Python Novice to Pythonista - Part 4 Pythonista

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duration: 36 hours |

Language: English (US) |

access duration: 180 days |

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Details

This is part 4 of the Python Novice to Pythonista learning path. Python continues to be one of the fastest growing programming languages on the market today. Because of its ease of use and many supporting frameworks, Python is widely used in web development, script writing, task automation, data science, and even cybersecurity. In this learning path, you will explore the different stages required to become a Pythonista.

This part of the learning path focuses on unit testing, developing and debugging with the PyCharm IDE, dealing with Excel data, network programming, and hashing and encryption algorithms.

You will find several training courses that prepare you to become a Pythonista. In addition, a livelab is available for you to practice. You finish this section with an exam.

Result

After completing this part of the learning path, you will be a true Pythonista. You will have refined your Python knowledge and skills in unit testing, developing and debugging with the PyCharm IDE, dealing with Excel data, network programming, and hashing and encryption algorithms.

Prerequisites

You are familiar with the basics of software development.

You have completed parts 1, 2 and 3 of this learning path.

Target audience

Software Developer, Web Developer

Content

Python Novice to Pythonista - Part 4 Pythonista

36 hours

Introduction to Using PyCharm IDE

PyCharm is one of the most intuitive and feature-rich IDEs available for Python development. Explore some of the important features of this IDE, such as debugging with breakpoints, Python package installation, and even customizing syntax highlighting.

Excel with Python: Working with Excel Spreadsheets from Python

Excel with Python: Working with Excel Spreadsheets from Python

Excel with Python: Performing Advanced Operations

Excel with Python: Performing Advanced Operations

Excel with Python: Constructing Data Visualizations

Excel with Python: Constructing Data Visualizations

Socket Programming in Python: Introduction

Sockets are a means by which two processes or applications can communicate information. Explore the basics of socket programming and see how small bits of data, ranging from simple text to Python objects, can be transferred between applications via sockets.

Socket Programming in Python: Advanced Topics

Socket Programming in Python: Advanced Topics

Python Design Patterns: Working with Creational Design Patterns

Explore the details and implementation of five commonly used creational design patterns - Singleton, Factory, Abstract Factory, Builder, and Object Pool.

Python Design Patterns: Principles of Good Design

  • Explore how the SOLID principles can help to make software

  • designs easier to understand and maintain. Examine the five SOLID
  • principles - Single Responsibility, Open/Closed, Liskov's
  • Substitution, Interface Segregation, and Dependency Inversion - as
  • well as the creational, structural, and behavioral design
  • patterns.

Python Design Patterns: Working with Structural Design Patterns

  • Explore the design and implementation of five commonly used

  • structural design patterns - Adapter, Decorator, Façade, Proxy, and
  • Flyweight. Examine how these patterns can be used for tasks like
  • working with legacy components, dynamically adding
  • responsibilities, offering a simple client interface, controlling
  • object access, and efficiently using lightweight resources.

Python Design Patterns: Working with Behavioral Design Patterns

  • Explore the design and implementation of five commonly used

  • behavioral design patterns - Strategy, Chain of Responsibility,
  • Observer, Command, and Iterator. Examine how these patterns can be
  • used in Python built-in functions, in simple and complex use cases,
  • for performing undo operations, and with Python special
  • methods.

Pythonista

  • Perform development tasks expected of Pythonistas such as debugging with PyCharm, working with spreadsheet data and creating charts, and writing applications that can communicate using TPC sockets. Then, test your skills by answering assessment questions after working with Singleton, Observer and Factory design patterns and implementing iterators using special methods.
  • This lab provides access to tools typically used when developing with Python, including:
  • � Python
  • � Anaconda
  • � Jupyter Notebook + JupyterHub
  • � Pandas, NumPy, SiPy
  • � Seaborn Library
  • � PyCharm IDE
  • � Spyder IDE
  • � MongoDB
  • � MySQL
  • � VS Code
  • This lab is part of the Pythonista track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

Final Exam: Pythonista

  • Final Exam: Pythonista will test your knowledge and application
  • of the topics presented throughout the Pythonista track of the
  • Skillsoft Aspire Python Novice to Pythonista Journey. Learners
  • seeking to test their knowledge and application of Pythonista
  • skills and those seeking to complete the Pythonista track of the
  • Skillsoft Aspire Python Novice to Pythonista Journey.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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