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Training NumPy - Accelerate Your Python Scientific Calculations

Ref: YDQ537
10 people max.
4400€ HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
4 journées
distanciel

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Learning objectives

  • Master advanced NumPy arrays to boost professional skills.
  • Develop optimized vectorized operations for enterprise data analysis.
  • Design efficient algorithms using broadcasting and multidimensional indexing.
  • Implement linear and statistical functions for certified applications.
  • Optimize memory and CPU performance in real-world data science projects.
  • Integrate NumPy into professional Python workflows for increased productivity.

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Advanced NumPy Arrays: Creation, Indexing, and Slicing (Vectorized Tools, Practical Exercises)

Discover advanced NumPy array creation techniques, from zero-copy to memory views, applied to real datasets. Practice boolean and fancy indexing to extract complex data, followed by exercises on reshaping and transposition. Analyze real enterprise cases, produce immediate visualizations with integrated Matplotlib, and validate your skills through a mini-project on scientific matrix manipulation.

Module 2NumPy Operations: Vectorization and Broadcasting (Ufunc Methods, Optimized Performance)

Dive into vectorization to accelerate calculations, explore universal functions (ufuncs) like add and multiply on large data volumes. Master automatic broadcasting for multidimensional operations without slow Python loops, test on physical simulations. Solve real enterprise problems with before/after benchmarks, generate performance reports, and integrate tips to avoid common production data pitfalls.

Module 3NumPy Linear Algebra: Matrices, Decompositions, and Statistics (Linalg, Polynomials, Analytical Deliverables)

Deepen linear algebra with linalg.dot, inv, eig to solve linear systems and simplified PCA. Calculate means, standard deviations, correlations on massive datasets via numpy.stats, apply to concrete AI cases. Develop predictive analysis scripts, visualize results with histograms and scatter plots, produce ready-to-use enterprise report deliverables, and optimize with random for fast Monte Carlo simulations.

Module 4NumPy Optimization and Integration: Performance, Pandas, SciPy (Best Practices, Final Certified Project)

Optimize memory with strides and masked arrays for large datasets, integrate NumPy with Pandas and SciPy for complete data pipelines. Profile with %timeit, apply basic Cython for x100 gains, test on real enterprise cases like financial modeling. Conclude with a capstone project: full-stack predictive analysis, personalized debriefing, and access post-training resources for immediate certified implementation.

Evaluation method

  • Daily interactive quizzes on the remote platform to validate NumPy skills.
  • Graded practical exercises with real-time feedback from expert trainers.
  • Final personal project: optimization of a data algorithm, graded and Qualiopi certified.

Learning method

  • 70/20/10 approach: 70% hands-on NumPy practice, 20% peer exchanges, 10% targeted theory.
  • Hands-on exercises on shared Jupyter Notebook in live remote sessions.
  • Real enterprise data use cases for immediate professional application.
  • Unlimited access to replays and resources for 6 months post-training for review.

Methods, materials and delivery

The Training NumPy - Accelerate Your Python Scientific Calculations program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training NumPy - Accelerate Your Python Scientific Calculations program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training NumPy - Accelerate Your Python Scientific Calculations program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
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« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
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« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
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« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
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« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
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« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

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