Public Interest Technology Certificate (PITC)

We are pleased to offer the PITC to government leaders to help them gain expertise in data management, digital innovation, and AI leadership. The Foundations for Evidence-Based Policymaking Act mandates federal agency data be accessible and requires agencies to develop statistical evidence to support policymaking. The PITC program will empower government leaders to improve their agencies and better serve constituents while also fulfilling this mandate. Jacqueline Speedy, Associate Dean, School of Public Policy and Management at Heinz College

• Cohort 1 (Summer 2022) Dates & Schedule

  Virtual Orientation: 1:00 - 4:30pm ET
  August 5, 2022

  Data Management Certificate
  Virtual Modules: 1:00 - 4:30pm ET
  (Note: all virtual class dates are Fridays)
  August 12, 19 (2022)
  September 9, 23 (2022)

  Digital Innovation Certificate
  Virtual Modules: 1:00 - 4:30pm ET
  (Note: all virtual class dates are Fridays)
  October 14, 21 (2022)
  November 3, 18 (2022)

  AI Leadership Certificate
  Virtual Modules: 1:00 - 4:30pm ET
  (Note: all virtual class dates are Fridays)
  December 2, 9 (2022)
  January 6, 20 (2023)

  Final Presentations: 
  February 3, 2023

  Please note: Students must complete all modules in sequence.

• Class Location

  All PITC Program deliveries will be virtual for Cohort 1; the November 3 session will be offered virtually with an optional in-person delivery in Washington, D.C., if possible, in accordance with public health guidance. Students will not be required to travel to complete the program.

• Program Costs
  • $10,500 for the entire program
  • $9,000 discounted rate for Carnegie Mellon alumni—including CIO, CISO, CRO, CDataO, and CDigitalO programs—CMU CyLab Partners, U.S. government employees, veterans, and employees of non-profit organizations
  • Fee includes all program materials
  • Optional credit card installment payment plan is available

  Please note: Due to the non-credit bearing nature of the PIT Certificate Program, students are unable to apply for tuition assistance, scholarship, or VA benefits.

  CANCELLATION/REFUND POLICY

  A non-refundable, non-transferable deposit of 1/6 of the total program cost is required to reserve a seat in the program.

  Should a student withdraw from the program after the deposit has been paid but prior to the program start date, students may have 5/6 of the program costs either refunded to them or transferred to the following cohort of the program.

  After the program start date, no refunds will be issued. However, under extenuating circumstances and with program director approval, students may petition to postpone their attendance to a future cohort and have 5/6 of the program costs applied accordingly.

• Deadlines

  Formal deadline for Cohort 1 is July 29, 2022. Please submit your application as soon as possible for consideration.

  If space remains in the cohort after the deadline, we will continue to accept applications on a first-come, first-served basis.

  Apply Now

• Foundations of Enterprise Data Management

  This module will set the stage for the Data Management Certificate, reviewing the core components of an enterprise data management program.

  This module will also review the necessary components of the data lifecycle management process and will end with a discussion on how to develop a data-driven decision-making culture in an organization.

• Data Strategy and Governance

  This module will focus on data governance best practices and how data leaders integrate effectively into organizational governance and operations.

  This module will also discuss the business case for enterprise data management through the development of a mission-aligned, data-driven strategic roadmap.

• Data Analytics for Public Policy

  Data is increasingly important for organizations to identify new markets, products, and services, streamline processes, and create unique consumer experiences. How do organizations build a culture focusing on data collection, exploration, and analysis?

  In this module, participants will have a chance to gain and solidify knowledge of the most important contemporary methods of analytics, develop an understanding of practical applicability, formulate analytic tasks in support of business objectives, and define successful projects.

• Data Visualization + Implementation Workshop

  This module will focus on best practices for data visualization, which include the evolution of data reporting and visualization, the elements of a good BI dashboard, goals of visualization, and the relationship between the information to be communicated and different types of visualizations.

  This module will also discuss effective ways to communicate data management-related organizational goals  to your executive team via well-crafted stories.

• Public Sector Digital Transformation

  Digital drives new efficiencies and new modes of work, and creates data to develop new experiences, products, and services. If not introduced effectively, it also opens up an organization to issues associated with culture, security, and privacy.

  This module will discuss the key issues that digital leaders will face when transforming their organization to open new opportunities.

• Emerging Tech and Innovation

  This module will focus on how a public interest technologist can assess the pros and cons associated with emerging technologies, develop strategy, and implement disruptive technologies for business advantage.

• Strategy and Change Management

  Organizational change occurs in many forms from minor transitions to transformations and upheavals. Effectively managing change involves different activities depending on the scope of change and the organization's readiness for it. Special attention will be given to managing disruptions from transitions and inevitable losses that change brings.

  This module will inform and discuss ways in which leaders can develop a data-driven transformation culture and become change leaders to enhance the competitive advantage of their organization.

• Human Centered Design + Implementation Workshop

  Design thinking is a user-centered, collaborative process used to identify problems and the definition of innovative solutions. Design thinking can be applied to developing new products, solving for societal challenges, creating new business models, and improving existing processes.

  This module will work to improve the design thinking skills of leaders to advance digital initiatives.

• Demystifying AI

  This module provides data leaders with a practical guide to using AI in the near future. Beginning with an overview of AI technologies and what they can and cannot do, this module will cover frameworks for human-AI collaboration and will outline how these systems are planned, executed, and deployed in the enterprise. We will provide tips for finding, organizing, and retaining AI talent and will conclude with advice for creating an enterprise AI strategy.

  The module will include time to discuss problems presented by students that might be addressable by AI.

• Data Science for Good

  Since the start of the big data, data science, and artificial intelligence movements, many data scientists have been motivated to apply these data collection advancements and their skills with complex algorithms to solve important problems with significant societal impact.

  This module will discuss how leaders can work with their data science colleagues to leverage this technology to achieve a more equitable world.

• Managing AI Projects

  With the growing demand for data science and AI skills, there are many options for students to learn the fundamentals of data and analytics modeling. There are fewer opportunities to learn how to manage these projects, which often involve leading teams with diverse skills and interacting with stakeholders in a variety of roles.

  This module offers practical guidance and experience around the process of initiating, delivering, and evaluating AI projects.

• Ethics of AI & Strategy + Implementation Workshop

  As organizations look to automate processes and glean insights from data, how can agencies ensure groups are using and acting on information in an ethical fashion?

  This module will discuss how leaders can assess/mitigate the development of bias within AI, and how to implement an effective AI strategy in the public sector that is inclusive of all constituents.