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. Indiana onsite live SciPy trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
SciPy is also known as Scientific Python.
NobleProg -- Your Local Training Provider
IN, Indianapolis - Lockerbie Marketplace
333 N. Alabama Street Suite 350, Indianapolis, united states, 46204
With its closeness to interstates and a dynamic global transportation infrastructure, as well as downtown amenities, the L...
With its closeness to interstates and a dynamic global transportation infrastructure, as well as downtown amenities, the Lockerbie Marketplace office on N. Alabama Street offers great accessibility. The office occupies the third floor of the smart Sears Building in the heart of Indianapolis’s historic district. Lockerbie Square is where many immigrants settled in the United States. Indianpolis (Indy) is an international city in Marion County that’s home to more than 500 overseas companies. It also has many vibrant sporting events including motoring mainstay, the Indy 500. Indianapolis lays claim to being one of the least expensive large cities in the US. The property is located near Lockerbie Chatham Arch and the main commercial hub of Massachusetts Avenue.
This instructor-led, live training in Indiana (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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