Mastering Python Programming Boot Camp (TTPS4820)

Course Objectives

Learning Objectives

This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you’ll learn how to:

• Create working Python scripts following best practices
• Use python data types appropriately
• Read and write files with both text and binary data
• Search and replace text with regular expressions
• Get familiar with the standard library and its work-saving modules
• Use lesser known but powerful Python data types
• Create real-world, professional Python applications
• Work with dates, times, and calendars
• Know when to use collections such as lists, tuples, dictionaries, and sets
• Understand Pythonic features such as list comprehensions and generators
• Write robust code using exception handling
• Create and use virtual environments

Need different skills or topics?  If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate.  We offer additional python, web development, data science, machine learning and other related topics that may be blended with this course for a track that best suits your needs. Our team will collaborate with you to understand your needs and will target the course to focus on your specific learning objectives and goals.

Course Prerequisites

Audience

This course is geared for technical users who are new to Python. Roles might include developers, software engineers, data analysts who want to enhance data processing, system administrators and web site administrators who want to use Python to support their server installations, developers who want more efficient web solutions, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts.

If you are coming from a non-technical background, you might consider the TTPS4803: Python for Everyone: Getting Started with Python Basics for Non-Developers (4 days) as an alternative to this course.

Pre-Requisites

To ensure a smooth learning experience and maximize the benefits of attending this course, you should have the following prerequisite skills:

• At least some prior hands-on experience with scripting or programming. You don’t need to be an expert in either, but you should have had some exposure and should be coming from a technical background.
• Working with Unix or Linux, and familiarity with using the command line interface for simple tasks, such as file navigation and executing commands.
• Basic familiarity working with text editors like Notepad, or IDEs, would be helpful as the course includes hands-on lab sessions requiring code editing.

Take After/ Follow On: We offer a wide variety of follow-on courses and learning paths for leveraging Python for next-level development, data science and analytics, AI and machine learning, automation, testing, networking, security and more.  The following course(s) might serve as good next steps in your learning journey.  Please see our site for a complete list.

• TTPS4850      Advanced Python Programming (4 days)
• TTPS4876      Intermediate Python for Data Science & Machine Learning (5 days)
• TTPS4878      Hands-on Data Analysis using Pandas (3 days)
• TTPS4879      Hands-on Predictive Analysis with Python (3 days)
• TTPS4876      Intermediate / Next-Level Python for Data Science & Machine Learning (5 days)
• TTPS4880      Hands-On Practical Python for Data Wrangling & Transformation (3 days)
• TTPS4883      Forecasting, Behavioral Analysis, and What-If Scenarios with Python (3 days)

Course Agenda

1. The Python Environment

• Starting Python
• Using the interpreter
• Running a Python script
• Editors and IDEs

2. Variables and Values

• Using variables
• Builtin functions
• String data
• Numeric data
• Converting types

3. Basic input and output

• Writing to the screen
• String formatting
• Command line arguments
• Reading the keyboard

4. Flow Control

• About flow control
• The if statement
• Relational and Boolean values
• while loops
• Exiting from loops

5. Array types

• Sequence types in general
• Lists and list methods
• Tuples
• Indexing and slicing
• Iterating through a sequence
• Sequence functions, keywords, and operators
• List comprehensions and generators

6. Working with files

• File I/O overview
• Opening a text file
• Reading a text file
• Writing to a text file

7. Dictionaries and Sets

• About dictionaries
• Creating dictionaries
• Getting values
• Iterating through a dictionary
• About sets
• Creating sets
• Working with sets

8. Functions

• Defining functions
• Returning values
• Parameters and arguments
• Variable scope

9. Sorting

• The sorted() function
• Custom sort keys
• Lambda functions
• Sorting in reverse
• Using min() and max()

10. Exception handling and logging

• Exceptions
• Using try/catch/else/finally
• Handling multiple exceptions
• Logging setup
• Basic logging

11. Modules and Packages

• Creating Modules
• The import statement
• Module search path
• Using packages
• Function and Module aliases

12. Introduction to Classes

• About object-oriented programming
• Defining classes
• Constructors
• Understanding self
• Properties
• Instance Methods and data
• Class methods and data
• Inheritance

13. Regular Expressions

• RE syntax overview
• RE objects
• Searching and matching
• Compilation flags
• Groups and special groups
• Search-and-replace
• Splitting strings

14. Dates and times

• Date and time representations
• Parsing dates from text
• Formatting as text
• Converting representations
• Calendar data
• Time zones

15. Working with the file system

• Paths, directories, and filenames
• Checking for existence
• Permissions and other file attributes
• Walking directory trees
• Using shutil for file operations

16. Advanced data handling

• Defaultdict and Counter
• Pretty-printing data structures
• Compressed archives (zip, gzip, tar, etc.)
• Persistent data

17. Network programming

• Using requests
• Grabbing web content
• Sending email
• Using SSH for remote access
• Using FTP

18. Effective Scripts

• Reading input files a la Unix
• Parsing command-line options
• Detecting the current platform
• Implementing logging

19. Virtual Environments

• Why are virtual environments needed
• Creating a virtual env
• Replicating an environment
• Virtual environment issues

Addendum & Resources

Course Materials

Setup Made Simple! Learning Experience Platform (LXP) 

All applicable course software, digital courseware files or course notes, labs, data sets and solutions, live coaching support channels, CodeCoach.AI anytime tutor access, and rich extended learning and post training resources are provided for you in our “easy access, single source, no install required” online Learning Experience Platform (LXP), remote lab and content environment. Access periods vary by course. We’ll collaborate with you to ensure your team is set up and ready to go well in advance of the class. Please inquire about set up details and options for your specific course of interest.