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. Dresden onsite live Python skope-rules trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Our training facilities are located at Weißeritzstrasse 30 in Dresden. Our spacious t...
Overview
Our training facilities are located at Weißeritzstrasse 30 in Dresden. Our spacious training rooms are located directly west of Dresden's old town and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the tram stop Kongresszentrum and the A17 motorway is also easily accessible.
Parking
The Mitte multi-storey car park, right around the corner, offers guarded parking spaces.
Local Services
Within walking distance is the Leonardo Hotel Dresden Altstadt, other hotels and a variety of restaurants are also nearby.
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 Dresden (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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