Data Science Foundations & Applied Capstone: A Hands-On Beginner Workshop

Data Science Foundations & Applied Capstone is a full-day, hands-on workshop designed to introduce participants to the foundations of modern data science through practical exercises and collaborative problem solving.
Participants will work with real-world datasets and gain experience across several stages of the data science workflow, including data preparation and exploratory statistics, interactive data visualization, and an introduction to applied artificial intelligence and Large Language Models (LLMs). The workshop will introduce concepts such as Retrieval-Augmented Generation (RAG) and provide participants with an opportunity to experiment with LLM APIs through guided exercises.
The afternoon will transition from guided instruction to an applied capstone activity. Participants will work in small teams to analyze a provided dataset, identify meaningful trends, anomalies, or insights, and develop a data-backed recommendation. Teams will have flexibility in choosing their approach, including statistical analysis, interactive visualization, or AI-assisted analysis. Instructors will be available throughout the session to provide technical guidance and help teams refine their approach.
The workshop will conclude with short project showcases, allowing teams to present their analytical approach, key findings, and recommendations to fellow participants.
This workshop is intended for participants who are interested in developing practical data science skills. Prior advanced experience in data science or artificial intelligence is not required.
What to Bring: Please bring a laptop and charger and arrive a few minutes early for setup.
Organized by IEEE NJ Coast Young Professionals. Sponsored by IEEE Young Professionals and the IEEE Foundation.
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Agenda:
9:30 AM – 10:00 AM | Welcome & Environment Setup
Welcome remarks, overview of the workshop, and setup of the coding environment and workshop resources. Participants will be guided through accessing the tools and notebooks required for the day's activities.
10:00 AM – 11:00 AM | Module 1: Making Sense of Data
Introduction to working with real-world tabular data using Python and Pandas. Participants will explore data loading, cleaning, handling missing or malformed data, and basic descriptive statistics. The exercises will use the NYC Energy and Water dataset as an example.
11:00 AM – 12:00 PM | Module 2: Interactive Visual Analytics
Participants will move beyond static charts and explore interactive data visualization. The session will cover techniques for visually exploring relationships, filtering data, and identifying patterns and outliers using interactive visualization tools.
12:00 PM – 1:00 PM | Module 3: Introduction to Applied AI & LLMs
An accessible introduction to Generative AI, embeddings, Retrieval-Augmented Generation (RAG), and LLM APIs. Participants will complete a guided exercise using an LLM API to perform a structured analysis task.
1:00 PM – 2:00 PM | Lunch & Networking
Lunch and an informal networking session. Participants will have an opportunity to interact with instructors and discuss data science career paths, research opportunities, and real-world applications of data science.
2:00 PM – 2:30 PM | Applied Capstone Kickoff
Introduction to the capstone dataset and project objectives. Teams will be challenged to identify a meaningful trend, anomaly, or insight and develop a data-backed recommendation.
2:30 PM – 4:15 PM | Supervised Team Hacking
Participants will work collaboratively in small teams while instructors provide guidance on data analysis, visualization, AI techniques, and troubleshooting.
4:15 PM – 4:45 PM | Peer Project Showcases
Teams will deliver short lightning presentations highlighting their analytical approach, key findings, and recommendations.
4:45 PM – 5:00 PM | Synthesis & Wrap-Up
Closing discussion, key takeaways, resource sharing, and information for continued learning.
Room: H306, Bldg: Hamilton Hall, 188 Ellison Street, Passaic County Community College, Paterson, New Jersey, United States, 07505