Data Science Team Training (DSTT) | Council of State and Territorial Epidemiologists (CSTE)

About The Program

Increasing the data science capacity of the public health workforce is a key component of the Data Modernization initiative (DMI). The Data Science Team Training program is a team-based, on-the job training program to promote data science upskilling at STLT (state, territory, local, tribal) public health agencies. Learners in the 12-month Data Science Team Training (DSTT) program work collaboratively on a project that addresses a current agency need related to DMI.

Program participants will upgrade their skills in data science through didactic instruction in online courses, working on priority projects, peer-to-peer learning, training stipend for professional development, and coaching from subject matter experts. DSTT includes a mix of live, virtual events and asynchronous training resources. Participants will build a set of foundational data science skills and direct their own learning according to their interest and project needs. Through their work on the project component, teams will accelerate real-world progress to address priorities of the data modernization initiative. Participants should anticipate committing 5-8 hours per month to this program, which will be distributed across engaging with course content, working on projects, and collaborating with peers. Participants will also be given year long membership to CSTE during their program year. This comes with access to subcommittees, which can be helpful in finding connections and learning more about the informatics community.

Program Components

Online course content on Coursera
Virtual peer-to-peer learning community
Monthly webinars led by subject matter experts
Project coaching from subject matter experts
Project-based learning

Training stipend that can be used for professional development of the project
Access to subject matter experts for skill coaching and project guidance
Additional sponsored training opportunities

About The Training

Course instruction in data science will be conducted using an online platform, Coursera. DSTT has a self-directed learner approach: CSTE will recommend a set of courses based on data science competencies, but learners are encouraged to pursue specific topics according to their own interests and project needs. The entire library of courses will be available to participants during the 12-month program.

Courses are available on a wide variety of data science topics including data analysis, computation and statistics, machine learning, and data visualization. The Coursera platform also offers a variety of courses on project management, communication, and leadership topics. Coursera has recently added Skillsets. Get the in-demand skills you need to grow professionally. Choose any SkillSet that aligns with your learning goals. Enroll in personalized recommendations from the SkillSet to increase your proficiency level.

Learners in DSTT will spend 2-3 hours per month engaged in scheduled program activities (webinars, meeting with project coaches) and 3-5 hours on project activities or online coursework, depending on individual learning goals and team needs.

Data Science Topics	Courses
Data Analysis	Programming with R and Python Spatial analysis using ArcGIS Using data from open sources and distributed sources
Computation and Statistics	Introduction to structured query language (SQL) SQL for data science Algorithms
Machine Learning	Introduction to Deep Learning Neural Networks TensorFlow
Data Visualization & Communication	Building dashboards to communicate data Using Tableau and Data Visualization software to create compelling communications

Eligibility Criteria

3-5 people per team
At least one health department epidemiologist

Project ready to be implemented
Letter of support from a supervisor

Teams must be based at a state, local, tribal, or territorial health agency. More than one team from an agency may apply. Teams may include partners external to the agency. Please note that federal employees can participate but may not receive funding reimbursement for travel or other expenses including training licenses or fees. Applicants should have a project that is ready to be implemented and aligns with the DMI. Potential projects could fall under the DMI activities of coordinating people and systems, accelerating data for action, and supporting strategic innovation. Ideal projects will align with DMI and address a data science problem at the intersection of epidemiology and public health laboratory data. Teams must provide a letter of support from a supervisor at their agency indicating that learners will have adequate time to participate in all activities needed to successfully complete their project.

Application

The Cohort 6 program year will run October 2025 to September 2026.

Applications for each year are open in late fall. The webinar recording and slides for the Cohort 4 program year are linked below.

Applications will be scored based on applicant interest and commitment, project alignment with DMI priorities, potential for growth in data science skills, project description, and impact on applied epidemiology practice. Applications must be completed for review and consideration. Submission of an application does not guarantee program acceptance. Interested parties can view the application preview below to prepare.

An application preview for past cohorts can be seen here (Data Science Team Training Application).

For questions, please email dstt@cste.org.