Online or onsite, instructor-led live Mathematica training courses in Oeiras.
Hotel Real Oeiras
nº5, R. Álvaro Rodrigues de Azevedo nº 5, 2770-197 Paço de Arcos, Paço de Arcos, Portugal, 2770-197 Paço de Arcos
With a privileged location near the business hubs of Oeiras, such as Lagoas Park, Tagus Park, and Quinta da Fonte, the Hotel ...
With a privileged location near the business hubs of Oeiras, such as Lagoas Park, Tagus Park, and Quinta da Fonte, the Hotel Real Oeiras is a 4-star hotel that offers all the conditions to organize all types of meetings and social events.
Whether it’s a business meeting, a congress, a business event, a social event, a dinner or a private lunch, a marriage, a baptism, an anniversary party or even if it’s an amusing child anniversary, the 8 multipurpose rooms are the ideal option.
With every room having natural light and direct access to the outdoor swimming pool and to the surrounding green areas, this hotel is the perfect choice to make your event memorable.
Introduces the core technologies needed to become an adept user of Mathematica, including the Wolfram Language, the notebook interface, programming fundamentals, visualization and interactivity features, and mathematics and statistics functionality. Small class sizes allow for interaction with the instructor, and in-person courses allow additional time for discussion, exercises, and Q&A.
The "Mathematica - wprowadzenie, wizualizacja i prezentacja danych" training is aimed at participants with basic mathematical knowledge. Mathematica, as a powerful mathematical engine, enables effective calculations, creating text documents, building charts and presenting data. Participants will gain practical skills in working with Mathematica, used, among others, in mathematics, physics, biology, financial analysis and other fields.
This instructor-led, live training in Oeiras (online or onsite) is aimed at data scientists who wish to use machine learning in Mathematica for data analysis.
By the end of this training, participants will be able to:
Build and train machine learning models.
Import and prepare data for machine learning.
Separate training data from test data.
Explore deep learning and neural network applications in data analysis.
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