Python Automation Course

Lesson 1 • Working with Built-in Data Structures

Manipulate lists, tuples, dictionaries, and sets to store and process automation data. Choosing the right structure directly impacts script efficiency.

Lesson 2 • Error Handling and Debugging Basics

Use try/except blocks and debugging tools to write resilient scripts. Automation scripts must handle unexpected states without crashing.

Lesson 3 • Functions and Code Reusability

Define, call, and organize functions to eliminate repetition in automation code. Introduces scope and return values critical for modular script design.

Lesson 4 • Core Python Syntax Essentials

Cover variables, data types, operators, and control flow constructs. These primitives underpin every automation script written later in the course.

Lesson 1 • OS-Level Task Automation

Execute shell commands, manage processes, and interact with environment variables from Python. Bridges Python scripts with the underlying operating system.

Lesson 2 • Path and Directory Management

Navigate and manipulate the file system using the pathlib and os modules. Reliable path handling prevents broken scripts across different operating systems.

Lesson 3 • Reading and Writing Files

Open, read, write, and close text and binary files using Python's built-in file API. File I/O is the entry point for most real-world automation tasks.

Lesson 4 • Working with CSV and JSON Files

Parse and generate CSV and JSON data, the two most common formats in automation pipelines. Connects file I/O skills to structured data processing.

Lesson 1 • Making HTTP Requests with Requests

Use the requests library to send HTTP calls, handle responses, and manage sessions. Provides the core toolset for API and web automation tasks.

Lesson 2 • Parsing HTML with BeautifulSoup

Extract structured data from raw HTML using BeautifulSoup selectors and traversal methods. Enables scraping of websites that do not expose a public API.

Lesson 3 • HTTP Fundamentals for Automation

Understand HTTP methods, status codes, headers, and request/response cycles. This knowledge is required before sending any automated web request.

Lesson 4 • Consuming and Automating REST APIs

Authenticate, paginate, and automate workflows against REST APIs. Connects HTTP skills to real integration scenarios used in professional environments.

Lesson 1 • Selenium Setup and Browser Control

Install Selenium, configure WebDriver, and open, navigate, and close browsers from Python. Establishes the foundation for all browser automation tasks.

Lesson 2 • Locating and Interacting with Elements

Find page elements using ID, CSS, XPath, and other locators, then click, type, and select. Element interaction is the core action in any browser automation script.

Lesson 3 • Automating Forms and Login Flows

Build scripts that log in, fill multi-step forms, and handle authentication challenges. Covers the most common real-world browser automation use case.

Lesson 4 • Advanced Selenium Techniques

Execute JavaScript, handle alerts, switch frames, and scrape data from complex pages. Extends core Selenium skills to handle edge cases in production scripts.

Lesson 1 • Introduction to pandas for Automation

Load, inspect, and filter tabular data using DataFrames. pandas is the primary tool for data-driven automation tasks in this course.

Lesson 2 • Data Transformation and Aggregation

Apply functions, group data, and compute summaries to transform raw data into insights. Transformation is the core step in any data automation pipeline.

Lesson 3 • Data Validation and Quality Checks

Write automated checks that detect duplicates, outliers, and schema violations in datasets. Data quality gates prevent errors from propagating through automation pipelines.

Lesson 4 • Automating Excel with openpyxl

Read, write, and format Excel workbooks programmatically using openpyxl. Enables full replacement of manual Excel reporting with automated Python scripts.

Lesson 1 • Monitoring and Alerting for Automation Jobs

Implement health checks, failure alerts, and run metrics to keep automation systems observable. Monitoring transforms a script into a production-grade automation service.

Lesson 2 • Introduction to Workflow Orchestration Tools

Survey orchestration platforms such as Apache Airflow and Prefect for managing complex DAG-based workflows. Prepares students for enterprise-scale automation environments.

Lesson 3 • Building Multi-Step Automation Pipelines

Chain discrete automation tasks into sequential and conditional pipelines. Pipeline design separates concerns and makes complex workflows maintainable.

Lesson 4 • Scheduling Scripts on the OS Level

Configure cron jobs on Linux/macOS and Task Scheduler on Windows to trigger Python scripts. OS-level scheduling is the simplest path to unattended automation.

Lesson 1 • Concurrency with Threading and Asyncio

Speed up I/O-bound automation tasks using threads and async/await patterns. Concurrency is essential when scripts must process hundreds of API calls efficiently.

Lesson 2 • Advanced API Authentication Patterns

Implement OAuth2 flows, JWT handling, and API key rotation in automation scripts. Secure authentication is mandatory for production API integrations.

Lesson 3 • Resilient Error Handling at Scale

Apply exponential backoff, circuit breakers, and dead-letter queues to large-scale automation. Resilience patterns prevent cascading failures in production systems.

Lesson 4 • Webhook Receivers and Event-Driven Automation

Build lightweight Flask endpoints that receive webhook payloads and trigger automation logic. Event-driven design eliminates polling and reduces latency.

Lesson 1 • Version Control with Git for Automation

Apply Git workflows to track changes, collaborate, and roll back automation scripts safely. Version control is a non-negotiable practice for production automation.

Lesson 2 • CI/CD Pipelines for Automation Projects

Automate testing, linting, and deployment using CI/CD pipelines triggered by Git events. CI/CD ensures every code change is validated before reaching production.

Lesson 3 • Deploying to Cloud and Serverless Platforms

Deploy automation scripts to cloud VMs, managed containers, and serverless functions. Cloud deployment enables 24/7 unattended execution at minimal cost.

Lesson 4 • Structuring Automation Projects Professionally

Organize code into modules, packages, and configuration files following Python best practices. Good structure makes automation projects maintainable and team-friendly.