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rstudio::conf(2022)

Michael Thomson

Flatiron Health
Quantitative Sciences
San Francisco

Contact Me

7:30am EDT

Breakfast 5. Maryland

9:00am EDT

How Data Science with R Works for Systems Administrators Maryland 6

11:00am EDT

How Data Science with R Works for Systems Administrators Maryland 6

12:30pm EDT

Lunch 5. Maryland

1:30pm EDT

How Data Science with R Works for Systems Administrators Maryland 6

3:30pm EDT

How Data Science with R Works for Systems Administrators Maryland 6

5:30pm EDT

Book Signing Reception 3. Cherry Blossom

7:30am EDT

Breakfast 5. Maryland

9:00am EDT

How Data Science with R Works for Systems Administrators Maryland 6

11:00am EDT

How Data Science with R Works for Systems Administrators Maryland 6

12:30pm EDT

Lunch 5. Maryland

1:30pm EDT

How Data Science with R Works for Systems Administrators Maryland 6

3:30pm EDT

How Data Science with R Works for Systems Administrators Maryland 6

5:30pm EDT

Welcome Reception 6. Riverview Ballroom

7:30am EDT

Breakfast 5. Maryland

9:00am EDT

Good practices for applied machine learning - from model development to model deployment 0. Potomac A+B

11:00am EDT

R Package Assessment: Lessons from Pharma 3. Cherry Blossom

11:20am EDT

Dive Deep into Metadata with Tplyr 3. Cherry Blossom R, Python, and Tableau: A Love Triangle 1. Potomac C

11:40am EDT

Packages and Process 3. Cherry Blossom

12:00pm EDT

Lunch 5. Maryland Pharma / Life Sciences - Birds of a Feather Maryland 1, 2, & 3

1:30pm EDT

Making Data Pipelines in R: A Story From A “Self-Taught” Perspective 4. National Harbor 10+11 Remote Content Execution with RStudio Connect and Kubernetes 2. Potomac D

1:50pm EDT

Scaling and automating R workflows with Kubernetes and Airflow 3. Cherry Blossom Data science in your customers hands on a budget and a deadline: Publishing Customer Facing Products with RStudio Connect 2. Potomac D

2:10pm EDT

An Integrated Workflow: Microsoft Azure DevOps, RStudio Workbench, RStudio Connect 3. Cherry Blossom

2:30pm EDT

Saving 1,000 hours with RStudio: selling R in your workplace 1. Potomac C Robust R Deployments: Building a Pipeline from RStudio to Production 2. Potomac D

3:20pm EDT

What they forgot to teach you about starting a business with R 3. Cherry Blossom Quarto for the Curious 1. Potomac C

3:40pm EDT

What they forgot to teach you about becoming an open source contributor 3. Cherry Blossom

4:00pm EDT

dbcooper: Turn any database into an R or Python package 4. National Harbor 10+11

4:30pm EDT

The Past and Future of Shiny 0. Potomac A+B

6:00pm EDT

Evening Dinner & Activities 7. Orchard Terrace

7:30am EDT

Breakfast 5. Maryland

9:00am EDT

Hello Quarto: Share • Collaborate • Teach • Reimagine 0. Potomac A+B

10:30am EDT

Developing internal tools for multi-lingual teams 1. Potomac C

10:50am EDT

How to be a pollinatoR 3. Cherry Blossom Achieving a seamless workflow between R, Python and SAS from within RStudio 1. Potomac C

10:55am EDT

Zero-setup R workshops with GitHub Codespaces 2. Potomac D

11:00am EDT

Making awesome automations with GitHub Actions 2. Potomac D

11:10am EDT

Enterprise-Level Data Science Success 3. Cherry Blossom Yes, you can use Python with RStudio Team! 1. Potomac C

11:30am EDT

An Introduction to the Apple Health Export 4. National Harbor 10+11

12:00pm EDT

Birds of a Feather - UseR Group Organizers Maryland 4, 5, & 6

1:30pm EDT

A Journey to Data Science: Tools for Equity and Diversity in STEM 3. Cherry Blossom

1:50pm EDT

Building Accessible Lessons with R and Friends 3. Cherry Blossom Demystifying the art of creating custom libraries for your organization 4. National Harbor 10+11

2:10pm EDT

You should be using renv 4. National Harbor 10+11

2:30pm EDT

Save an ocean of time: streamline data wrangling with R 1. Potomac C

3:20pm EDT

Introducing Rhino: Shiny application framework for enterprise 2. Potomac D

3:40pm EDT

From summarizing projects to setting tags, uses of parsing R files 4. National Harbor 10+11

4:00pm EDT

An introduction to R7 4. National Harbor 10+11

4:30pm EDT

Data science training in communities with limited technology resources and opportunities 0. Potomac A+B