Python for Researchers: Analyze Data, Automate Tasks, Accelerate Discovery
Go beyond spreadsheets and unlock the power of your research data with Python! This hands-on course is designed specifically for researchers, graduate students, and professionals with little or no prior programming experience.
Learn the essential Python skills to streamline your workflow, analyze complex datasets effectively, create publication-quality visualizations, and automate repetitive tasks. We focus on practical applications relevant to academic and research environments, using tools like pandas, matplotlib, and Jupyter Notebooks.
What You’ll Gain:
* Efficient Data Handling: Master data cleaning, manipulation, and analysis using the powerful pandas library.
* Compelling Visualizations: Create informative plots and figures with matplotlib suitable for presentations and publications.
* Workflow Automation: Save valuable time by automating repetitive analysis and data processing steps.
* Reproducible Research: Learn best practices for documenting your analysis in Jupyter Notebooks for transparency and reproducibility.
Through practical exercises using relevant sample datasets and a final mini-project integrating these skills, you’ll leave with the confidence and ability to apply Python effectively in your own research. Includes presentation slides, sample data, helpful cheat sheets, and curated online resources.
Objective
Learn how to create effective visualizations for exploratory data analysis and publication-quality reports using Python’s matplotlib and seaborn libraries.
Objective:
Introduce participants to basic machine learning concepts and applications using the scikit-learn library. By the end of the session, they should be able to build and evaluate simple predictive models.
Google