260 – $9,800 depending on the course
Columbia University’s School of Engineering offers a Data Science for Executives certificate program through EdX. It’s geared toward executives who want to learn more about statistical thinking, machine learning and how data will impact businesses in the future. It addresses the unique information that executives need to know as data becomes fundamental in the enterprise. The courses are taught by professors at Columbia University through EdX’s online platform.
Duration: Five weeks per course
The Boston University Certificate in Data Analytics is offered through the Boston University MET. The program includes four courses or 16 credits and can be completed part-time on-campus or online. The courses include foundations of analytics with R, data analysis and visualizations with R, web analytics and mining and data mining. The program covers probability theory, statistical analysis methods and tools, data visualization, data mining theories and techniques, text mining and web mining. You’ll finish with “a solid knowledge of concepts and techniques in data analytics as well as a solid exposure to the methods and tools for data mining and knowledge discovery,” according to BU.
Prerequisites: Bachelor’s degree from a regionally accredited institution and the equivalent to BU’s MET CS 546 course, Introduction to Probability and Statistics.
Tuition: $465 per level 100-599 course; $880 per level 600 courses and above
Location: On-campus or online
Duration: Two months per course
The MicroMasters program in Statistics and Data Science from MIT consists of four online courses that cover the foundations necessary to understand the tools and methods used in data science. You’ll receive hands-on training in data analysis and machine learning, experience with machine learning algorithms and also cover the basics of probability and statistics. The credential can also be applied towards a PhD in Social and Engineering Systems (SES) through the MIT Institute for Data, Systems and Society (IDSS) or it can also help you get ahead on a master’s degree from another university.
Prerequisites: No prerequisites, but it’s recommended that you complete the Multivariable Calculus course on MIT OpenCourseWare before you start the program; you’ll also need proficiency in Python
Tuition: $300 per course and for the capstone exam
Duration: 12-18 months, on average
Stanford’s Center for Professional Development offers a graduate certificate program in Mining Massive Data Sets. It’s a four-course program that focuses on the growing need for businesses to “transform large quantities of information into intelligence that can be used to make smart business decisions,” according to Stanford. It’s best suited to software engineers, statisticians, predictive modelers, market research and analytics professionals and data miners working with large amounts of raw data.
Prerequisites: Knowledge of basic computer science principles and skills, ability to write non-trivial computer programs, understanding of algorithms, data structures, basic probability theory and linear algebra; you’ll also need a conferred bachelor’s degree with an undergraduate GPA of 3.0 or better
Duration: 1-2 years on average; program must be completed within 3 years