Online or onsite, instructor-led live Python skope-rules training courses demonstrate through interactive hands-on practice how to use skope-rules to automatically generate rules based on existing data sets.
Python skope-rules 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 Python skope-rules training can be carried out locally on customer premises in Munich or in NobleProg corporate training centers in Munich.
NobleProg -- Your Local Training Provider
Munich
NobleProg München , Landshuter Allee 8-10, München, germany, 80637
Overview
Our training facilities are located at Landshuter Allee 8-10 in Munich. Thanks t...
Overview
Our training facilities are located at Landshuter Allee 8-10 in Munich. Thanks to good transport connections, our spacious training rooms are easy to reach and offer optimal training conditions.
Directions
The NobleProg training facilities are conveniently located not far from the A95 and A96 motorways. The underground station Rotkreuzplatz and the S-Bahn station Donnersbergerbrücke are within walking distance.
Parking spaces
There are numerous free parking spaces around our training rooms.
Local infrastructure
Not far from Landshuter Allee you will find various restaurants and in the nearby Arnulfstrasse there are several hotels.
This course introduces the student to the Python language. Upon completion of this class, the student will be able to write non trivial Python programs dealing with a wide variety of subject matter domains. Topics include language components, working with a professional IDE, control flow constructs, strings, I/O, collections, classes, modules, and regular expressions. The course is supplemented with many hands-on labs, solutions, and code examples.
After Completing the course students will be able to demonstrate knowledge and understanding of Python Security Principles.
In this instructor-led, live training in Munich (onsite or remote), participants will learn how to use Python skope-rules to automatically generate rules based on existing data sets.
By the end of this training, participants will be able to:
Use skope-rules to extract rules from available data.
Apply skope-rules to carry out classification, particularly useful in supervised anomaly detection, or imbalanced classification.
Generate rules for classifying new incoming data.
Fit rules to address real-world problems in fraud detection, predictive maintenance, intrusion detection, insurance application approvals, etc.
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