Online or onsite, instructor-led live SciPy training courses demonstrate through interactive hands-on practice how to use SciPy to create advanced scientific computing functions with Python.
SciPy training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live SciPy training can be carried out locally on customer premises in Limoges or in NobleProg corporate training centers in Limoges.
SciPy is also known as Scientific Python.
NobleProg -- Your Local Training Provider
Limoges, City Center
NobleProg Limoges, 50 Boulevard Gambetta, Limoges, France, 87000
The nearest airport to the training center: Limoges International Airport
Nearest train station: Limoges-Bénédictins train...
The nearest airport to the training center: Limoges International Airport
Nearest train station: Limoges-Bénédictins train station
Nearest parking lot to training center: Parking Place d'Aine
Nearby cafés, restaurants and bars: Restaurant ESCROCS, Restaurant Le Glacier, Bar Le Duc Etienne
Training can also be organized on your premises in Strasbourg or remotely. The 3rd option is to rent a room specifically for the duration of the course.
Training sessions can be given in English or French. For each session, we organize a coordination call with the trainer and participants to adapt the program to your expectations and level. Training includes theory, discussion, questions/answers and practical exercises.
Remote training is delivered via DaDesktop for training, a software package published by NobleProg that enables participants to have a workstation (VM) set up specifically for the training.
This instructor-led, live training in Limoges (online or onsite) is aimed at developers who wish to use SciPy to create advanced scientific computing functions with Python.
By the end of this training, participants will be able to:
Set up the necessary development environment to start creating scientific computing functions.
Get the full benefit of SciPy features by performing practical examples of complex operations.
Implement and optimize mathematical algorithms and functions to solve scientific problems.
Design data structures and interpolation methods for visualization, processing, and analysis.
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