Data Science Workshop - Spring 2025 | NBL

Welcome to the Data Science Workshop - Spring 2025 hosted by New Brunswick Libraries (NBL)!
This workshop series is designed to introduce participants to essential data science concepts, tools, and applications.

Workshop Topics & Descriptions

1. Introduction to Python Programming

💡 Beginner-friendly | Hands-on
This workshop is tailored for those with little to no programming experience. It covers:

• Python syntax and script execution
• Jupyter Notebook & Google Colab
• Variables, Data Types, and Operators
• Control Structures: If-Else statements, loops, functions
• Data Structures: Lists, tuples, sets, dictionaries

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2. Mastering Data Analysis: Pandas and NumPy Essentials

📊 Data Analysis & Manipulation
Participants will dive into powerful data analysis tools:

• NumPy: Arrays, indexing, vectorized operations
• Pandas: DataFrames, Series, handling missing data, filtering, and aggregations
• Hands-on exercises using real-world datasets

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3. Introduction to Tableau: Visualizing Data Made Easy

📈 Interactive Data Visualization

• Learn to create interactive dashboards
• Explore dynamic charts and graphs
• Connect and transform data for storytelling
• Uncover hidden insights with Tableau

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4. Introduction to Machine Learning: Supervised Learning

🤖 Fundamentals of Predictive Modeling

• Understanding Supervised Learning
• Classification & Regression algorithms
• Hands-on with Linear Regression, Random Forests, Gradient Boosting Machines

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5. Introduction to Machine Learning: Unsupervised Learning

🧠 Discovering Hidden Patterns

• Explore Clustering techniques: K-Means, DBSCAN
• Learn Dimensionality Reduction with PCA
• Introduction to Association Rules for market basket analysis

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6. Data-Driven Decision Making: A/B Testing and Statistical Hypothesis Testing

📊 Statistical Methods for Business & Research

• Understand A/B Testing fundamentals
• Conduct Hypothesis Testing
• Practical case studies for data-driven decision-making

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7. Demystifying Generative AI

🤖 Understanding AI’s Impact

• What is Generative AI?
• Myths vs. Realities
• Ethical considerations and best practices
• How to integrate AI into personal and professional workflows

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8. Large Language Models: From Theory to Implementation

📚 LLMs in Action

• Introduction to Large Language Models (LLMs)
• How they work and their capabilities
• Hands-on implementation & responsible AI practices

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9. Generative AI Applications with AI Agents

🤖 Building Autonomous AI Systems

• Learn how Generative AI agents work
• Combining Language Models, Tools, and APIs
• Automating tasks and problem-solving with AI

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10. Building Intelligent Recommendation Systems

🎯 Personalized AI for Digital Platforms

• How Netflix, Amazon, and Spotify predict what users want
• Collaborative Filtering & Content-Based Recommendation
• Build your own Recommendation System with Python