Intermediate Artificial Intelligence 42 hours

AI Automation with Python: Build 10 Production-Ready Intelligent Systems

Master Python AI automation — build document processors, smart email systems, data pipelines, code reviewers, monitoring tools, and production-ready AI workflows using the Claude API

10 Chapters

40 Lessons

868 min total

Free

Build 10 production-ready AI automations with Python AI automation is one of the highest-paid skills in software: companies everywhere are replacing manual, repetitive work with intelligent systems that run 24/7. This pr...

What you'll learn

Foundations of AI Automation
Project 1 — Intelligent Document Processor
Project 2 — Smart Email Automation System
Project 3 — Automated Data Pipeline with AI
Project 4 — AI Content Generation Engine
Project 5 — AI Code Review and Quality System

+ 4 more chapters below

Engr. Mejba Ahmed

Course Instructor

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Chapters 10

Lessons 40

Duration 42 hours

Level Intermediate

Certificate On Completion

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About This Course

Build 10 production-ready AI automations with Python

AI automation is one of the highest-paid skills in software: companies everywhere are replacing manual, repetitive work with intelligent systems that run 24/7. This project-driven course teaches you to build them — real, deployable automations, not toy scripts — using Python and the Claude API.

After setting up a professional AI-engineering environment and learning to design resilient automation architectures, you build one complete system after another.

The systems you'll build:

Intelligent document processor — PDF parsing, data extraction from unstructured docs, and automated invoice processing
Smart email automation — IMAP + modern auth, AI classification and priority scoring, and context-aware response drafting
Automated data pipeline — web collection, AI-powered cleaning and normalization, and a market-research system
Content generation engine — blog and social pipelines with quality gates, SEO analysis, and automated reporting
AI code review system — codebase understanding, review pipelines, test generation, and Git/PR integration
Monitoring & alerting — log analysis, anomaly detection, and automated incident classification
Multi-modal processor — Claude Vision for image understanding, cataloging, and visual QA
Workflow orchestrator — multi-step, event-driven automations with error recovery and self-correction

You finish with production deployment and a career path — Docker, cost optimization at scale, security and compliance, and the roadmap from AI automator to AI architect.

Who this is for: developers with basic Python who want a portfolio of real, revenue-relevant automation systems. By the end you'll be able to design, build, and deploy intelligent automations businesses will pay for.

Who this course is for

Developers who know the basics and want production skills

Practitioners leveling up in Artificial Intelligence

Builders shipping real-world projects

Best if you're already comfortable with the basics and want production-grade depth.

Course Curriculum

10 chapters 40 lessons 868 min

2 lessons available to preview

1 Why AI Automation Is the Highest-Paid Skill in 2026

Preview 16min

2 Python Environment Setup for AI Engineering

Preview 20min

3 The Anthropic SDK — Your Automation Engine

22min

4 Designing Resilient Automation Architectures

18min

1 Building a PDF Parsing Pipeline with PyMuPDF

24min

2 AI-Powered Data Extraction from Unstructured Documents

22min

3 Automated Invoice Processing and Validation

26min

4 Building the Complete Document Intelligence API

20min

1 Connecting to Email with IMAP and Modern Auth

20min

2 AI Email Classification and Priority Scoring

22min

3 Automated Response Drafting with Context Awareness

24min

4 Building the Full Email Automation Service

20min

1 Web Data Collection with httpx and BeautifulSoup

22min

2 AI-Powered Data Cleaning and Normalization

20min

3 Building an Automated Market Research System

24min

4 Scheduling and Monitoring Your Data Pipelines

18min

1 Building a Blog Content Pipeline with Quality Gates

22min

2 Social Media Content Generation at Scale

20min

3 SEO Optimization with AI-Powered Analysis

24min

4 Automated Report Generation from Raw Data

22min

1 Parsing Code and Understanding Codebases

24min

2 Building an AI Code Review Pipeline

22min

3 Automated Test Generation and Coverage

26min

4 Git Integration and PR Review Automation

20min

1 Building a Log Analysis Pipeline

22min

2 AI-Powered Anomaly Detection in Metrics

24min

3 Automated Incident Classification and Routing

20min

4 Building a Self-Monitoring System Dashboard

22min

1 Image Understanding with Claude Vision

22min

2 Automated Image Cataloging and Tagging

20min

3 Building a Visual QA System

24min

4 Multi-Modal Document Understanding

22min

1 Designing Complex Multi-Step Workflows

24min

2 Building an Event-Driven Automation System

22min

3 Error Recovery and Self-Correcting Workflows

20min

4 Composing Pipelines into Production Workflows

24min

1 Containerizing AI Automations with Docker

22min

2 Cost Optimization — Running AI at Scale

20min

3 Security, Compliance, and Responsible Automation

24min

4 Career Roadmap — From AI Automator to AI Architect

18min

Your Instructor

Engr. Mejba Ahmed

AI Developer · Software Engineer · Entrepreneur

I build production AI systems and full-stack applications for a living, and I teach the exact workflows I use in real projects — not theory. Over 8+ years I've shipped 1,500+ projects, founded Ramlit Limited, and now build agentic AI tooling with Claude, GPT and open models. AI School is where I share that hands-on playbook so you can build and ship real work.

8+ years in production 1,500+ projects shipped Founder, Ramlit Limited