Online or onsite, instructor-led live Anaconda training courses demonstrate through interactive hands-on practice how to use the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a single platform.
Anaconda 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. Csongrád onsite live Anaconda trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Anaconda, previously Continuum Analytics, is also known as Anaconda Distribution or Anaconda Individual Edition.
NobleProg -- Your Local Training Provider
Szeged
NobleProg Szeged, Maros utca 1., Szeged, hungary, 6721
The NobleProg conference rooms are located in the city center, right next to the garden of the beautiful castle of Szeged and...
The NobleProg conference rooms are located in the city center, right next to the garden of the beautiful castle of Szeged and close to the Tisza river. These conference rooms can be hired as lecture, seminar, teaching or meeting rooms. With natural lighting from two large windows, a variety of artificial lighting options and great technical equipments, such as projector, computers, full sound system with speakers, and internet, this meeting room has great possibilities for successful presentations or trainings. Our professional staff is taking care of the preparation and implementation of the high quality conferences.
This instructor-led, live training in Csongrád (online or onsite) is aimed at data scientists who wish to use the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a single platform.
By the end of this training, participants will be able to:
Install and configure Anaconda components and libraries.
Understand the core concepts, features, and benefits of Anaconda.
Manage packages, environments, and channels using Anaconda Navigator.
Use Conda, R, and Python packages for data science and machine learning.
Get to know some practical use cases and techniques for managing multiple data environments.
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