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Illustration: R Training with Artificial Intelligence (AI) course

R Training with Artificial Intelligence (AI)

Many people first encounter R through statistics courses and gradually develop
their skills by consulting manuals, technical documentation, and online
resources. Although this approach helps them perform analyses, it often
overlooks workflow organization, code quality, and the effective use of
development tools.

This can lead to significant technical debt, including lost time,
trial-and-error programming, difficulty troubleshooting problems, and reliance
on inefficient work methods.

This course teaches you how to integrate artificial intelligence into your R
environment so that you can work more efficiently. You will learn how to use
tools such as Gemini and Posit Assistant to plan an analysis, generate and
explain code, troubleshoot errors, explore data, and continuously improve your
skills.

The goal is not to replace learning R or understanding statistical methods.
Instead, you will learn how to use AI as a true copilot that supports and
accelerates your work.

This course is suitable for both beginners who want to accelerate their
learning and experienced R users who want to modernize their workflows.

1 day 9:00 a.m. to 4:30 p.m. Online, Montreal, Quebec City Beginner
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The R Training with Artificial Intelligence (AI) course at a glance

Length
1 day
Schedule
9:00 a.m. to 4:30 p.m.
Format
Live virtual class or in person in Montreal and Quebec City
Level
Beginner
Audience
Tous
Price
$550 per participant, or $467 for public bodies and non-profits (plus taxes)
Language
French or English

Doussou Formation and R Training with Artificial Intelligence (AI): key facts

Upcoming R Training with Artificial Intelligence (AI) sessions

Online

R Training with Artificial Intelligence (AI) course outline

Setting Up Artificial Intelligence Tools

  • Create or configure a Google Account;
  • Access Gemini and Google AI Studio;
  • Obtain and securely manage a Gemini API key;
  • Explore Google’s main online tools;
  • Compare Gemini with other AI assistants and models;
  • Understand data privacy and confidentiality considerations.

Programming with AI

  • Explore the main tools used with R;
  • Understand the roles of RStudio, Google Colab, and Quarto;
  • Configure a Google Colab notebook to work with R;
  • Generate, comment on, and explain code with AI;
  • Improve scripts and troubleshoot errors;
  • Use Gemini in conversational mode and with code blocks;
  • Convert a notebook into a Quarto document;
  • Move from an online environment to a local development environment.

Using Posit Assistant in RStudio

  • Explore Posit Assistant and its main features;
  • Use the assistant directly within RStudio;
  • Generate, explain, and modify R code;
  • Troubleshoot errors using the project context;
  • Use AI-powered code-editing suggestions;
  • Understand the limitations of an AI assistant integrated into a development environment.

Using AI Features Effectively

  • Write clear, precise, and contextualized prompts;
  • Use AI to plan an analysis;
  • Interact with technical documentation or PDF manuals;
  • Analyze code, tables, charts, and diagrams;
  • Compare multiple solutions suggested by AI;
  • Validate AI-generated answers, code, and results;
  • Protect personal, confidential, and organizational data.

Learning R Syntax with AI

  • Explore the fundamental elements of R syntax;
  • Create objects, vectors, and data frames;
  • Use functions and operators;
  • Generate examples tailored to your skill level;
  • Ask AI to explain and adapt code examples;
  • Diagnose and correct common errors;
  • Create a self-assessment quiz;
  • Develop a personalized AI-assisted learning plan.

Performing Data Analysis with R and AI

  • Explore the main Tidyverse packages;
  • Use data.table to work with large datasets;
  • Compare base R, Tidyverse, and data.table;
  • Import and explore a dataset;
  • Clean, transform, and validate data;
  • Create summary tables and data visualizations;
  • Use AI to generate, explain, adapt, and correct code;
  • Apply the workflow to your own data.

Performing Statistical Analysis with AI

  • Find and use reliable technical documentation;
  • Translate a business or research need into an analytical approach;
  • Select an appropriate statistical method with AI assistance;
  • Compare two means using a t-test;
  • Calculate and interpret Cohen’s d;
  • Select the appropriate parameters and function arguments in R;
  • Verify assumptions and interpret the results;
  • Adapt the workflow to other statistical analyses.

Prices and practical information

Preferred rate

$467 / participant

Public bodies and non-profits · plus taxes

Standard price

$550 / participant

Businesses and individuals · plus taxes

Practical information

  • Length: 1 day
  • Schedule: 9:00 a.m. to 4:30 p.m.
  • Format: Live virtual class or in person in Montreal and Quebec City
  • Payment: online (PayPal or card) when registering, or by invoice for organizations
  • Funding: Doussou Formation is a training organization accredited by the CPMT. For Quebec employers subject to the Act to promote workforce skills development (payroll over $2M), this course can count toward their 1% training obligation.
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Corporate R Training with Artificial Intelligence (AI) training

Train your whole team as a private group, on your own documents, at your premises or in a virtual class, on the dates that suit you.

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Participant reviews

97% satisfaction (end-of-course evaluations, 120 evaluations) · Read all testimonials

Why take this R Training with Artificial Intelligence (AI) course

Objectives: what you will be able to do

  • Configure the main AI tools used with R;
  • Write effective prompts to generate, explain, and debug code;
  • Use AI with Google Colab, RStudio, and Quarto;
  • Plan a data analysis before writing code;
  • Compare base R, Tidyverse, and data.table approaches;
  • Use AI to explore data and perform basic statistical analyses;
  • Evaluate the quality, relevance, and reliability of AI-generated code;
  • Create a personalized plan for continuing to learn R.

Prerequisites

  • Basic computer skills;
  • Previous exposure to R or an interest in data analysis;
  • A computer on which R and RStudio can be installed;
  • A Google Account to access Gemini and Google Colab.

What is included

  • Course materials and exercise files for each participant
  • Certificate of attendance
  • Optional personalized coaching after the course
  • In public in-person sessions:
    • Tea and coffee
    • Lunch at a nearby restaurant
    • Parking (in some cities)
    • Wi-Fi access

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