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 Kuala Lumpur or in NobleProg corporate training centers in Kuala Lumpur.
NobleProg -- Your Local Training Provider
Kuala Lumpur KL Sentral
1 Sentral, Level 16, Jalan , Kuala Lumpur, malaysia, 50470
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. A...
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. Although 1 Sentral is just outside the central business district, Kuala Lumpur Sentral is known as a transportation hub and as one of the designated Multimedia Supercorridor (MSC) locations. A Government designated zone, the MSC is designed to leapfrog Malaysia into the information and knowledge age. The zone aims to attract companies with tax breaks and facilities such as high speed internet and proximity to the local international airport. 1 Sentral is a 30-storey office tower covering an acre and is equipped with facilities such as mini auditorium, gymnasium and recreational area. Its architecture has integrated a variety of design techniques that make it eco-friendly and aesthetically-pleasing. Restaurants, top hotels and shopping centres are all within a five- to 10-minute walk from the centre
In this instructor-led, live training in Kuala Lumpur (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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