LSB Data Camp

GEN AI Tutorial 3 Part Series: Advanced Generative AI Agent Models

Tuesday, March 19
6:00 pm – 8:00 pm
Sankey 116

The last part of the 3 Part Series: Designing and building your own applications using Generative AI taught by Dr. Mustafa Akben.

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GEN AI Tutorial 3 Part Series: Retrieval Augmented Generation Based Generative AI models

Tuesday, March 12
6:00 pm – 8:00 pm 
Sankey 308

Designing and building your own applications using Generative AI taught by Dr. Mustafa Akben. This is the 2nd session. The last session will be on March 19.

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GEN AI Tutorial 3 Part Series: Simple Chatbot Customization with Prompt Engineering

Tuesday, February 27
6:00 pm – 8:00 pm
Sankey 308

Designing and building your applications using Generative AI taught by Dr. Mustafa Akben. The next two dates are March 12 and March 19 are a part of the series.

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More Analysis, Less Coding Using SAS Visual Analytics
Tuesday, February 13
6:00 PM – 8:00 PM
Sankey 308

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In this hands-on workshop, learn how to use SAS Visual Analytics to visualize your data, identify trends and examine relationships in your data.  We will also learn how to easily build and refine predictive models, and run numerous scenarios simultaneously. You can ask more what-if questions to get better, faster results. Throughout this session, we will use SAS Viya for Learners, a free cloud-based suite of applications for students and educators, which offers programming, data preparation, visualization, modeling, and more, within a single interface.

Presented by: Linda Jordan, Principal Analytical Training Consultant, SAS

Business and Social Network Analysis with Gephi
Tuesday, November 14
6:00 PM – 8:30 PM
Sankey 116 

Networks are everywhere. This module introduces basic concepts of networks and then guides you to analyze business and social networks with Gephi, a stand-alone tool for calculating statistics and visualizing networks. Computer programming experience is not required. This module will cover the following topics.

Nodes, links, and network types
Centrality measures
Loading and analyzing network data in Gephi
Visualizing networks
After completing this module, you will be able to view business and social connections as networks and analyze their structures rigorously.

Presented by Dr. Hyunuk Kim

Data Visualization Using Power BI
Tuesday, September 12
6-8:30 p.m.
Sankey 308

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In this class we will take a deep dive into Data Visualization technologies and techniques. We will begin to learn the art of understanding the audience and how to navigate the business questions asked. We will learn how to convey a compelling data-driven story to a business executive using Power BI.

By the end of this module, learners will:

• Learn to dissect the business question being asked when tasked with creating a data visualization or dashboard
• Take a deep dive into Power BI. Learn how it can be used to answer a real world business problem
• Learn to keep an open mind when it comes to visualizing data. The best visualizations require the most creativity

Instructor: Eric Maxon, a senior marketing analyst for Carolina Biological Supply Company

SQL Data Camp: Data Retrieval and Transformation for Analytics
Tuesday, September 26
6-8:30 p.m.
Sankey 308

Register Here

Welcome to the SQL Data Camp! This tutorial offers a hands-on experience that will introduce you to the power of Structured Query Language (SQL), a foundational skill for anyone interested in data analytics.

In this data camp, you’ll be guided through various interactive tasks where you will:

• Understand SQL Fundamentals: Gain a solid understanding of SQL’s basic concepts, including databases, tables, queries, and data manipulation
• Execute SQL Queries: Learn how to write and execute SQL queries to retrieve, filter, and sort data from databases.
• Perform Data Manipulation: Learn about inserting, updating, and deleting data in SQL databases to manage information effectively.
• Implement Data Joins: Explore various types of joins to combine data from multiple tables and create comprehensive insights.
• Aggregate Data: Learn how to summarize and analyze data using aggregation functions like SUM, AVG, COUNT, MIN, and MAX.
• Design and Manage Databases (if time permits) Understand the principles of database design, normalization, and indexing to optimize performance and maintain data integrity.

By the end of this SQL tutorial, you’ll be equipped with an understanding of how to work with SQL databases, analyze data, and implement data transformations important for analytics.

Instructor: Associate Professor Su Dong from the Department of Management & Entrepreneurship in the Love School of Business

Generative AI Workshop: Understanding ChatGPT
Tuesday, October 10
6-8:30 p.m.
Sankey 308

Register Here

Welcome to the Generative AI  Data Camp! This tutorial provides a hands-on journey, immersing you into the captivating and confusing world of Generative AI, with a particular focus on ChatGPT, a pioneer in conversational AI models.

Throughout this workshop, participants will engage in a series of interactive tasks where they will:

• Understand Generative AI Fundamentals: Understand the basics of generative AI tools, comprehending their capabilities, strengths, and applications.
• Learn about Prompt Engineering: Delve into the intricacies of prompt design, exploring how the right questions can guide the model’s responses.
• Develop Engaging Learning Activities: Explore methods to integrate ChatGPT into the learning process – learn how it enables an interactive learning experience,  in addition to allowing an efficient search for information
• Discuss Ethical Considerations: Reflect upon the ethical implications of using Generative AI, understanding potential biases, and strategies to minimize them. Discuss ways to maximize the benefits of this technology while mitigating its effects on our critical and creative thinking.

By the conclusion of this Generative AI workshop, participants will be empowered with a clearer understanding of ChatGPT’s capabilities, an ability to harness its potential in education while learning to utilize them ethically.

Instructor: Assistant Professor Mustafa Akben in the Department of Management and Entrepreneurship in the Love School of Business

As current and future statisticians, data scientists, and general data stewards, we create data, collect data, store data, transform data, visualize data, and ultimately impact how data are used. With this responsibility, it is imperative that we confront the ways in which data and algorithms have been used to perpetuate social inequities and seek to eliminate biased decisions and algorithms in our own work. Join a conversation where we discuss the landscape of bias and equity in data science and machine learning with a focus on harms related to race and gender. Consider questions to ask throughout the workflow of a data project, including key decisions at the start of a project, when collecting data, and when designing and interpreting algorithms. Walk away with a better understanding of approaches and tools for addressing bias and inequity in data and algorithms that can support improved data-driven decision-making.

Instructor: Emily Hadley, a research data scientist with the RTI International Center for Data Science and AI

Are you tired of spending hours on manual data processing tasks? Do you want to learn how to use extract, transform, and load (ETL) techniques more efficiently so you can focus on the analysis and interpretation of financial data? Then join us for our Data Camp session on Alteryx!

Alteryx is a powerful data analytics and process automation software platform that can help you simplify data preparation, speed up insights, and improve collaboration. Using hands-on practices, we’ll will guide you step-by-step in developing the skills and knowledge you need to get started with the software.

By the end of the module, learners will:

• Understand the benefits of Alteryx and how it can help you streamline data analytics processes and improve decision-making.
• Learn how to use Alteryx’s drag and drop tools for data preparation, including cleaning, blending, and transforming data.
• Learn how to create workflows and automate processes in Alteryx to save time and improve productivity.

Instructor: Assistant Professor Kevin Agnew of the Department of Accounting

In this session, we will examine concepts of data visualization and learn how Tableau can help you make sense of your large dataset. You will also learn how to prepare your data for compelling storytelling. Prof. Ajjan will guide you step-by-step to build a story and convey data insights clearly and directly.

By the end of the module, learners will:

• Build a solid foundation with core concepts and techniques for working with data to create visualizations in Tableau
• Develop an understanding of visual best practices
• Learn how to create a digital story to effectively share your information and insights

Instructor: Dr. Haya Ajjan

In this session, we will examine concepts of data analytics with a special focus on web-based data. Specifically, you will build a solid foundation with core concepts in web-based analytics. You will also apply popular industry-standard analytics tools to analyze web-scale data and gain meaningful insights from them. A mixed teaching approach—a combination of short lectures and hands-on practices—will be adopted to guide you step-by-step to build effective web-based analytics systems to support real-world business decisions.

By the end of the module, learners will be able to:

• Understand the key concepts in web-based analytics, including web development basics, definition and categories of web analytics
• Apply practical analytics techniques for working with web-scale data to support decision-making across multiple business domains following the analytics processes (e.g., data collection, preprocessing, analytical modeling, evaluations, deployment, etc.)
• Evaluate the innovative applications of web analytics in modern businesses and organizations and potentially create new business opportunities

Instructor: Dr. Long Xia

In this module, we’ll learn about R, the free, open source, and powerful statistical software. We’ll use the RStudio developer environment, also free to download, and the R language to import, clean, visualize, and summarize our data. Instructions for set-up (Mac or PC) will be provided.

By the end of the module, we will:

• Learn how to install R, R Studio, and navigate our developer environment.
• Use “Tidyverse” packages and syntax to explore our data.
• Discuss the basics of moving from “point and click” statistical analysis to a more reproducible and automated workflow.

Instructor: Dr. Adam Aiken

In this learning module, we will examine concepts of data mining with a special focus on textual data, which has become a major data format in the business world. Specifically, you will build a solid foundation with core concepts in text mining and analytics. You will also apply popular text mining tools to analyze text data from multiple perspectives (e.g., topic modeling, sentiment analysis, text classification, etc.) and gain meaningful insights. This module will guide you step-by-step to build effective text analytics systems to support real-world business decisions.

By the end of the module, learners will be able to:

• Understand the key concepts in text analytics, including various types of text analytics and how each of them would support practical business operations and decision-making;
• Apply different levels of text analytics algorithms, including basic lexicon-based methods, traditional machine learning, and state-of-the-art deep learning;
• Evaluate the innovative applications of text analytics in modern businesses and potentially create new business opportunities.

Instructor: Dr. Long Xia

In this session, you will learn the basics of Robotic Process Automation and how RPA software can be used to automate repeatable tasks that have been traditionally performed by humans. We will examine the characteristics, benefits, types of robots, and processes suited for RPA. Prof. Agnew will guide you through the process of creating a robot, scraping data, looping, reading data and writing to Excel using UiPath.

By the end of the module, learners will:

• Understand the basics of Robotic Process Automation
• Identify processes that can be automated
• Develop and deploy basic robots independently using UiPath RPA Platform

Instructor: Dr. Kevin Agnew

Join us on for an interactive, hands-on-workshop exploring Machine Learning Operational Implementations (MLOps in brief) on Dataiku’s end-to-end platform for everyday AI.

By the end of the module, learners will:

• Easily access and explore data sources
• Prepare training data
• Build machine learning models
• Deploy one to generate predictions on new, unseen records, and
• Manage a model through its lifecycle

Presented by Dataiku team members Chris Butler, partner solutions architect, Molly Jones, solutions engineer and Andrew Williams, solutions engineer.