The National Consortium for Data Science

DataBytes: AI-Powered Development for Research Cyberinfrastructure
2026-06-23 12:00 - 13:00 (America/New_York) | via Zoom
AI coding assistants are reshaping how research software is built and maintained, but most guidance targets industry, not research cyberinfrastructure (CI).
During this webinar, Komal Thareja, a Senior Research Software Engineer at RENCI at the University of North Carolina at Chapel Hill, will fill that gap with hands-on demonstrations tailored to CI roles, using real examples from NSF Major Facility projects. Topics include scaffolding scientific workflows, generating APIs from OpenAPI specs, building publication dashboards, and creating presentation materials. Designed for PIs/managers, developers, and students, the session highlights workflows you can adopt immediately, common AI failure modes, prompt techniques that improve results, and security considerations for using AI with research code. No prior AI experience required.
Key Takeaways for attendees:

Role-specific AI workflows for research CI, drawn from real NSF Major Facility projects
Practical guidance for PIs/managers, developers, and students
What AI gets wrong in research software—and how to recover
Prompt engineering techniques that improve scientific software outcomes
Security best practices for using AI with research code and infrastructure

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Foundations of AI: Deep Dive into Retrieval Augmented Generation (RAG)
2026-05-28 15:00 - 17:00 | via Zoom
This brief course will take what we’ve learned in the Intro to Generative AI (or Accelerated GenAI) course and go deeper in the world of Retrieval Augmented Generation (RAG) systems. You’ll learn to upgrade your RAG with query rewriting, reranking, citation generation, and more sophisticated evaluation tools. We’ll also touch on agentic RAG. You should come out of this class with the tools to make a more sophisticated RAG system. It is strongly suggested to have knowledge of Generative AI and Python coding, NLP is useful but not required.
Prerequisites: Intermediate Python skills, knowledge of generative AI may be useful but is not required.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships to faculty, staff, and students affiliated with nonprofit higher education institutions.

To apply for a full scholarship, complete this Google form.
DO NOT complete the UNC Event Registration form unless our staff asks you to complete it.
Scholarship Recipients will be notified no later than Friday, May 1, 2026.

Foundations of AI: Advanced Generative AI for Coders
2026-05-21 13:00 - 17:00 | via Zoom
This new course will introduce more advanced topics in Generative AI, including a deeper look at some of the tools we touch on in the intro course as well as introducing new topics like agentic AI and the broader aspects of a modern AI workflow. We’ll go over deterministic workflows versus autonomous agents, advanced prompting, schema-constrained outputs, and more to take your generative AI knowledge to the next level and help you get the most out of the power of Generative AI as a coder. After taking this course, you should be able to use and understand Generative AI beyond its use in chatbots. It is strongly recommended to have some knowledge of generative AI, NLP, and Python before taking this course.
Prerequisites: Intermediate Python skills and a basic understanding of generative AI – if you do not have any background in generative AI, you are encouraged to register for the accelerated Intro to Generative AI class offered before this course to get up to speed on the basics.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships to faculty, staff, and students affiliated with nonprofit higher education institutions.

To apply for a full scholarship, complete this Google form.
DO NOT complete the UNC Event Registration form unless our staff asks you to complete it.
Scholarship Recipients will be notified no later than Friday, May 1, 2026.

Foundations of AI: Intro to Generative AI for Coders - Accelerated
2026-05-14 15:00 - 17:00 | via Zoom
This will be an accelerated version of our popular “Intro to Generative AI” course, intended to give an overview of what Generative AI is, how it works from a high level, and how to use basic technical tools to leverage Generative AI.
Those who take this course will have the basic knowledge needed to use LLMs to create useful tools, and will have the understanding behind the technology to improve their prompt engineering skills as well.
This course is ideal for people who are interested in the Advanced Generative AI for Coders and Deep Dive into Retrieval Augmented Generation courses but have not taken classes in the technical basics of generative AI.
Prerequisites: Intermediate Python, some familiarity with AI/Machine Learning is helpful but not required.
Register for the Event
Scholarship Information
NCDS is pleased to offer a limited number of full scholarships to faculty, staff, and students affiliated with nonprofit higher education institutions.

To apply for a full scholarship, complete this Google form.
DO NOT complete the UNC Event Registration form unless you are asked to complete it.
Scholarship Recipients will be notified no later than Friday, May 1, 2026.

DataBytes: An Agentic Operating System for Toxicology
2026-04-22 12:00 - 13:00 | via Zoom
Chemical safety assessment today is slow, costly, and fragmented—held back by siloed data streams and workflows that haven’t kept pace with scientific complexity. While many in the field focus on automating report generation, this webinar introduces a different paradigm: an agentic operating system where AI agents collaborate with toxicologists rather than replace them.
What does “agentic” truly mean beyond the buzz? Through live demonstrations, Thomas Luechtefeld, PhD, CEO and Founder of Insilica, will show how autonomous systems can reason across heterogeneous scientific evidence, surface insights before they’re requested, and accumulate institutional knowledge over time. He’ll explore the architectural and epistemic shift from treating AI as a prediction tool to designing AI as infrastructure—an approach that becomes essential in domains where accuracy directly impacts regulatory decisions and public health.
Attendees will learn:

Why autonomous agents require fundamentally different architecture than traditional machine‑learning pipelines
How AI systems can retain and build on organizational knowledge instead of starting from scratch
What “production‑ready” looks like when outputs must withstand scientific and regulatory scrutiny
A live demonstration of an AI agent reasoning through a toxicology question in real time
The real limitations of current agent architectures—and where the technology still falls short

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Spring 2026 NCDS Virtual Career Panel
2026-02-26 17:00 - 18:00 | via Zoom
Join panelists working in sports analytics, growth equity, and data and AI security as we explore the paths that lead to a career in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there. We’ll also dive into the hard and soft skills that turn a top candidate into the perfect candidate for a role in this competitive field.
Panelists:

Leena Dave – Truist | Senior Vice President, Data Governance Metrics and Reporting
Peter Engler – Seattle Seahawks | Seattle Seahawks Football Research Assistant
Namrata Jumani – Radian Capital | Associate
Zixin Nie – RTI International | Data Privacy Specialist

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DataBytes: Breaking the Georeferencing Bottleneck - How AI is Transforming Natural History Collections
2026-02-18 12:00 - 13:00 | via Zoom
Large language models (LLMs) offer a transformative solution to one of the most persistent challenges facing natural history collections: converting textual locality data from specimen labels into precise geographical coordinates. Traditional georeferencing methods require substantial expertise, time, and financial resources, constraints that have left millions of specimens in museums and herbaria without spatial data. Our standardized testing demonstrates that contemporary LLMs can achieve near-human accuracy in georeferencing tasks while dramatically reducing both processing time and costs. By integrating LLMs into existing digitization workflows, institutions can accelerate the spatial enablement of their collections, unlocking new research opportunities in biodiversity science, climate change studies, and conservation planning. This approach has immediate practical applications for collection managers while advancing the broader goal of making natural history data more accessible and analytically powerful for the research community.

What to expect:

Performance benchmarks and validation: Understand how LLM accuracy compares to traditional georeferencing methods across different specimen types, locality descriptions, and geographic regions, with concrete metrics from standardized testing.
Scalability and resource optimization: Discover how LLMs can dramatically reduce georeferencing bottlenecks, enabling collections to process thousands of specimens at a fraction of the traditional cost and time investment.
Unlocking collection value: See how accelerated georeferencing opens new avenues for research applications, data mobilization initiatives, and cross-institutional data sharing that were previously limited by spatial data gaps.

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LinkedIn Like a Data Scientist: Strategic Networking for the Digital Age
2026-01-27 12:00 - 13:00 | via Zoom
We’re delighted to host Becky Brown once again for an updated session exploring LinkedIn best practices. Becky has held multiple positions at SAS during her decades-long career at the software giant. These days, Brown helps sales leaders leverage digital platforms to build stronger connections and more opportunities. Learn her favorite techniques and tricks of the trade.
About Becky Brown
Becky is a trainer and coach for sales teams wanting to leverage digital platforms like LinkedIn and Sales Navigator to build relationships, uncover opportunities, and create fuller pipelines. She manages a Social Selling certification program and runs global communications for the team.
Becky brings a broad set of experiences from 37 years in sales, marketing and enablement in the technology industry. You can find Becky on LinkedIn and volunteering for the sea turtle patrol in her beloved Emerald Isle, NC.

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DataBytes: Calling all Data Scientists...Introducing ROBOKOP
2025-12-10 12:00 - 13:00 | via Zoom
ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways) is a knowledge graph system that aims to accelerate and advance scientific discovery by enabling users to simultaneously explore dozens of integrated and harmonized sources of biomedical knowledge. ROBOKOP has been applied to suggest mechanistic insights into biomedical questions and hypotheses for subsequent testing across multiple domains, including hepatotoxicity, environmental determinants of disease, drug repurposing and mechanism of action, and others.
During this NCDS webinar, Dr. Karamarie Fecho will provide a short presentation and live demonstration of ROBOKOP, followed by an opportunity for attendees to pose questions to ROBOKOP and explore answers.
After this webinar, attendees will:
● Gain a general understanding of knowledge graphs
● Be aware of the ROBOKOP knowledge graph system and know how to access it
● Have a basic understanding of how to query ROBOKOP and interpret results
Funding
ROBOKOP is funded by NIEHS with joint support from the NIH Office of Data Science (#U24ES035214). Drs. Alexander Tropsha and Chris Bizon, of the University of North Carolina at Chapel Hill, serve as Principal Investigators.
About Dr. Karamarie Fecho
Dr. Fecho holds a PhD degree in Neurobiology from UNC’s School of Medicine. Her scientific background is broad and spans the clinical and translational spectrum, from basic science to clinical research to healthcare quality assurance/improvement and data science.
Kara currently serves as Founder and CEO of Copperline Professional Solutions, which is a small biomedical consulting company that she founded in 2010. Through Copperline, Kara has engaged with numerous academic organizations, pharmaceutical companies, tech start-ups, and non-profits, providing a wide array of services, products, and expertise.
Kara also is a Research Affiliate at RENCI, where in recent years she has been focused on the development and application of biomedical knowledge graphs. This webinar will focus on her work on the ROBOKOP (Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways) knowledge graph system.
REGISTER HERE

DataBytes: Real-World AI Evaluation: Overcoming the AI Assurance Bottleneck
2025-10-30 11:00 - 12:00 | via Zoom
Current AI evaluation methods focus solely on the underlying technology and lack the necessary detail for real-world deployment decisions. Civitaas aims to bridge this gap and accelerate AI market readiness by evaluating the quality, safety, and utility of AI technologies in the real world. We achieve this through real-time user feedback as they interact with AI systems, leading to more meaningful outcomes that enable businesses to leverage AI effectively and responsibly.
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Foundations of AI: Introduction to Deep Learning
2025-10-29 13:00 - 17:00 | via Zoom
In this course you’ll learn about Artificial Intelligence (AI), starting with foundational concepts in machine learning and deep learning, then moving to the basics of Natural Language Processing and Computer Vision that got us to our current boom in Generative AI as demonstrated by GPT-3, DALL-E and other well-known tools. Learn how to train your own AI models, and how to make the most of open-source and pre-trained models on the market.
— How machine learning works
— Basics of deep learning
— Basics of Natural Language Processing
— How to do deep learning with language data
Prereqs: Familiarity with Python is strongly encouraged. Some knowledge of data science and machine learning is useful but not required.
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NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: Introduction to Deep Learning course on Wednesday, Oct. 29 , 2025 from 1 p.m. – 5 p.m. ET.
To apply for a full scholarship, submit your application via this form. DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

2025 NCDS Fall Career Panel: Analyzing Data Science Careers
2025-10-01 18:00 - 19:00 | via Zoom
Join panelists working in a variety of fields, leveraging their knowledge and experience in data science to forge distinct careers in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there. We’ll also dive into the hard and soft skills that make a top candidate the only candidate for a role in this competitive field. Get ready to dive into the following topics:

Do I need a graduate degree to be competitive?
What are three things I should do as an undergrad to make my resume stand out?
HELP! I don’t have a degree in data science!

Moderator: Sarah Egan Warren, Teaching Assistant Professor, Institute for Advanced Analytics and Lead Facilitator, UNC System’s Faculty Learning Community for AI in Teaching & Learning, North Carolina State University
Panelists:

Laura Faircloth, Arabic NLP Scientist, MetaMetrics
Emily Hadley, Security Researcher, Microsoft AI Red Team
Ben Heller, GenAI Transformation Lead, Google Cloud
Vrushali Sawant, Data Scientist, Data Ethics Practice, SAS

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Foundations of AI: Intro to Generative AI for Non-Coders
2025-09-24 13:00 - 17:00 | via Zoom
This four-hour workshop is designed to provide non-technical audiences an understanding of AI, its fundamental concepts, and its practical applications. The course clarifies technical jargon and reveals how everyday people rely on AI in their personal and professional lives.

Attendees will receive big picture explanations of how AI works and will learn about opportunities and risks in the field.
They will leave the course with deeper awareness of AI use in their work environment and a greater technical understanding of how AI drives innovation across sectors.
Attendees will also learn the basics of prompt engineering, with examples on how to get the best outputs from generative AI tools by learning best practices in prompt engineering.

Prerequisites: None! This course is open and encouraged for anyone and everyone.
Register for the Event
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: Intro to Generative AI for Non-Coders on Wednesday, Sept. 24 from 1 p.m. – 5 p.m. ET.
To apply for a full scholarship, submit your application via this form. DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

DataBytes: Introducing the NCATS Biomedical Data Translator: A new tool for Biomedical Data Integration and Inference
2025-08-27 12:00 - 13:00
Speaker: Chris Bizon, Director of Analytics and Data Science, RENCI
Host: Becky Boyles, Deputy Director, RENCI
The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open-source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. To demonstrate Translator’s application and impact, we highlight features of the user interface in the context of three real-world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism.
Key takeaways include the following:

Based on rich concept modeling and deep provenance tracking, we’ll provide an overview of how Translator works.
Opportunities to engage with Translator at http://ui.transltr.io and through our Ambassadors and Champions program.

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Chris Bizon | bizon@renci.org
Chris Bizon is the director of Analytics and Data Science. He leads a team that applies a range of analytical methods including knowledge graphs, machine learning, visual analytics, semantic web-based reasoning, and textual annotation across many domains. He joined RENCI in 2008 as a member of the informatics group, where he worked in the areas of high-throughput sequencing, genomic analysis, and clinical genomics. Prior to joining RENCI, he spent a decade in the private sector working as both a developer and a researcher in the areas of fluid dynamics simulations and the application of machine learning to drug discovery. He holds a BS in Physics from the University of North Carolina at Chapel Hill and a PhD in Physics from the University of Texas at Austin, where he developed numerical models of nonlinear phenomena including pattern formation in oscillated granular media.

DataBytes: The AI Security Gap: How Close Are We to Achieving Trustworthy AI?
2025-06-11 12:00 - 13:30 | via Zoom
Key Findings from the NIST AI 100-2 Report
In this webinar, Apostol Vassilev will examine the recently published 2025 edition of the NIST Al 100-2 report, a crucial resource for organizations seeking to ensure the security of Al systems. The talk will focus on the security of generative Al models, tailored to address the needs of Al practitioners and stakeholders in the audience. The report provides a comprehensive taxonomy of concepts and terminology in the field of adversarial machine learning (AML), organizing key Al technologies, attack life cycle stages, and attacker goals, objectives, capabilities, and knowledge into a conceptual hierarchy. By identifying current security challenges in the Al system life cycle and describing methods for mitigation and management, the report aims to establish a common language for the rapidly evolving AML landscape. This webinar will provide attendees with a deeper understanding of the development and deployment of more trustworthy and responsible Al systems.
Register Here

Foundations of AI: The Basics of Natural Language Processing
2025-05-15 13:00 - 17:00 | via Zoom
In this workshop you’ll learn the basics of Natural Language Processing (NLP): the subfield of AI and data science dedicated to human language.
You’ll also learn:

How to do basic analyses with unstructured text data
How to use deep learning to create NLP models from scratch and finally how
How large language models (LLMs) and Generative AI work and connect to other NLP skills.

We’ll touch on some aspects of deep learning that are specific to NLP, some more basic analyses of unstructured data and how to deal with lots of unlabeled text (e.g. clustering) and basically go deeper on things that are really NLP-related as opposed to AI more generally.
Pre-requisites
Basic Python knowledge required, machine learning knowledge helpful but not required, very basic data science knowledge (i.e. linear regression) is recommended.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: The Basics of Natural Language Processing course on Thursday, May 15, 2025 from 1:00 p.m. – 5:00 p.m. ET.

To apply for a full scholarship, submit your application via this form.
DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

DataBytes: Do Large Language Models Have a Legal Duty to Tell the Truth?
2025-04-24 12:00 - 13:00
Large language models (LLMs) do not distinguish between fact and fiction. They will return an answer to almost any prompt, yet factually incorrect responses are commonplace. Our tendency to anthropomorphise machines and trust models as human-like truth tellers — consuming and spreading the bad information that they produce in the process — is uniquely worrying. They are not, strictly speaking, designed to tell the truth.
Yet they are implemented in many sectors where truth and detail matter such as education, science, health, the media, law, and finance. Our guest presenter Sandra Wachter coined the idea of “careless speech” as a new type of harm created by large language models (LLM) that poses cumulative, long-term risks to science, education, and shared social truth in democratic societies. These subtle mistruths are poised to cumulatively degrade and homogenize knowledge over time.
This begs the question: Do large language models have a legal duty to tell the truth?
Join us as Sandra shows the prevalence of hallucinations, and we assess the existence of truth-related obligations in EU human rights law and the Artificial Intelligence Act, Digital Services Act, Product Liability Directive and Artificial Intelligence Liability Directive. We will close by proposing ideas of how to reduce hallucinations in LLMs and a robust Q & A opportunity.
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Foundations of AI: Intro to Generative AI for Coders
2025-03-20 17:00 - 21:00
This course will give you an overview of what Generative AI is and how it works, and how to do some basic tasks in Generative AI. You’ll learn some tips and tricks for prompt engineering and prompt tuning, as well as more advanced techniques like RAG, fine-tuning and how to evaluate generative model performance. By the end of the course you should have enough knowledge to combine open-source LLMs with a more targeted dataset to efficiently handle AI tasks that are relevant to your work.
Prerequisites
Understanding basic Python and the very basics of data science (i.e., what data looks like in a csv format and how to do a simple linear regression) would be helpful in this class. Understanding machine learning basics is good, but not required.
Register for Course
Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: Intro to Generative AI for Coders course on Thursday, Mar. 20, 2025 from 5:00 p.m. – 9:00 p.m. ET.

To apply for a full scholarship, submit your application via this form.
DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

Foundations of AI: Intro to AI and Deep Learning
2025-02-20 13:00 - 17:00
In this course you’ll learn about Artificial Intelligence (AI), starting with foundational concepts in machine learning and deep learning, then moving to the basics of Natural Language Processing and Computer Vision that got us to our current boom in Generative AI as demonstrated by GPT-3, DALL-E and other well-known tools. Learn how to train your own AI models, and how to make the most of open-source and pre-trained models on the market.

How machine learning works
Basics of deep learning
Basics of Natural Language Processing
How to do deep learning with language data

Prerequisites
Understanding basic Python and the very basics of data science (i.e., what data looks like in a csv format and how to do a simple linear regression) would be helpful in this class. Understanding machine learning basics is good, but not required.
Register for Course
Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: AI for Non Coders course on Thursday, Feb. 20 from 1:00 p.m. – 5:00 p.m. ET.

To apply for a full scholarship, submit your application via this form.
DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

2025 NCDS Spring Career Panel: Analyzing Data Science Careers
2025-02-05 17:00 - 18:00
Join panelists working in a variety of fields, leveraging their knowledge and experience in data science to forge distinct careers in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there. We’ll also dive into the hard and soft skills that make a top candidate the only candidate for a role in this competitive field. Get ready to dive into the following topics:

Do I need a graduate degree to be considered for my dream job?
What are three things I can do to stand out from the competition?
HELP! I don’t have a degree in data science!

Register for the Event

Careers in Data Science: Rock Your LinkedIn Profile with Becky Brown
2025-01-29 12:00 - 13:00 | via Zoom
Your presence on LinkedIn and other social channels is the first impression you make on clients and your network. Creating the right presence is the key to having people “opt-in” to conversations with you. Join this session to learn how to articulate a clear and authentic personal brand, how to define your LinkedIn strategy, and how to build a LinkedIn profile that connects with your target audience so you can make more authentic connections.
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About the Speaker | Becky Brown
Becky Brown brings almost four decades of experience into her work as a coach, trainer, and LinkedIn content creator. Her career spans a blend of sales and marketing roles in the technology field and she currently works to support her colleagues as senior sales enablement program manager at the largest privately-held software company in the role. She focuses on helping professionals find greater fulfillment in work and life by expanding their insights and perspectives through meaningful social connections. Becky earned a Business degree from Meredith College and holds certifications in LinkedIn coaching, social selling, career coaching and professional life coaching.

DataBytes: Intro to NLP, LLMs and more - a Taste of Foundations of AI
2024-12-12 12:00 - 13:00
In this short session you’ll learn the basics of Natural Language Processing, starting with turning words and sentences into embeddings for use in deep learning tasks, as well as an intro to language models, large and otherwise. You’ll learn some hands-on tips and tricks for making sense of language data, and get a technical but beginner-friendly introduction to the wide world of AI with language.
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DataBytes: Navigating the Data Divide: Approaching Analytics Across Organizational Maturity Levels
2024-10-17 12:00 - 13:00
Organizations at varying levels of analytical maturity are increasingly seeking to optimize their data usage. This presentation, delivered by two experienced data scientists, will discuss how analytics can vary across different environments. The speakers will draw on their work with clients across the analytical maturity spectrum, highlighting their efforts to enhance analytically established organizations and develop capabilities in analytically emerging ones. They will examine a range of analytical methodologies and how these can either support or hinder organizational performance. This presentation will focus on how different organizations engage with analytics based on their maturity levels, outlining the specific opportunities and challenges each faces. The goal is to provide attendees with practical insights on how different organizations approach data analytics so that they can be prepared to make analytic contributions at any organization.
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2024 NCDS Fall Career Panel: Analyzing Data Science Careers
2024-10-09 17:00 - 18:00
You don’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.
During our fall event, you’ll join panelists working in data and Al security, human movement analysis in research and clinical labs, and more as they explore the paths that lead to a career in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there and dive into the hard and soft skills that make a top candidate the only candidate for a role in this competitive field.
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Foundations of AI: AI for Non-Coders
2024-09-26 13:00 - 17:00
Ever say to yourself: what even is an LLM? How do I get from chatting with ChatGPT to talking about larger AI products? How do I answer these nonstop questions from colleagues, customers, leadership and more in this new landscape?
Do you find yourself needing expertise on AI that, quite frankly, you didn’t sign up for?
This course is designed to meet the needs of people who are not necessarily well-versed in math and science but who know that they need to know the basics about AI in this changing landscape.
You’ll learn about what AI can accomplish, the intuitions behind how it works (no math or coding necessary!), and opportunities and risks. You’ll come away feeling confident that you know not only what an LLM actually is, but understand all the jargon people use to talk about it.
Register for the Course

Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: AI for Non Coders course on Thursday, Sept. 26 from 1:00 p.m. – 5:00 p.m. ET.
To apply for a full scholarship, submit your application via this form. DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

Scaling Up: Developing a Coordinating Hub for Data Competency
2024-09-17 12:00 - 13:00
In this session, Dr. Crista Arangala will introduce Elon University’s Data Nexus. The Data Nexus initiative was created as part of a five-year Quality Enhancement Plan developed during its most recent accreditation process and serves as a coordinating hub for data competency initiatives at the university throughout the plan and beyond. In its first year, Data Nexus has been focused on assessing foundational technology and statistical competency of all of Elon University’s undergraduate students. Through Data Nexus, Elon University has also created a process for faculty across the institution to apply for courses to be designated as Data-Intensive and has introduced a new Micro-credential in Advanced Data Competency. Data Nexus also offers a variety of programming across campus including data camps, workshops, and data challenges. Data Nexus also offers grants to support faculty, staff, and student data-driven initiatives. In year two, Data Nexus will continue to develop curricular and co-curricular data-intensive experiences for the general Elon University undergraduate student body.
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About Dr. Crista Arangala
Dr. Crista Arangala is the Director of Elon University’s Data Nexus and Professor of Mathematics. The Data Nexus initiative was created as part of a five-year Quality Enhancement Plan developed during its most recent accreditation process and serves as a coordinating hub for data competency initiatives at the university throughout the plan and beyond. Dr. Arangala has a PhD in mathematics from the University of Cincinnati and a Masters in Higher Education from Stony Brook University. She has been at Elon University in North Carolina for 24 years, researching in a variety of fields including inverse problems, applied partial differential equations, applied linear algebra, mathematical modeling, and service-learning education. Dr. Arangala has a special interest in inquirydiscovery learning and ran a traveling science museum with her Elon University students in Kerala, India for 9 years. Dr. Arangala was chosen to be a Fulbright Scholar in 2014 as a visiting lecturer at the University of Colombo where she continued her projects in inquiry learning in Linear Algebra and began working with a modeling team focusing on Dengue fever research. Dr. Arangala has published several textbooks that implores inquiry learning techniques including Exploring Linear Algebra: Labs and Projects with Matlab and Mathematical Modeling: Branching Beyond Calculus. Her latest text, Linear Algebra with Machine Learning and Data, connects her teaching interests of infusing data into the mathematical curriculum and her research interests in applied linear algebra.

Careers in Data Science: Measuring Social Impact at the Kennedy Center
2024-09-11 18:00 - 19:00
From liberal arts major to major impact
What do Musical Theater, Psychology, History, and Business Administration all have in common? These fields can all provide you with successful tools and experiences that can lead to valuable careers incorporating data science. In this session, Trés McMichael, Senior Program Manager for Social Impact Civic Alliances at the Kennedy Center in Washington, D.C., will discuss his pathways from a liberal arts education to a non-profit professional who has incorporated research, evaluation, and data visualization as a tool to support arts, culture, and community change.
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About Trés McMichael
Trés McMichael is a joy-filled arts leader and performer who is passionate about community empowerment, arts education, and social justice. Originally from Baltimore, Trés is an alumnus of Elon University, where he graduated with degrees in Music Theatre (BFA) and Arts Administration (BA). He also holds an MFA in Arts Leadership and a certificate in Fundraising Leadership from Seattle University. While pursuing his graduate degree, he was named an EDI Research Fellow with the Association of Arts Administration Educators. He has worked with various nonprofit and arts organizations such as Arena Stage, DC Collaborative, and the NAACP. Through his work, Trés strives to do work that is in and with, not to or for, the communities he serves.

DataBytes: Data Viz, Chemistry, Art, and Public Health: Making Sense of Street Drugs
2024-08-29 12:00 - 13:00
At the Street Drug Analysis Lab, researchers analyze street drug samples from around the country and have detected about 300 unique chemical substances. But making sense of chemicals is a notorious challenge, with long names, esoteric molecules, and overlapping pharmacological properties. Therefore, the team created a flexible ontology that can adapt over time, and developed visualizations to bring order to the chaos. Using a type of chord diagram called hierarchical edge bundling (.js package), they conceptualized co-occurrence of substances in the drug supply based on 6,000 drug samples from 34 US states, showing connections between classes of molecules. Working with a local graphic designer, hand drawn illustrations highlight particularly dangerous combinations of substances and tell the story of where the samples came from.
Join team members Nabarun Dasgupta and Anuja Panthari at the intersection of chemistry, art, public health, and data science, as they describe how their project brings order to the unruly illicit drug supply. The key message: The drug supply is vast, but it is knowable.
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About the Speakers
Nabarun Dasgupta
Nabarun Dasgupta, PhD, MPH, is a scientist who studies drugs and infectious diseases. His passion is telling true stories about health with numbers. Centered in pharmaco-epidemiology, his work amplifies community and patient voices in public health. Since 2002 he has done pioneering work in pain management, opioid overdose prevention, and addiction treatment. He also has deep expertise in health informatics and machine learning. In 2023 he was honored by being placed on the TIME100 Next list of rising global leaders.
As an applied epidemiologist, Dasgupta has served as an advisor to the US Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO). Operating with an appreciation for the social determinants and of health, he is committed to countering the impacts of racist drug policies. At UNC IPRC, he works at the Opioid Data Lab (OpioidData.org). His street drug analysis lab tests community-donated samples from around the country to figure out what lurks in the drug supply. Dasgupta co-founded two pioneering non-profit organizations. Project Lazarus in Wilkes County (North Carolina) was hailed by the Obama White House as a model for community-based overdose prevention. Remedy Alliance For The People is a groundbreaking national non-profit bulk distributor of free and low-cost naloxone to harm reduction programs. Previously he was the Chief Science Officer of Epidemico, a health informatics startup he co-founded using technology developed at Harvard Medical School. He is also an associate editor at the American Journal of Public Health.
Dasgupta earned degrees from Princeton University (molecular biology), Yale University (epidemiology of microbial diseases), and the University of North Carolina (pharmacoepidemiology). Follow him on Twitter (@nabarund).
Anuja Parathi
Anuja Panthari is an MPH Data Science candidate at UNC Gillings School of Public Health. She completed her BS in Cognitive Science and Statistics from UC Santa Cruz in 2022. Under the guidance of Dr. Dasgupta, she has been involved in harm reduction research at the Street Drug Analysis lab, assisting with multiple cutting-edge data analytics and visualization projects that will help communities demystify the street drug supply.

Data Matters 2024
2024-08-05 - 2024-08-09
Data Matters™ is a week-long series of one and two-day courses aimed at students and professionals in business, research, and government. 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. Data Matters gives students the chance to learn about a wide range of topics in data science, analytics, visualization, curation, and more from expert instructors.
Registration is now open for the Data Matters series which will be held August 5 – 9, 2024. Register here.

DataBytes: Using GenAI to win STTR and SBIR Government Grants
2024-06-20 16:00 - 17:00
Through a competitive awards-based program, STTR and SBIR federal grants enable small businesses to explore their technological potential and open new opportunities to profit from its commercialization. However, it can be difficult for first-time applicants to get their foot in the door, between sorting through guidelines, requirements, and deadlines, and trying to locate successful examples. GrantScout is automating grant search, writing, and submission. The tool uses traditional deep learning methods and generative AI to unlock funding for everyone. Join GrantScout founders Felicia Chen and Jennifer Tang as they present how the government provides over two million grants for small businesses, the ways that their team fine-tunes their own models to create strong technical proposals, and lessons they’ve learned from past experiences that helped them build the platform.
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