2024 NCDS Spring Career Panel: Analyzing Data Science Careers | March 5 at 5 PM ET
Early career professionals and students won’t want to miss these data science professionals provide insight into what it takes to capture the attention of top recruiters in data science and data analytics. Our panelists represent a variety of career stages and they are ready to discuss what it takes to set yourself apart as you launch your career search. Join us to learn more about:
- What programming languages are in demand now
- Unexpected ways to promote your experience
- What experiences you should gain early in your career
The free, virtual career panel will feature Paige Spell (Elder Research), Melinda Thielbar (Fidelity Investments), Rachini Moosavi (UNC Health), and Adam Cottrell (SAS). Registrants will receive a link to the recording following the event.
Those interested in the event can register directly at this link: https://bit.ly/NCDS_CareerPanel_Spring2024.
Data Matters: Spring Ahead | March 11 - 15
Data Matters: Spring Ahead is a week-long series of one and two-day courses aimed at students and professionals in business, research, and government. Courses include: Intermediate Python, Basics in R for Data Science and Statistics, Overview to AI and Deep Learning, Intermediate Data Visualization, Deep Learning in Python, and Introduction to Programming in R. The short course series is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI.
Those interested in the event can register directly at this link: https://datamatters.org/registration/.
DataBytes: Supporting AI Risk Management in the Analytics Lifecycle | April 30 at 3:30 PM ET
The National Institute of Standards and Technology (NIST) released an AI Risk Management Framework for trustworthy and responsible use of AI and analytics. NIST offers a portfolio of measurements, standards, and legal metrology to provide recommendations that ensure traceability, enable quality assurance, and harmonize documentary standards and regulatory practices. Their framework is very detailed with recommendations across four functions: govern, map, measure, and manage.
Join Sophia Rowland, a Senior Product Manager focusing on ModelOps and MLOps at SAS, walks us through incorporating these recommendations into the analytics lifecycle. Attendees to this session will gain a greater understanding of trustworthy AI best practices as well as user roles and expectations for building responsible analytics. Registrants will receive a link to the recording following the event.
Those interested in the event can register directly at this link: https://bit.ly/NCDS_DataBytes_April2024.