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 - Create Impactful Visualizations training are: Intermediate mastery of Python, knowledge of NumPy and Pandas, experience in data manipulation.. A preliminary interview validates your eligibility.

Is the training available in person?

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

Training Matplotlib - Create Impactful Visualiza... | 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 - Create Impactful 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 - Create Impactful 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 - Create Impactful 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 access terms and deadlines

Training program

Module 1Advanced Matplotlib Fundamentals: Figures, Axes, and Basic Customization (Pyplot, Object-Oriented)

Dive into the deep mechanisms of Matplotlib by manipulating figures and axes via the object-oriented API, configure logarithmic and dual scales, perform practical exercises on real datasets to plot lines, bars, and scatters, produce your first customized charts with impactful legends and titles, gain fluency to visualize your analyses instantly.

Module 2Subplots and Layouts: Multiple Grids, Nesting (GridSpec, plt.subplots)

Build complete dashboards by assembling subplots with GridSpec and flexible layouts, chain exercises on concrete cases like multivariate analyses, integrate coherent colors and optimal spacing, test on time series data to create heatmaps and correlation matrices, leave with reusable templates that boost your presentations.

Module 3Advanced Styles and 3D: Themes, Annotations, 3D Projections (mplot3d)

Apply Seaborn-like themes and custom styles for a professional look, add annotations, arrows, and shaded areas through interactive exercises, explore the mplot3d module for 3D surfaces and point clouds on large datasets, simulate real scientific visualizations, master high-resolution exports for immediate publications.

Module 4Integrations and Optimization: Pandas, Automation, Reports (savefig, LaTeX)

Integrate Matplotlib with Pandas for express plots, automate chart generation via scripts and loops, optimize performance on large volumes with adapted backends, finalize with a capstone project on a concrete business case, export to vector PDF and SVG, leave with a portfolio of ready-to-use visualizations.