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 Auckland or in NobleProg corporate training centers in Auckland.
NobleProg -- Your Local Training Provider
Auckland, ANZ Centre
Level 33, ANZ Centre, 23-29 Albert Street, , Auckland, new zealand, 1010
The Regus Business Centre is located on the 33rd floor of the ANZ building which is one of Auckland's most recognisable landm...
The Regus Business Centre is located on the 33rd floor of the ANZ building which is one of Auckland's most recognisable landmarks. The centre offers premium A Grade work space and has recently undergone an extensive refurbishment, making the building one of Auckland’s most sought after CBD addresses. The centre is a short walk to the Viaduct, Queen Street or Wynyard Quarter and has easy access to motorways and is well serviced by public transport. The centre provides an impressive street perspective and expansive views across the Waitemata. ANZ centre is home to some of the most recognised businesses in New Zealand, including major financial institutions, lawyers and insurance companies. The centre offers first-class on-site facilities and amenities including restaurants, retail facilities and banks. The ANZ centre offers a perfect solution for local and overseas companies looking for flexible and fully-equipped offices with comprehensive services at a reasonable price.
In this instructor-led, live training in Auckland (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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