Mastering Python Programming Boot Camp

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

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 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.

• Advanced Python Programming (4 days)
• Intermediate Python for Data Science & Machine Learning (5 days)
• Hands-on Data Analysis using Pandas (3 days)
• Hands-on Predictive Analysis with Python (3 days)
• Intermediate / Next-Level Python for Data Science & Machine Learning (5 days)
• Hands-On Practical Python for Data Wrangling & Transformation (3 days)
• 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