Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Advanced R Training - Master Complex Statistical Models training are: Mastery of basic R, vector programming, descriptive and inferential statistics.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Advanced R Training - Master Complex Statistical Models training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Advanced R Training - Master Complex Statistical... | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Advanced R Training - Master Complex Statistical Models training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Advanced R Training - Master Complex Statistical Models training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Advanced R Training - Master Complex Statistical Models training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training access terms and deadlines

Training objectives

Optimize processing of large data volumes with data.table and dplyr.

Develop advanced predictive models using lm, glm, and randomForest.

Create interactive visualizations with ggplot2 and Shiny.

Automate data workflows with purrr and futures.

Deploy R applications in production via R Markdown and plumber.

Analyze time series with forecast and tsibble.

Training program

Module 1Advanced Data Manipulation: data.table, dplyr, tidyr (tools, exercises, real datasets)

Dive into optimizing your R scripts by manipulating millions of rows with data.table for ultra-fast joins, chain with dplyr for smooth pipelines, tidyr for restructuring complex datasets, complete exercises on real cases like e-commerce log analysis, produce ready-to-use automated reports, all while gaining speed and precision to boost your daily productivity.

Module 2Statistical and Predictive Modeling: lm, glm, caret (models, validations, predictions)

Build generalized linear regressions with glm to predict customer churn, explore randomForest via caret to classify medical images, validate your models with cross-validation and ROC curves, apply on real Kaggle datasets like Titanic survival, generate reliable predictions with confidence intervals, transform your analyses into actionable insights that impress your stakeholders.

Module 3Visualization and Deployment: ggplot2, Shiny, R Markdown (dashboards, apps, deployed deliverables)

Create publication-ready graphics with ggplot2 to explore temporal trends, develop interactive dashboards via Shiny for live KPI monitoring, integrate everything into R Markdown reports exportable to PDF/HTML, deploy apps on shinyapps.io with plumber for data APIs, test on real business projects like sales tracking, leave with a concrete portfolio showcasing your advanced R expertise.