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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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The Training: Mastering NumPy for Data Analysis: Fundamentals and Advanced Practices 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 Training: Mastering NumPy for Data Analysis: Fundamentals and Advanced Practices 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 Training: Mastering NumPy for Data Analysis: Fundamentals and Advanced Practices 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.
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Presentation of NumPy and installation. Understanding ndarrays. Creation, essential properties (shape, dtype, size). Basic operations: initialization, access, modifications. Import and export of simple data.
Operations on arrays: arithmetic, aggregations, basic statistics. Logical operations and filters. Advanced indexing, slicing, axis modification. Using stacking, splitting, and merging methods for arrays. Handling missing data, masking.
Broadcasting and vectorization to accelerate calculations. Efficient manipulation of large data. Introduction to shared memory and views versus copies. Use of universal functions (ufuncs), random, and linspace. Case studies: real-world analysis (prediction, descriptive statistics on large data volumes), integration with Pandas and Matplotlib.
Target audience
Data analysts, scientists, Python developers wishing to optimize their manipulation of numerical data
Prerequisites
Basic knowledge of Python (variables, loops, functions)
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