Introduction to R for Basic Statistical Analysis with the Help of Generative AI (Beginner)Home Training Catalog Introduction to R for Basic Statistical Analysis with the Help of Generative AI (Beginner) Intelligence Artificielle Générative Data Science Open Source Publishing Theoretical and applied statistics Short courses On-site courses Face-to-face Remote/Virtual English French Objectives Discover the fundamentals of R and generative AI tools. Learn the basics of descriptive statistical analysis and apply them to real-world datasets. Learn how to automate common tasks in R using generative AI. Master the creation of simple visualizations and data presentation. Get introduced to the concepts of simple regressions and hypothesis testing. Generate workflows and automated reports with R Markdown. Prerequisites: Basic statistics training Affinity for coding Comfort with computer tools and internet access Pedagogical Methods and Support: Sessions guided by the instructor Interactive digital resources Practical workshops on real-life cases Use of AI to assist learning Monitoring and Evaluation of Learning Outcomes: Practical exercises and case studies Multiple-choice quizzes (MCQs) and on-the-spot assessments Individual feedback on exercises Program Half-day 1: Introduction to Generative AI and Its Application in Statistical Analysis Introduction to Generative AI Definition and fundamental principles How generative AI models work Strengths and limitations of generative AI in data processing How Generative AI Can Simplify Learning Statistical Tools Practical Use Case for Beginners Generating fake data examples to illustrate statistical concepts Offering simplified explanations for basic concepts (mean, standard deviation, etc.) Structuring a step-by-step approach for a simple statistical analysis Half-day 2: First Steps with R Installation and Getting Started with RStudio Interface First Scripts: Introduction to Key Object Types in R Introduction to Essential Packages: dplyr, tidyr, ggplot2 Exploring a Simple Dataset Half-day 3: Effectively Visualizing and Analyzing Your Data Descriptive Analysis: Means, medians, standard deviations, frequencies. Creating Visualizations: Histograms, boxplots, bar charts. Case Study: Analyzing and visualizing a real dataset. Introduction to Automation: Using AI to generate simple visualization scripts. Half-day 4: Introduction to Regression and Hypothesis Testing Simple Linear Regressions: Concepts and implementation. Introduction to Hypothesis Testing Practical Workshop with Simulated or Real Datasets Half-day 5: Automating Analysis with R and Generative AI Prompt Engineering for Automating Analysis with R Writing simple prompts to generate R code. Automating key steps: data loading, cleaning, analysis, and visualization. Practical Example: Creating an Automated Workflow with R and Generative AI Loading a data file. Summarizing data and producing simple visualizations. Generating an automated report (HTML or PDF) using R Markdown. Duration 17 hours Level Beginner Audience Professionals, students, beginner researchers, or individuals in career transition wishing to get started with data analysis using R and generative AI tools. Participants 8 people maximum Instructor Salima Salima hold a PHD in economics from the University of Paris 1 Panthéon-Sorbonne, and spares no efforts when it comes to passing on knowledge and know-how. She is genuinely devoted to Educational purposes. Inter-company sessions 2025 - [on 1 full day and 3 half-days planned remotely] in french: - March 31st [09:00/12:30 – 13:30/17:00] April 1st [14:00/17:30] April 2nd and 3rd [09:00/12:30] - May 19th [09:00/12:30 – 13:30/17:00] May 20th, 22nd, and 23rd [09:00/12:30] 1750 EUR excluding VAT per person. For intra-company sessions: please contact us for a personalized quote. Next session : 31 March 2025 Register Ask for a quote Are you looking for information about a training course? You want to set up a customized training session? Contact our pedagogical team! Notice: JavaScript is required for this content. Upcoming trainings Intelligence Artificielle Générative Generative Artificial Intelligence for Scientific Monitoring Objectives Describe the general working principle of Deep Learning and Generative Artificial Intelligence. Use advanced prompting techniques to meet business needs. Synthesize articles and scientific content by producing concise summaries that highlight key points and main conclusions. Improve technological monitoring by configuring, customizing, and automating generative artificial intelligence tools to monitor and summarize the latest research published in specific fields. Identify key points in a specific scientific field and detect missing research topics needed to complete an existing theoretical model. Translate articles. 17 and 21 March Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Introduction to R for Basic Statistical Analysis with the Help of Generative AI (Beginner) Objectives Discover the fundamentals of R and generative AI tools. Learn the basics of descriptive statistical analysis and apply them to real-world datasets. Learn how to automate common tasks in R using generative AI. Master the creation of simple visualizations and data presentation. Get introduced to the concepts of simple regressions and hypothesis testing. Generate workflows and automated reports with R Markdown. 31 March01, 02 and 03 April Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Artificial Intelligence for Scientific Communication and Popularization Objectives Understand the fundamentals of Generative AI and its applications in communication Use AI in communication strategy: defining target audiences, structuring messages, choosing formats… 01 and 02 April Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Prompt Engineering Objectives Describe how a Generative AI (GenAI) works in order to optimize its use in daily tasks Apply prompt engineering methods to use GenAI tools effectively Identify use cases within your professional environment 04 April Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Artificial Intelligence for Image Analysis Objectives Acquisition of the basics in image analysis Mastery of tools and techniques for AI-assisted analysis Hands-on practice and development of image pipelines using Generative AI 08 and 15 April Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Integrating Artificial Intelligence into your scientific teams Objectives Understand Generative AI, its functioning, and its limitations Explore the applications of Generative AI and use cases for scientists Define a plan for integrating Generative AI into your team/laboratory and prioritize the first actions 13 May Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Generative AI for Qualitative Analysis Objectives Understand the fundamentals of generative AI and its applications. Master AI-assisted qualitative analysis techniques. Use AI for analyzing and presenting qualitative data. 02 and 03 June Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Enhance your statistical analyses with R and Generative AI (Advanced) Objectives • Deepen your mastery of R to perform advanced statistical analyses.• Discover and leverage generative AI tools to automate common tasks in data analysis.• Optimize analytical processes by integrating automated workflows.• Structure complex workflows effectively and innovatively.• Strengthen the understanding and application of advanced statistical concepts to real and simulated cases. 09, 10, 12 and 13 June Register Ask for a quote Upcoming trainings Intelligence Artificielle Générative Generative Artificial Intelligence for Research Education Objectives Discover the general principles of Deep Learning and Generative Artificial Intelligence, and benefit from the potential of Generative AI tools. Use advanced prompting techniques to meet business needs. Classify generative AI tools according to the media they implement (text-to-text, text-to-image, etc.), and select the right tool for a specific use case. Produce educational activities such as course notes, study guides, or chapter summaries to assist students in their learning. Design exams and quizzes based on the training content developed for students, saving time in course preparation. Generate scenarios or case studies for group projects, based on current topics or scientific advancements, to expand the possibilities of course facilitation (content, group workshops, etc.). Adapt your teaching and prepare your students for the Generative AI revolution. 26 June03 July Register Ask for a quote Previous Next
