Graduate Certificate Programs in Data Science

Harvard's Data Science Certificate program prepares students with the necessary knowledge base and useful skills to tackle real-world data analysis challenges. The program covers concepts such as probability, inference, regression, and machine learning and helps students to develop an essential skill set that includes R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with Unix/Linux, version control with git and GitHub, and reproducible document preparation with RStudio.

The Professional Certificate in Applied Data Science from the Thayer School of Engineering at Dartmouth positions professionals to take full advantage of this trend. Upon completing this program, students will be ready to take advantage of new opportunities and face new challenges in the field of Data Science.

This program is for the career Launchers, with a background in STEM, wanting to enter an exciting, evolving field with a foundation that ensures flexibility as new platforms and technologies emerge. Titles may include business analyst, financial analyst, software engineer, data analyst, and associates; Career Builders, aiming to build on their existing skills in data science in a technical capacity. Titles may include technical roles across fields and industries; Career Switchers, moving from a non-technical job function, seeking new ways to expand opportunities, engage in continuous learning, and increase their earning potential in a high-demand field. Titles may include non-technical professionals at the junior management or early executive level in a business function such as general management, sales, marketing, administration or human resources banking & financial services, consulting, operations, and information technology. Additional data analysis and technical problem-solving education may be required to be eligible for analyst roles.

In just six months, you will become skilled in the fundamentals of data science, mastering critical concepts using Python. By receiving one-on-one support from a mentor who is an expert in the industry, you will be prepared to accelerate your career as a data scientist.

This certificate program is designed for individuals who want a hands-on introduction to data mining applications. This seven-week program will introduce participants to the basic methods of machine learning and big data. This program utilizes asynchronous eLearning combined with live meetings with the professors and other students. Students will build a practical understanding of machine learning techniques through a hands-on approach. Participants will learn new analytical techniques to generate powerful insights that can be implemented immediately in their workplace.

In this certificate program, you will develop an understanding of the data science process and the vocabulary of data science, explore the what and why behind machine learning and AI, gain hands-on experience with the technologies and techniques used by data scientists, develop an executive understanding of data science capabilities and limitations, develop an understanding of how machine learning techniques can aid process improvement and planning, and develop an understanding of Monte Carlo simulations and how they can be applied to process improvement.

The Certification of Professional Achievement in Data Sciences prepares students to expand their career prospects or change career paths by developing foundational data science skills. Individuals looking to strengthen their career prospects or make a career change by developing in-depth expertise in data science would benefit from this program.

The Graduate Certificate in Applied Data Science introduces the tools, methods, and conceptual approaches used to support modern data analysis and decision-making in professional and applied research settings. It exposes students to the challenges of working with data (e.g., asking a good question, inference and causality, decision-making) as well as to the new tools and techniques for data analytics (machine learning, data mining, and more).

The certificate is particularly designed to meet the needs of the graduate students in Berkeley’s professional schools — both professional master’s students and doctoral students — as well as graduate students in the social sciences and the arts & humanities.

The need for expertise in data analytics continues to grow in all organizations and disciplines. Graduate students in every field are now working with data from new sources: websites, electronic medical records, transaction records, sensor networks, smart phones, and digitized records and documents. The analytical tools and methods traditionally used to derive insights from structured and well-curated data sets (census, surveys, and administrative data) are not sufficient for this new, unstructured and often user-generated data.

The Graduate Certificate in Applied Data Science provides hands-on practice working with unstructured and user-generated data to identify new ways to inform decision-making. The curriculum educates professionals and scholars to be intelligent consumers of data science techniques in a variety of domains, with a foundation of skills for applying these techniques in their own domains.

The Certificate in Data Science from Georgetown University equips students with the technological and analytical skills needed to capture, clean, model, and present data. As a student, they can develop and present data analytics, statistical models, and visualizations using the Python programming language and industry standard software. Students will develop their listening skills and learn data presentation techniques in the class.

The overarching goal of the Graduate Data Science Certificate Program is to train a cadre of skillful data scientists with significant multidisciplinary knowledge, broad analytical skills and agile technological abilities. The program emphasizes the practice of modeling using modern technology to handle large, incongruent, and heterogeneous collections of data. The Graduate Certificate for Data Science is approved by the Rackham School for Graduate Studies.

The program provides interactive data-centered training and involves 9 credits of courses and 3 credits of experiential training that require a written report on data analytics. MIDAS faculty from different disciplines provide mentorship and advising and the Institute offers merit-based top-off scholarships for graduate students enrolled in the certificate program. The Graduate Data Science Certificate Program is open for enrollment on a rolling basis. U-M graduate students from any field are eligible to enroll. Minority and underrepresented students are strongly encouraged to enroll and complete the program.

Students are encouraged to take classes outside the student’s core degree program/department. Completion of the program is expected in 2-4 semesters.

Graduate students interested in enrolling in the MIDAS Data Science Graduate Certificate Program are encouraged to review the Prerequisites and complete the Graduate Data Science Readiness Self-Assessment Pretest. Please note that your first semester grades must be posted before applying for this certificate.

The Graduate Data Science Certificate Program is only open to U-M students currently enrolled in a graduate degree-granting program.

The School of Information and Library Science (SILS) is offering a Certificate in Applied Data Science (CADS) to Geography Majors and Minors and students from four other departments. The Certificate is an opportunity to continue building your data science qualifications and apply them in a ‘practicum’ to wrap up the certificate requirements. This CADS is a way to demonstrate the applied significance of your geography credentials.

The program is for students who are not in computer science or other majors that are exclusively focused in this realm, and as a result, fills skill-building and professional development niches for geographers who are already developing data science skills and applying them to real world issues.

The Wake Forest University Certificate in Data Science (DS) program seeks to train and mentor students to become well qualified scientists and researchers. The certificate provides training in algorithms for structured and unstructured datasets, as well as statistical modeling techniques for such datasets. Students will study the theory and application of databases, data processing, data mining, statistical modeling and statistical learning.

Students who successfully complete the DS Certificate Program will receive a certificate in Data Science, as well as a degree in any other graduate programs in which they matriculate. The Certificate Program is implemented by collaboration among the programs of Computer Science and Mathematics & Statistics at Wake Forest University.

To indicate interest in this program, please complete the form linked here. One of the faculty members involved in the DS Certificate Program will reach out to you regarding the program. The current co-directors of the program are Dr. Sam Cho (Department of Computer Science) and Dr. Rob Erhardt (Department of Mathematics and Statistics).

Students must take 15 credits of data science courses, with two courses selected from the area of Statistical Modeling and Statistical Learning, two courses selected from the area of Computational Data Science, and one course from a set of defined electives. The courses falling into each area are described in Course Requirements.

The DS Co-Directors are tasked with approving a student’s plan of coursework. Students enrolled in the Interdisciplinary Graduate DS Certificate Program as well as another graduate program must complete all graduate degree requirements in the individual department to which they were admitted. Courses from the areas of Statistical Modeling and Statistical Learning and Computational Data Science taken from outside a student’s home department do not count towards both the DS certificate and the home degree program.

The advanced certificate in data science is a multidisciplinary, cross-departmental, graduate credential administered by the University of Rochester’s Goergen Institute of Data Science, and approved by the New York State Board of Education. The advanced certificate program prepares students to apply data science techniques, including machine learning, to derive insights from large data sets in various application domains.

The program is designed for individuals with working knowledge of data science, gained through industry or academic experience, who would like to formalize their training with a deeper mastery of fundamental concepts in the field.

The Advanced Certificate in Data Science program is 16 credits, or the equivalent of four, graduate level courses. The program can be completed in two to four semesters of part-time study. Courses are currently offered in the fall and spring semesters during the day, and attendance is required. At this time, we do not offer courses in the evenings or over the summer.

There are three different course plans designed to suit each student’s unique background and level of preparation.

Students are permitted to take one course as an unmatriculated student and use it toward the advanced certificate. Courses MUST be at the graduate (400) level and not undergraduate (200) level. Students interested in transferring credits earned from the advanced certificate to the Master of Science (MS) in data science program should contact the program advisor at [email protected].