By the end of this expert-led, hands-on course, you will have the skills to write more efficient, organized, and professional Python code. You will build confidence in using Python for real-world applications, from automating tasks to handling complex data and building scalable programs.

Here are a few of the key skills you will gain:

Write More Efficient and Readable Code – Use Python’s advanced data structures, functional programming techniques, and best practices to make your code cleaner, faster, and easier to maintain.

Automate System and File Operations – Work with OS services, process files and directories, launch external programs, and manage system tasks with Python scripts.

Work with Databases and APIs – Connect to SQL databases, execute queries, and integrate with web services using Python’s database libraries and HTTP request tools.

Improve Debugging and Code Performance – Use debugging tools, performance profiling, and unit testing with PyTest to identify issues and optimize your programs.

Handle Concurrency and Parallel Processing – Write more responsive and scalable programs using threading, multiprocessing, and asynchronous programming techniques.

Build Applications and Process Data Effectively – Develop GUI applications with PyQt, process structured data formats like JSON, XML, and YAML, and serialize data for storage and exchange.

With 50% hands-on practice and expert guidance, you will not only learn these skills—you will apply them, ensuring you leave the course ready to take on more complex Python projects with confidence.

If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals.

This intermediate and beyond level course is designed for professionals who have basic Python experience and want to deepen their skills for more advanced programming, automation, and application development. It is ideal for software developers, data analysts, system administrators, and engineers looking to write more efficient code, work with real-world data, and build scalable applications.

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change and may adjust during live delivery based on audience skill level, interests and participation.

1. Python refresher

Builtin data types

Lists and tuples

Dictionaries and sets

Program structure

Files and console I/O

If statement

for and while loops

2. OS Services

The os and os.path modules

Environment variables

Launching external commands with subprocess

Walking directory trees

Paths, directories, and filenames

Working with file systems

3. Dates and Times

Basic date and time classes

Different time formats

Converting between formats

Formatting dates and times

Parsing date/time information

4. Binary Data

What is Binary Data?

Binary vs text

Using the Struct module

5. Pythonic Programming

The Zen of Python

Tuples

Advanced unpacking

Sorting

Lambda functions

List comprehensions

Generator expressions

String formatting

6. Functions, modules, and packages

Four types of function parameters

Four levels of name scoping

Single/multi dispatch

Relative imports

Using init effectively

Documentation best practices

7. Intermediate classes

Class/static data and methods

Inheritance (or composition)

Abstract base classes

Implementing protocols (context, iterator, etc.) with special methods

8. Metaprogramming

Implicit properties

globals() and locals()

Working with object attributes

The inspect module

Callable classes

Decorators

Monkey patching

9. Developer Tools

Analyzing programs with pylint

Using the debugger

Profiling code

Testing speed with benchmarking

10. Unit testing with PyTest

What is a unit test?

Writing tests

Working with fixtures

Test runners

Mocking resources

11. Database access

The DB API

Available Interfaces

Connecting to a server

Creating and executing a cursor

Fetching data

Parameterized statements

Using Metadata

Transaction control

ORMs and NoSQL overview

12. PyQt

Overview

Qt Architecture

Using designer

Standard widgets

Event handling

Extras

13. Network Programming

Builtin classes

Using requests

Grabbing web pages

Sending email

Working with binary data

Consuming RESTful services

Remote access (SSH)

14. Multiprogramming

The threading module

Sharing variables

The queue module

The multiprocessing module

Creating pools

About async programming

15. Scripting for System Administration

Running external programs

Parsing arguments

Creating filters to read text files

Implementing logging

16. Serializing data

Parsing XML with ElementTree

Updating the XML tree

Creating new XML documents

Reading/Writing JSON data

Reading/writing CSV data

YAML, other formats

Time Permitting Chapters

17. Virtual Environments

Use case for

Creating an environment

Activating and deactivating

Replicating an environment

Useful tools

18. Type hinting

Annotate variables

Learn what type hinting does NOT do

Use the typing module for detailed type hints

Understand union and optional types

Write stub interfaces

19. Advanced data handling

Discover the collections module

Use defaultdict, Counter, and namedtuple

Create dataclasses

Store data offline with pickle