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 NumPy Initiation - Master arrays to boost your analyses training are: Python basics: variables, lists, loops, simple functions. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training NumPy Initiation - Master arrays to boost your analyses training is available in remote. The format can be adapted to your needs (inter, intra, custom).

Training NumPy Initiation - Master arrays to boo... | 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 NumPy Initiation - Master arrays to boost your 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 Training NumPy Initiation - Master arrays to boost your 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 Training NumPy Initiation - Master arrays to boost your 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 objectives

Install and import NumPy in your Python environment

Create and manipulate multidimensional arrays

Perform vectorized arithmetic operations

Master indexing, slicing, and reshaping

Apply NumPy to real-world data analysis cases

Optimize calculations to speed up your scripts

Integrate NumPy with Pandas for seamless workflows

Training program

Module 1Introduction to NumPy: installation and first arrays (basic tools, arrays)

Discover NumPy by installing the library via pip, import it into Jupyter Notebook, create your first arrays from lists or zeros, explore attributes like shape and dtype through interactive exercises, manipulate real data to visualize immediate performance gains, produce your first optimized scripts that will make you want to dive deeper.

Module 2Creating and manipulating NumPy arrays: advanced methods (np.array, linspace)

Dive into array creation with np.array, np.linspace, and np.arange, resize with reshape and transpose, concatenate via np.concatenate in practical cases on sales datasets, test broadcasts for intuitive operations, generate random matrices to simulate data, leave with ready-to-use notebooks that transform your daily workflows.

Module 3Vectorized mathematical operations: efficient calculations (add, multiply, stats)

Speed up your calculations with universal functions like add, subtract, and multiply on large arrays, compute means and standard deviations via np.mean and np.std on financial datasets, vectorize complex formulas without slow loops, compare before/after performance in timed exercises, produce integrated Matplotlib graphs to validate your impactful results.

Module 4Indexing, slicing, and booleans: precise data access (fancy indexing)

Master advanced slicing, boolean indexing, and fancy indexing to filter customer data in the blink of an eye, apply masks on multidimensional arrays in real marketing analyses, selectively modify values with where, optimize complex queries, leave confident with techniques that multiply your efficiency by 10 on concrete projects.

Module 5Advanced functions and NumPy projects: practical integration (eigen, FFT, data cases)

Synthesize with np.linalg for eigenvalues, explore FFT for signals, integrate NumPy with Pandas on a final predictive analysis project, debug common errors in a group, optimize a complete script to process 1 million rows in seconds, earn a certification and reusable templates that boost your data career.