Data Science Training Program
Natalie Elphick
The scripting language R is considered one of the most powerful languages for quantitative analysis, statistics, and graphics. This workshop will help you get started using R to analyze your datasets and create graphs for visualization. You’ll do hands-on exercises to demystify data analysis using R.
In this course, you’ll learn:
- RStudio interface
- Addition, subtraction, basic math operations
- Assigning values to variables
- Commenting in a script
- Logical operators
- Intro to functions and libraries
- Reading data
- Troubleshooting error messages
- Exploring data (basic summaries such as mean, median, etc.)
- Selecting subsets of data
- Plotting data
- Data structures available in R
Bring your laptop with RStudio and R installed.
Novice: This is an introductory workshop in the R Scripting series. No prior experience with programming or R/RStudio is required for this course. No prerequisites. Absolute beginners are especially welcome! Advanced-level packages such as Seurat will not be covered.
Visit the workshop site for more details and materials.
Details
Dates
1:00pm–3:00pm
1:00pm–3:00pm
Location
OnlineAudience
Gladstone and UCSFContact(s)
The Gladstone Data Science Training Program was started in 2018 to provide trainees with learning opportunities and hands-on workshops to improve their skills in bioinformatics and computational analysis. This program offers a series of workshops throughout the year to enable trainees to gain new skills and get support with their questions and data.
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Diversity, Equity, and Inclusion
At Gladstone, we are committed to providing events and professional development activities that resonate with our community’s diverse members. Our goal is to develop creative programming that encompasses a wide variety of ideas and perspectives to inspire, educate, and engage with everyone within our walls.
We want to effect positive change through our events and activities by providing a platform for discussions on important topics related to increasing diversity and inclusiveness in the sciences.