The Data Science and AI Academy is the first of several NC State Academies, which are true university-wide efforts involving all 10 colleges. The Data Science and AI Academy's goal is to network and catalyze data science across all three pillars of the university's land-grant mission: education, research and service to the state of North Carolina. At NC State, data science is for everyone.
The Data Science and AI Academy offers 1-credit project-based courses and customized non-credit courses on a variety of topics grounded in our
ADAPT course model (All Campus Data Science Accessible Project-based Teaching and Learning). We seek instructors from industry, government and academia who are excited about broadening participation in data science and welcoming learners from many disciplines.
Our courses attract faculty and staff from across the university as well as learners outside of the university. Instructors will join a professional teaching community that meets twice monthly to discuss data science teaching and learning research and practice.
Data at Work and AI at Work courses are developed and include consultation with the client. They have minimal lecturing and address problems, tasks and challenges from the clients work environment, using the same, simulated or adjacent data as that found in the workplace. Learners engage in practice and/or projects relevant to their daily work. Data at Work and AI at Work (not-for-credit) courses have a customized schedule.
The successful candidate(s) will develop and teach customized, active, hands-on, project-based non-credit courses in Data Science and AI.
Examples of Past Data at Work and AI at Work Courses:
- A Hands on Introduction to AI and Machine Learning,
- Exploration of AI Uses in Human Resources,
- Data at Work for Extension Agents,
- Data Science Bootcamp for Incoming Graduate Students.
- Advanced Excel and Power BI for government employees
Appointments will be for on a contract basis with the possibility of renewal.
Note that this position is only for teaching on a temporary and part-time basis. |