Instructor-led training

Advanced Programming Techniques with Python Training in Radford, Virginia

Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses.

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What you'll learn

Python continues to be a popular programming language, perhaps owing to its easy learning curve, small code footprint, and versatility for business, web, and scientific uses. Python is useful for developing custom software tools, applications, web services, and cloud applications. In this course, you'll build upon your basic Python skills, learning more advanced topics such as object-oriented programming patterns, development of graphical user interfaces, data management, creating web service-connected apps, performing data science tasks, unit testing, and creating and installing packages and executable applications.

Prerequisites

To ensure your success in this course, you should have experience with object-oriented programming and Python 2.x or 3.x.

Course Outline

Lesson 1: Selecting an Object-Oriented Programming Approach for Python Applications

Topic A: Implement Object-Oriented Design

Topic B: Leverage the Benefits of Object-Oriented Programming

Lesson 2: Creating Object-Oriented Python Applications

Topic A: Create a Class

Topic B: Use Built-in Methods

Topic C: Implement the Factory Design Pattern

Lesson 3: Creating a Desktop Application

Topic A: Design a Graphical User Interface (GUI)

Topic B: Create Interactive Applications

Lesson 4: Creating Data-Driven Applications

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

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

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

Topic A: Handle Exceptions

Topic B: Write a Unit Test

Topic C: Execute a Unit Test

Lesson 8: Packaging an Application for Distribution

Topic A: Create and Install a Package

Topic B: Generate Alternative Distribution Files

Appendix A: Mapping Python Course Content to Python Institute Certification Exams

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