Key points about this course

Duration : 3 Days
Public Class : RM 4,500.00
Live Virtual Class : RM 3,600.00

HRD Corp Claimable Course

PCPP1: Certified Professional in Python Programming 1
Exam Code : PCPP-32-101

Live Virtual Class

Public Class

In-House Training

Private Class

Course Overview

PCPP – Certified Professional in Python Programming certifications (PCPP-32-1xx and PCPP-32-2xx) are professional credentials that measure your ability to accomplish coding tasks related to advanced programming in the Python language and related technologies, advanced notions and techniques used in object-oriented programming, selected library modules (file processing, communicating with a program’s environment; mathematics-, science-, and engineering-oriented modules), GUI programming, network programming, as well as creating tools, frameworks and complete systems.

PCPP1 – Certified Professional in Python Programming 1 certification shows that the individual is familiar with the more advanced perspective of classes and features of object-oriented programming. The scope of certification also includes graphical user interface programming, as well as working with selected library modules allowing to process different kinds of files, communicate with a program’s environment, and utilize tools and resources for the purposes of carrying out math-, science-, and engineering-related tasks.

Becoming PCPP1 certified ensures that the individual is fully acquainted with all the advanced means provided by Python 3 and related technologies to enable her/him to advance her/his career as a professional Python developer.

Course Prerequisites

PCAP | Certified Associate in Python Programming Certification (PCAP-31-02 or PCAP-31-01)

Course Content

Module 1: File Processing and Communicating with a Program’s Environment

Objectives covered by the module 

  • Processing different kinds of files
    • sqlite3– interacting with SQLite databases
    • xml– creating and processing XML files
    • csv– CSV file reading and writing
    • logging– basics logging facility for Python
    • configparser– configuration file parser
  • Communicating with a program’s environment:
    • os– interacting with the operating system,
    • datetime– manipulating with dates and time
    • io– working with streams,
    • time– time access and conversions

Module 2: Math, Science, and Engineering Tools

Objectives covered by the module

  • math – a basic tool for elementary evaluations
  • NumPy – fundamental package for scientific computing
  • SciPy – an ecosystem for mathematics, science, and engineering
  • Matplotlib – 2D plotting library producing publication quality figures
  • Pandas – a library providing high-performance and data analysis tools
  • SciKit-image – a collection of algorithms for image processing

Module 3: GUI Programming

Objectives covered by the module

  • What is GUI and where it comes from
  • Constructing a GUI – basic blocks and conventions
  • Event-driven programming
  • Currently used GUI environments and toolkits
  • tkinter— Python interface to Tcl/Tk
    • tkinter’s application life cycle
    • Widgets, windows and events
    • Sample applications
  • pygame– a simple way of developing multimedia applications

Module 4: Python Enhancement Proposals

Objectives covered by the block

  • What is PEP?
  • Coding conventions – not only style and naming
  • PEP 20 – The Zen of Python: a collection of principles that influences the design of Python code
  • PEP 8 – Style Guide for Python Code: coding conventions for code comprising the standard library in the main Python distribution
  • PEP 257 – Docstring Conventions: what is docstring and some semantics as well as conventions associated with them
  • A tour of important PEPs

Module 5: Advanced Perspective of Classes and Object-Oriented Programming in Python

Objectives covered by the module

  • Classes, Instances, Attributes, Methods
  • Working with class and instance data
  • Copying object data using shallowand deep operations
  • Inheritance and Polymorphism
  • Different faces of Python methods: staticand class methods
  • Abstract classes vs. method overloading
  • Composition vs. Inheritance – two ways to the same destination
  • Implementing Core Syntax
  • Subclassing built-ins
  • Attribute Encapsulation
  • Advanced techniques of creating and serving exceptions
  • Serialization of Python objects using the picklemodule
  • Making Python object persistent using the shelvemodule
  • Metaprograming
    • Function decorators
    • Class decorators
    • Metaclasses

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