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 Training Matplotlib Advanced - Impactful and Customized Visualizations training are: Mastery of Python, Pandas, and basics of Matplotlib (simple figures, basic plots).. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Matplotlib Advanced - Impactful and Customized Visualizations training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Training Matplotlib Advanced - Impactful and Cus... | 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 Training Matplotlib Advanced - Impactful and Customized Visualizations 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 Training Matplotlib Advanced - Impactful and Customized Visualizations 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 Training Matplotlib Advanced - Impactful and Customized Visualizations 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 objectives

Master subplots and complex layouts for multi-view dashboards.

Customize styles, themes, and colors for publication-ready charts.

Create interactive animations and dynamic 3D visualizations.

Optimize performance for large datasets and vector exports.

Integrate Matplotlib with Plotly and Seaborn for powerful hybrids.

Develop real-world use cases in data storytelling.

Training program

Module 1Advanced Subplots and Layouts: Multi-Panel Figures (GridSpec, make_subplots)

Dive into nested subplots, discover GridSpec and Flexible Layouts to structure complex dashboards, complete practical exercises on real datasets like time series, create your first customized layouts with dynamic annotations, and export to interactive PDF, all while optimizing space for impactful presentations.

Module 2Styles, Themes, and Customization: rcParams, Advanced Colormaps

Explore Seaborn and native Matplotlib themes, modify rcParams for a unique corporate style, test perceptually optimized colormaps on heatmaps and contours, apply through exercises on your business data, generate custom palettes with ColorBrewer, and validate accessibility of your visuals for maximum impact.

Module 3Animations and 3D: FuncAnimation, mplot3d for Immersive Dynamics

Create smooth animations with FuncAnimation on data evolutions, integrate interactive sliders via Matplotlib widgets, dive into 3D with projections and surfaces, practice on concrete cases like spatio-temporal models, export to GIF/HTML5, and measure gains in audience engagement.

Module 4Integrations and Real Cases: Plotly, Seaborn, Data Storytelling

Hybridize Matplotlib with Plotly for web interactivity, merge with Seaborn for advanced stats, develop a complete data storytelling project on a Kaggle dataset, optimize rendering for large volumes, produce portfolio-ready deliverables, and present your creations in a pitch session.