Python Series
Complete any 3 workshops in this series to earn a "Python 101" digital badge for your LinkedIn profile!
Designed for learners at all levels, this series provides a hands-on introduction to Python programming — from the basics of variables and loops to real-world data analysis with libraries like Pandas and Polars. We’ll also explore advanced topics such as topic modeling with BERTopic, a powerful tool for analyzing text data.
Join us for a hands-on, in-person workshop where you’ll learn the fundamentals of Python programming—including data types, variable assignment, if-else statements, and loops. No prior coding experience required. This workshop is part of the Python 101 series, designed for complete beginners. It also serves as a prerequisite for attending other Python workshop series if you have no prior coding background.
This hands-on 90-minute workshop introduces you to Pandas DataFrame - Python's powerful tool for working with structured data. Perfect for beginners ready to start their data journey. In this session, we will learn:
1) Load and explore data from CSV files using pandas
2) Perform essential DataFrame operations: filtering, sorting, and transforming your data
3) Work with time series data
4) Perform descriptive statistical analysis on your data Who Should Attend: Beginners with basic Python knowledge who want to dive into data analysis.
No prior experience with pandas or data manipulation required. Participants are expected to bring their laptop to this workshop.
This hands-on 90-minute workshop introduces you to Polars DataFrame - Python's high-performance alternative to pandas, designed for speed and efficiency when working with structured data. Perfect for those ready to explore next-generation data processing tools.
In this session, we will learn:
1) Load and explore data from CSV files using Polars with lazy evaluation techniques
2) Perform essential DataFrame operations: filtering, sorting, and transforming data using Polars' expressive syntax
3) Work with time series data on Polars
Who Should Attend: Python users with basic pandas experience who want to explore faster data processing alternatives. Some familiarity with DataFrame concepts helpful but not required. Participants are expected to bring their laptop to this workshop.
This hands-on 90-minute workshop introduces you to Large Language Model APIs that let you programmatically interact with AI models like Claude and GPT for custom applications, automation, and experimentation.
In this session, we will learn:
1) Understand what APIs are and how to make your first API calls to language models
2) Navigate API playgrounds and explore different LLM providers (Claude, OpenAI, and others)
3) Understand common settings: context windows, max tokens, temperature, top-k, and top-p, and system prompts
4) Explore use cases in academia, such as using LLMs to classify text sentiment.
Who Should Attend: This in-person workshop welcomes participants with basic Python knowledge, including those new to APIs. No prior API experience required - we'll start with fundamentals before diving into LLM-specific features.
Curious about uncovering hidden themes in large collections of text — such as social media posts, article abstracts, or short reports? This hands-on workshop introduces BERTopic, a powerful Python library for topic modeling that leverages transformer-based embeddings and clustering.
This workshop series was designed by Dong Danping, Senior Librarian, Research & Data Services and Bella Ratmelia, Senior Librarian, Research & Data Services. If you have any questions, please contact Danping at dpdong@smu.edu.sg or Bella at bellar@smu.edu.sg.
Please refer to the related materials and recording (if available) for this workshop below.
Code-free Data Science and Analytics Series (CDSAS)
*Please note that digital badging is not yet available for this series.
Join Prof Kam (SCIS) in this 9-episode series of R workshops. No prior R programming experience is needed as long as you are willing to learn!
This workshop series was designed by Assoc Prof. Kam Tin Seong, School of Computing and Information Systems. If you have any questions, you may contact Prof. Kam at tskam@smu.edu.sg or the library at library@smu.edu.sg.
Please refer to the related materials and recording (if available) for this workshop below.
Description of workshop:
ProQuest's TDM Studio helps you accelerate your research by allowing you to run text data mining analyses on extensive licensed materials, including historical newspapers, reports, and dissertations.
The platform offers a Virtual Workbench for Python and R coding, as well as no-code visualization tools. It's a great tool for thesis research, sentiment analysis, and topic modeling.
By the end of the session, you will be able to:
Navigate TDM Studio's Visualization and Workbench dashboards.
Create, analyze, and export datasets using built-in no-code tools like geographic analysis, topic modeling, and sentiment analysis.
Run custom Python analysis on the virtual machine and save your results.
This workshop was designed by Brandon WIlliams, TDM Studio Consultant. If you have any questions, please contact Redzuan Abdullah, Senior Librarian at redzuana@smu.edu.sg.
Please refer to the related materials and recording (if available) for this workshop below.