Microassist

Data Science

Advanced Programming Techniques with Python

Course Overview

Python® continues to be a popular programming language,  due 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.

Course Length

3 days

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Target Audience

This course is designed for existing Python programmers who have at least one year of Python experience and who want to expand their programming proficiency in Python 3.

Course Prerequisites

To ensure your success in this course, you should have experience with object-oriented programming and Python 2.x or 3.x. You can obtain this level of skills and knowledge by taking the following Logical Operations courses:

  • Introduction to Programming with Python®

Course-specific Technical Requirements

Hardware:

For this course, you will need one computer for each student and one for the instructor. Each computer will need the following minimum hardware configurations:

  • 1 gigahertz (GHz) 64-bit (x64) processor.
  • 4 gigabytes (GB) of Random Access Memory (RAM).
  • 32 GB available storage space.
  • Monitor capable of a screen resolution of at least 1,024 × 768 pixels, at least a 256-color display, and a video adapter with at least 4 MB of memory.
  • Bootable DVD-ROM or USB drive.
  • Keyboard and mouse or a compatible pointing device.
  • Fast Ethernet (100 Mb/s) adapter or faster and cabling to connect to the classroom network.
  • IP addresses that do not conflict with other portions of your network.
  • Internet access (contact your local network administrator).
  • (Instructor computer only) A display system to project the instructor’s computer screen.

Software:

  • Microsoft® Windows® 10 (64-bit).
  • Python version 3.9.0 (python-3.9.0.amd64.exe, provided with the course data files).
  • PyCharm Community Edition version 2020.2.3 ( pycharm-community-2020.2.3.exe, provided with the course data files). Python is distributed under the Python Software Foundation License (PSFL). PyCharm Community Edition is distributed under the Apache® License 2.0.
  • MySQL Community Server version 8.0.22 ( mysql-installer-web-community-8.0.22.0.msi, provided with the course data files). MySQL Community Server is distributed under the GPL license.
  • Script to set up the MySQL connector ( Setup MySQL Connector.bat, provided with the course data files).
  • If necessary, software for viewing the course slides. (Instructor machine only.)

Learning Outcomes / Objectives

In this course, you will expand your Python proficiencies. You will:

  • 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.

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Topic List

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