Please be sure to read over each track information page and program policies. Participants may only attend ONE session for Spring 2026 Working Connections.
Session I: Fridays, February 13 – March 13, 1PM – 5PM ET.
Session II: Fridays, March 20 – April 17, 1PM – 5PM ET.
The goal of the National IT Innovation Center’s (NITIC) Working Connections professional development is to equip IT faculty at two-year institutions of higher education with the expertise needed to teach their track content in a subsequent semester. This ensures that the most current information reaches their classrooms, either as a stand-alone course or as supplemental material to an existing course.
This 20-hour professional development track supports educators in reimagining teaching, assessment, and curriculum design in response to the rapid integration of artificial intelligence across education and the workforce. The experience is intentionally hands-on, with participants actively using AI tools throughout each session rather than observing demonstrations alone.
Participants develop a clear understanding of foundational AI concepts and explore how large language models function as instructional support tools rather than content shortcuts. Through guided, interactive work with tools such as ChatGPT, Claude, Gemini, NotebookLM, Scribe, and Guidde, educators practice streamlining course design, creating clearer instructional materials, and improving student support in real time.
A central focus of the track is the redesign of assessment practices for an AI-enabled classroom. Participants engage directly in reworking existing assignments into authentic, AI-aware assessments that emphasize critical thinking, process, reflection, and real-world application. By the end of the track, each participant leaves with practical workflows, instructional artifacts, and assessment strategies they can immediately implement in their own courses using primarily free or institutionally accessible AI tools.
By the end of this track, participants will be able to:
None, curiosity and willingness to explore new instructional approaches recommended.
None.
The instructor may provide digital resources, examples, and templates. The instructor may provide optional open-access articles and tool documentation.
Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.
Nancy Miller is an award-winning IT professor, AI-powered teaching leader, and Cisco Networking expert with over 25 years of experience in network management, cybersecurity, and instructional design. A national presenter and certified AI educator, she specializes in helping colleges integrate modern tools like Microsoft PowerApps to streamline workflows, enhance student engagement, and build career-ready skills. Nancy’s work spans AI literacy, automation, and hands-on IT curriculum design, empowering faculty and students across North Carolina and beyond. Her workshops blend real-world practice with practical innovation, giving participants the confidence to design smarter, more efficient learning and administrative solutions.
This track is a five-day, hands-on series for community college instructors who want to integrate modern Python, API-driven data, and AI tools into their existing courses. Participants will work through instructor-provided labs in Google Colab, Excel (via Python add-ins), Streamlit, and Power BI that they can take back and reuse or lightly adapt in their own classes. The emphasis is on practical, low-friction activities that expose students to real-world data, basic AI capabilities, and interactive analytics, while minimizing prep time and infrastructure needs for both faculty and students.
NOTE: This track closely mirrors the content covered in the Summer III 2025 Working Connections offering, “Advanced Data Analytics – Machine Learning with Python, Power BI & Excel.” Participants who completed that 2025 track are encouraged to select a different option, as the material will be largely overlapping.
While not tied to a single certification, this track can support preparation for:
By the end of this track, participants will be able to:
Attendees should:
No required textbook. All materials (notebooks, slides, lab sheets, and example code) will be provided digitally.
Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.
Chris Santo is residential faculty in the Mathematics, Computer Science, and Engineering Division at Scottsdale Community College, part of the Maricopa Community College District, where he teaches courses in Java programming, data structures, data analytics, Tableau, Power BI, and Python for data analytics. He has taught mathematics, computer science, and computer information systems courses across multiple Maricopa colleges, including Glendale, Paradise Valley, Scottsdale, Rio Salado, and Mesa Community College, since 2008.
Chris has more than 30 years of experience in the information technology sector, spanning roles in computer lab management, technical support, systems administration, application development, database programming, systems integration, project management, IT management, and reliability-focused consulting. His work bridges industry and academia, using data analytics and advanced IT solutions to improve enterprise operations while mentoring the next generation of technologists.
He also teaches in the Master of Information Studies program at Trine University and is a Certified Reliability Leader (CRL). Chris is currently pursuing a Ph.D. in Computer Science with a concentration in Artificial Intelligence at the University of Southern Mississippi, and holds an MS in Computer Science (Cybersecurity and Big Data, with distinction) and an MBA from Arizona State University, an MS in Information Sciences and Telecommunications from the University of Pittsburgh, and a BS in Mathematics and Computer Science from PennWest California.
Learn how to use Python’s advanced data structures; explore Python libraries useful for Data Analysis; acquire and clean data with Python tools – LLMs need good, clean data!
N/A.
Students will be able to:
A familiarity with introductory-level Python; basic syntax and simple program structure. Students should create a Google account if they do not already have one. Students should create a GitHub account if they do not already have one.
None.
PC or MAC, fast internet, webcam & microphone.
Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.
Pamela Brauda is a faculty member in the School of Technology at Florida State College at Jacksonville, where she teaches courses in programming, networking, and data science. Pamela is a co-designer of the A.S. in Data Science Technology program at FSCJ, co-principal investigator for the DataTEC project (NSF Grant #1902524 “Meeting Industry Needs through a Two-Year Data Science Technician Education Program”), a faculty co-advisor for the FSCJ STARS Computing Corps, and the proud owner of an autographed copy of “R for Data Science” by Hadley Wickham. Before teaching at FSCJ, Pamela worked as a Metadata Analyst with the Florida Department of Law Enforcement, taught programming and software development at the University of North Florida, created and operated several small businesses, and taught high school mathematics. She graduated from the University of Georgia with a B.S. and from the University of North Florida with an M.S. in Computer Science.
David Singletary is a faculty member in the School of Technology at Florida State College at Jacksonville. He teaches courses in software development, data science, and AI. In a previous life David was employed as a software engineer at Cisco and various startup companies in Silicon Valley. David graduated from the University of Central Florida with a B.S. and from the University of Colorado with an M.S. in Computer Science.
This 20-hour professional development track supports educators in reimagining teaching, assessment, and curriculum design in response to the rapid integration of artificial intelligence across education and the workforce. The experience is intentionally hands-on, with participants actively using AI tools throughout each session rather than observing demonstrations alone.
Participants develop a clear understanding of foundational AI concepts and explore how large language models function as instructional support tools rather than content shortcuts. Through guided, interactive work with tools such as ChatGPT, Claude, Gemini, NotebookLM, Scribe, and Guidde, educators practice streamlining course design, creating clearer instructional materials, and improving student support in real time.
A central focus of the track is the redesign of assessment practices for an AI-enabled classroom. Participants engage directly in reworking existing assignments into authentic, AI-aware assessments that emphasize critical thinking, process, reflection, and real-world application. By the end of the track, each participant leaves with practical workflows, instructional artifacts, and assessment strategies they can immediately implement in their own courses using primarily free or institutionally accessible AI tools.
By the end of this track, participants will be able to:
None, curiosity and willingness to explore new instructional approaches recommended.
None.
The instructor may provide digital resources, examples, and templates. The instructor may provide optional open-access articles and tool documentation.
Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.
Nancy Miller is an award-winning IT professor, AI-powered teaching leader, and Cisco Networking expert with over 25 years of experience in network management, cybersecurity, and instructional design. A national presenter and certified AI educator, she specializes in helping colleges integrate modern tools like Microsoft PowerApps to streamline workflows, enhance student engagement, and build career-ready skills. Nancy’s work spans AI literacy, automation, and hands-on IT curriculum design, empowering faculty and students across North Carolina and beyond. Her workshops blend real-world practice with practical innovation, giving participants the confidence to design smarter, more efficient learning and administrative solutions.
This session introduces faculty to CompTIA Cloud+ certification content and prepares instructors to teach vendor-neutral cloud computing concepts in their courses. Participants will explore cloud architecture, security, deployment, and operations while gaining familiarity with the exam objectives and effective teaching strategies for hands-on cloud labs. Faculty will leave equipped to develop curriculum that prepares students for cloud computing careers and industry certification.
Cloud+ CV0-003
Introductory computer science courses or experience.
None.
CompTIA Cloud+ Guide to Cloud Computing, 2nd Edition, Cengage MindTap, 9798214027531 (can request evaluation access through Cengage)
Instructors will want to request instructor evaluation access to the CompTIA Cloud+ Guide to Cloud Computing eBook with MindTap, 2nd edition from Cengage.
Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.
Dr. Stephanie Wascher is an experienced cybersecurity and IT faculty member with over 20 years of experience teaching networking, cybersecurity, virtualization, and cloud-related technologies in higher education and workforce training environments. She currently serves as Academic Chair and Professor of Computer and Information Systems, where she leads curriculum development, manages secure lab environments, and delivers instruction aligned to industry certifications including CompTIA, Cisco, and VMware. Her background includes extensive hands-on experience with virtualization, Windows Server, networking, and security infrastructures that directly support Cloud+ concepts. Stephanie is also actively engaged in workforce alignment initiatives, grant-funded programs, and industry partnerships, ensuring training remains relevant, practical, and certification-focused.
An introductory, hands-on workshop that equips participants with practical models and Python skills to design, simulate, analyze, and execute quantum circuits across simulators and cloud-based quantum hardware.
AWS Braket–related skill badges
None.
Building Quantum Software With Python: A Developer’s Guide (Manning Publications, 2025).
Please note that content is subject to change or modification based on the unique needs of the track participants in attendance.
David Singletary is a faculty member in the School of Technology at Florida State College at Jacksonville. He teaches courses in software development, data science, and AI. In a previous life David was employed as a software engineer at Cisco and various startup companies in Silicon Valley. David graduated from the University of Central Florida with a B.S. and from the University of Colorado with an M.S. in Computer Science.
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