Description

Description

Python® remains a favored programming language, likely due to its accessible learning curve, minimal code requirements, and adaptability for various purposes including business, web development, and scientific applications. Python proves invaluable for crafting tailored software tools, applications, web services, and cloud-based solutions. In this course, you’ll expand upon your foundational Python proficiency, delving into more sophisticated subjects such as object-oriented programming patterns, graphical user interface development, data manipulation, crafting web service-integrated applications, executing data science operations, conducting unit testing, and constructing and deploying packages and executable applications.

Training Objectives

• Select an object-oriented programming approach for Python applications.
• Create object-oriented Python applications.
• Create a desktop application.
• Create data-driven applications.
• Create and secure web service-connected applications.
• Program Python for data science.
• Implement unit testing and exception handling.
• Package an application for distribution.

Course Outline

• Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications<br />
• Topic A: Implement Object-Oriented Design<
• Topic B: Leverage the Benefits of Object-Oriented Programming<
• Lesson 2: Creating Object-Oriented Python Applications<br />
• Topic A: Create a Class<
• Topic B: Use Built-in Methods<
• Topic C: Implement the Factory Design Pattern<
• Lesson 3: Creating a Desktop Application<br />
• Topic A: Design a Graphical User Interface (GUI)<
• Topic B: Create Interactive Applications<
• Lesson 4: Creating Data-Driven Applications<br />
• Topic A: Connect to Data<
• Topic B: Store, Update, and Delete Data in a Database<
• Lesson 5: Creating and Securing a Web Service-Connected App<br />
• Topic A: Select a Network Application Protocol<
• Topic B: Create a RESTful Web Service<
• Topic C: Create a Web Service Client<
• Topic D: Secure Connected Applications<
• Lesson 6: Programming Python for Data Science<br />
• Topic A: Clean Data with Python<
• Topic B: Visualize Data with Python<
• Topic C: Perform Linear Regression with Machine Learning<
• Lesson 7: Implementing Unit Testing and Exception Handling<br />
• Topic A: Handle Exceptions<
• Topic B: Write a Unit Test<
• Topic C: Execute a Unit Test<
• Lesson 8: Packaging an Application for Distribution<br />
• Topic A: Create and Install a Package<
• Topic B: Generate Alternative Distribution Files<
• Appendix A: Mapping Python Course Content to Python Institute Certification Exams