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 Pandas Expert Training - Optimize Massive Data Analyses training are: Advanced proficiency in Python, intermediate Pandas, NumPy, handling large datasets.. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Pandas Expert Training - Optimize Massive Data Analyses training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Pandas Expert Training - Optimize Massive Data A... | 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 Pandas Expert Training - Optimize Massive Data Analyses 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 Pandas Expert Training - Optimize Massive Data Analyses 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 Pandas Expert Training - Optimize Massive Data Analyses 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 Pandas Indexing: MultiIndex, Optimized Slicing (Hierarchical Tools, Groupby Methods)

Dive into MultiIndex to structure multidimensional datasets, practice advanced slicing on real cases like e-commerce logs, chain custom groupby exercises with apply and transform, produce reusable scripts for fast analyses, gain immediate fluency and efficiency on your data projects.

Module 2Pandas Performance: Vectorization, Memory Mapping (Numba Tools, Categoricals)

Optimize memory with categoricals and sparse data, test vectorization on 10GB datasets via timed exercises, integrate Numba to accelerate UDFs, analyze real bottlenecks on Kaggle datasets, deliver production-ready scalable functions, transform your slow workflows into ultra-fast machines.

Module 3Pandas Scalability: Dask, Modin Integration (Distributed Tools, Parallelism)

Scale up with Dask for out-of-memory datasets, migrate Pandas DataFrames to Modin by practicing on simulated clusters, solve massive ETL exercises like IoT streams, generate automated parallel pipelines, master lazy evaluation for x10 gains, boost your productivity on big data.

Module 4Advanced Pandas Pipelines: Custom ETL, Extensions (pdpipe Tools, Extensions API)

Build modular ETL pipelines with pdpipe and custom transformers, apply to banking fraud detection cases, code Pandas extensions via the official API, test robustness on noisy data, produce plug-and-play modules, revolutionize your data processes with expert modularity and reusability.

Module 5Pandas in Production: Real-Time, Deployment (Streaming Tools, Docker Integration)

Process real-time streams with Pandas and Kafka connectors, deploy scalable apps via Docker and FastAPI, simulate production monitoring on live datasets, finalize capstone project with interactive dashboard, secure and optimize for 99% uptime, graduate with full expertise for critical missions.