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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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Don't let this gap widen
Without this advanced NumPy training, your Python scripts remain slow: a data scientist loses an average of 20% of time on non-vectorized loops, leading to project delays multiplied by 3 and unnecessary exploding cloud costs of 500€/month.
Broadcasting errors generate silent bugs, skewing 15% of ML analyses and costing thousands of euros in rework.
Miss optimized ufuncs, and your massive datasets (1GB+) crash, blocking critical insights.
70% of professionals admit to stagnating without advanced expertise, missing promotions and innovative projects.
Invest 21 hours to multiply your productivity x10, avoid these pitfalls, and dominate data processing.
The Advanced NumPy Training - Optimize Your Massive Calculations in 3 Days 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.
To ensure the quality of the Advanced NumPy Training - Optimize Your Massive Calculations in 3 Days training, Learni provides the following 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.
The assessment of skills acquired during the Advanced NumPy Training - Optimize Your Massive Calculations in 3 Days training is carried out through:
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.
Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Dive into fancy indexing and array views to manipulate massive datasets without unnecessary copies, perform exercises on real matrices from scientific simulations, create boolean masks to filter noisy data, produce immediate visualizations with integrated Matplotlib, and validate your skills via a mini image preprocessing project, while gaining execution speed from the first session.
Discover magical broadcasting for operations on arrays of varying shapes without slow loops, implement custom ufuncs to accelerate your custom calculations, test on concrete cases like time series signal analysis, measure performance gains with timeit, optimize memory via strides, and build a vectorized ML algorithm prototype, for results 10x faster that will boost your data projects.
Integrate NumPy with Pandas for powerful DataFrames and with SciPy for advanced statistics, develop a complete pipeline on a real Kaggle dataset, profile performance with Numba and Cython, fix common memory leaks, deploy a final deliverable like an optimized ready-to-use module, and leave with pro tips to scale your big data applications in production.
Target audience
Data scientists, machine learning engineers, data analysts seeking to advance their skills in advanced NumPy.
Prerequisites
Mastery of intermediate Python, NumPy basics (arrays, slicing, elementary vectorized operations).
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