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. Federal District onsite live Python skope-rules trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Mexico City - Mariano Escobedo
Mariano Escobedo 510, Ciudad de Mexico, mexico, 11590
The Mexico City Mariano Escobedo Center is on the 12th floor and penthouse of a tall, slimline commercial building with bold ...
The Mexico City Mariano Escobedo Center is on the 12th floor and penthouse of a tall, slimline commercial building with bold vertical detailing giving it instant kerb-appeal.
Mexico City - Cygni Santa Fe
Alfonso Nápoles Gandara 50, Mexico City, mexico, 1210
The Mexico City Cygni Santa Fé Center is on the top floor of a four-story building that is one of Mexico City's foremost bus...
The Mexico City Cygni Santa Fé Center is on the top floor of a four-story building that is one of Mexico City's foremost business addresses. It has landscaped grounds and an imposing entrance, and the center enjoys incredible views across to the high-rise skyline of Santa Fé, a leading district for financial services businesses.
In this instructor-led, live training in Federal District (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.
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.
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