Week 5 Live Session (AI)
This lesson is called Week 5 Live Session (AI), part of the R in 3 Months (Fall 2026) course. This lesson is called Week 5 Live Session (AI), part of the R in 3 Months (Fall 2026) course.
Transcript
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We gave an informal, optional introduction to using AI for R coding. We covered data privacy, the different ways to work with AI, and a live demo of having Claude write, explain and help verify code in Positron.
You'll learn:
- How to change your Claude privacy setting so your chats are not used to train models, and what 30-day retention and zero data retention agreements mean
- Why to ask AI to write code for an analysis rather than do the analysis itself, so you have a verifiable record of what was done
- How to use an AI extension in Positron to import and reshape data, make charts, and choose between manual, automatic and auto modes
- How to ask AI to add detailed comments to code and how to verify its output by running the code piece by piece and comparing it with the raw data
- Why working inside your editor with a tool that sees your R session beats copying and pasting between a chatbot and your code
Resources mentioned:
- Claude
- Claude Code
- ChatGPT
- Codex
- Posit Assistant
- Positron
- RStudio
- Privacy and AI assistants (Posit blog)
- Raycast
- Handy
- {tidyverse}
- {readxl}
- {janitor}
Key moments:
- 01:46 Participants share how they have used AI for coding
- 09:25 A participant describes using Claude for gene expression analysis
- 11:42 Ask AI to write code so results can be verified
- 14:41 Data security and the Posit privacy article
- 17:40 Turning off model training in Claude privacy settings
- 21:10 Question on enterprise accounts and organizational AI policies
- 25:10 Web app, desktop app, editor extension and terminal compared
- 30:47 Posit Assistant demo importing penguins data and making a scatter plot
- 34:33 Claude extension demo planning an Excel import
- 41:51 Dictating prompts to AI with Raycast and Handy
- 45:57 Question on how to verify AI output against raw data
- 47:41 Having AI add detailed comments to explain code
- 51:32 Question on efficiently verifying AI data cleaning, including tests
Have any questions? Put them below and we will help you out!
Course Content
143 Lessons
1
Welcome to Fundamentals of R
01:20
2
Update Everything
02:26
3
Start a New Project
02:38
4
The Tidyverse
03:24
5
Pipes
03:52
6
select()
04:43
7
mutate()
03:22
8
filter()
10:18
9
Quiz
10
summarize()
05:38
11
Grouped Summaries
04:24
12
arrange()
02:50
13
Create a New Data Frame
03:30
14
Quiz
15
Bring it All Together (Data Wrangling)
07:09
16
Week 2 Project Assignment
13:10
17
Week 2 Coworking Session (Fall 2026)
18
Week 2 Live Session (Fall 2026)
59:16
1
The Grammar of Graphics
04:36
2
Scatterplots
03:40
3
Histograms
04:51
4
Bar Charts
04:53
5
Quiz
6
Setting color and fill Aesthetic Properties
02:43
7
Setting color and fill Scales
05:12
8
Quiz
9
Setting x and y Scales
02:58
10
Adding Text to Plots
05:50
11
Plot Labels
02:59
12
Themes
02:10
13
Facets
02:56
14
Save Plots
02:49
15
Bring it All Together (Data Visualization)
06:14
16
Week 3 Project Assignment
06:02
17
Week 3 Coworking Session (Fall 2026)
18
Week 3 Live Session (Fall 2026)
1:00:46
1
Best Practices in Data Visualization
03:38
2
Tidy Data
02:25
3
Pipe Data in ggplot
08:18
4
Reorder Plots to Highlight Findings
03:50
5
Line Charts
04:13
6
Use Color to Highlight Findings
08:23
7
Declutter
07:53
8
Add Descriptive Labels to Your Plots
09:18
9
Use Titles to Highlight Findings
08:30
10
Use Annotations to Explain
06:35
11
Quiz
12
Week 9 Coworking Session (Fall 2026)
13
Week 9 Live Session (Fall 2026)
59:10
1
Advanced Markdown
07:10
2
Tables
15:48
3
Advanced YAML and Code Chunk Options
05:42
4
Inline R Code
03:42
5
Making Your Reports Shine: Word Edition
05:08
6
Making Your Reports Shine: PDF Edition
07:37
7
Making Your Reports Shine: HTML Edition
06:08
8
Presentations
11:12
9
Dashboards
06:20
10
Websites
08:11
11
Publishing Your Work
02:37
12
Quarto Extensions
06:38
13
Parameterized Reporting, Part 1
07:02
14
Parameterized Reporting, Part 2
04:03
15
Parameterized Reporting, Part 3
06:22
16
Quiz
17
Week 12 Coworking Session (Fall 2026)
18
Week 12 Live Session (Fall 2026)
57:26
1
Working with dates
18:22
2
Working with labelled data
05:35
3
Understanding Documentation Pages
05:20
4
Factors in R
11:18
5
Add citations to Quarto documents
10:42
6
Change titles of facet plots
08:16
7
Population pyramid plot
04:24
8
Crosstabs
06:58
9
Difference between == and %in%
03:17
10
Quarto - rendering and working directories
13:05
11
Regular expressions
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