Clinics and Workshops with OSS
Hands-On Learning for Research Computing
Open Source with SLU offers interactive clinics and workshops designed to build practical skills in research computing, software development, and open science practices. These sessions provide hands-on experience with tools and techniques essential for modern computational research.
Workshop Series
Git and GitHub for Researchers
Learn version control fundamentals specifically tailored for research workflows. Participants gain experience with collaborative coding, managing research data versions, and using GitHub for project organization and sharing. This workshop covers branching strategies for experimental work, handling large datasets, and integrating version control with common research tools.
Python for Data Analysis
Develop proficiency in Python libraries essential for research computing, including pandas, NumPy, matplotlib, and Jupyter notebooks. Workshops progress from basic data manipulation to advanced analysis techniques, with examples drawn from various research domains including life sciences, social sciences, and engineering.
R Programming for Statistical Analysis
Build expertise in R for statistical computing and graphics, covering data import/export, statistical modeling, and publication-quality visualization. Sessions include hands-on practice with real research datasets and guidance on reproducible analysis workflows using R Markdown and related tools.
Web Scraping and API Integration
Learn to collect data from web sources using ethical scraping techniques and API integration. Workshops cover legal and ethical considerations, rate limiting, data cleaning, and integration with research databases. Participants work with real-world examples relevant to their research domains.
Machine Learning for Research Applications
Explore machine learning techniques applied to research problems, covering supervised and unsupervised learning, model validation, and interpretation of results. Sessions focus on practical implementation using popular libraries and frameworks, with emphasis on understanding when and how to apply different approaches.
Database Design for Research Data
Develop skills in designing and implementing databases for research data management, covering relational database concepts, SQL fundamentals, and integration with analysis tools. Workshops include hands-on practice with database design, querying, and connecting databases to analysis environments.
Clinic Format
Drop-In Technical Support
Weekly drop-in sessions provide one-on-one technical support for ongoing research computing challenges. Bring your code, data, or technical questions for personalized assistance from experienced developers and researchers.
Lab-Specific Training
Customized training sessions designed for individual research labs, focusing on tools and techniques most relevant to specific research domains. These sessions can be scheduled to accommodate lab meeting times and research schedules.
Collaborative Problem-Solving
Group sessions where participants work together on common research computing challenges, fostering peer learning and knowledge sharing across different research domains and experience levels.
Who Should Attend
Graduate Students and Postdocs
Build computational skills essential for modern research while connecting with peers facing similar technical challenges. Sessions provide practical experience that directly supports dissertation research and career development.
Research Staff and Technicians
Develop technical expertise to better support laboratory research operations and data management responsibilities. Training focuses on tools and workflows that improve efficiency and reproducibility in research support roles.
Faculty and Principal Investigators
Stay current with evolving research computing tools and best practices. Sessions provide strategic insights into computational approaches that can enhance research productivity and enable new research directions.
Undergraduate Researchers
Gain foundational skills in research computing while working alongside graduate students and postdocs. Training provides valuable experience for students considering graduate school or careers in data-intensive fields.
Registration and Schedule
Workshops are offered throughout the academic year with both daytime and evening sessions to accommodate different schedules. Registration is free for SLU community members. Check our news pages or Join our Slack workspace for upcoming sessions.
Contact oss@slu.edu to request specific topics, suggest new workshop ideas, or arrange lab-specific training sessions.