This workshop will introduce LaTeX, a typesetting system used to prepare documents and separate text from formatting. This introductory workshop will focus on using Overleaf, an online real-time collaborative LaTeX editor.

This workshop will provide an introduction to bibliometric methods. Bibliometrics, or the use of tools and statistical methods to analyze published books and articles, can be a useful approach to understanding a body of knowledge and the way researchers are collaborating or publishing work on a topic. We will cover the basics of gathering a dataset for bibliometric analysis using tools like Scopus and SciVal; provide an overview of software tools for analyzing bibliographic data; and discuss examples of bibliometric analyses across a range of disciplines. The workshop is aimed at graduate students, staff, and faculty researchers, but anyone is welcome to join.

CMU Libraries supports open access publishing through various mechanisms, including publisher agreements, APC funds, and by providing an institutional repository. Join this workshop to learn about utilizing CMU's open access support.

We will utilize AI chatbots like ChatGPT, Bard, and Co-pilot to support the process of learning to code. Using Python as our teaching tool, participants will acquire skills that are transferable to other programming languages. We will explore how AI chatbots can be invaluable resources for understanding, writing, and refining code, as well as for facilitating transitions between different coding languages.

Workshop attendees will:

1. AI Fundamentals: Understand key concepts and terminology related to generative AI.
2. Practical Application: Use generative AI as a programming assistant to enhance coding efficiency, troubleshoot errors, and tackle projects with greater confidence.
3. Critical Evaluation: Develop the ability to assess the accuracy, reliability, and usefulness of AI-generated code and solutions.
4. Ethical and Practical Evaluation: Examine the ethical implications of generative AI, recognizing its strengths, weaknesses, biases, limitations, and potential for misuse.
5. Adaptability and Continuous Learning: Cultivate skills to continuously adapt to advancements in AI technology.

In this workshop, we will explore the fundamentals of machine learning using scikit-learn. Participants will learn essential techniques for data preparation, model building, and evaluation through practical, hands-on exercises. This curriculum is designed for beginners, providing a clear and straightforward introduction to machine learning concepts. By the end of the workshop, you will have an understanding of how to apply these skills to real-world problems, regardless of your prior programming experience.

This is a three-part workshop series (please register for each session separately):

• Part 1: Introduction to Machine Learning and Supervised Methods
• Part 2: Ensemble Methods
• Part 3: Unsupervised Methods and Neural Networks