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Udemy

Build an AI Automated Ordering System with Python & AWS

via Udemy

Overview

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Master Demand Forecasting, Docker, Lambda, and Logistics Logic. bridging the gap between AI modeling and real-world SCM

What you'll learn:
  • Build a serverless AI application using Python, Docker, and AWS Lambda.
  • Implement machine learning demand forecasting using Scikit-learn and Pandas.
  • Design real-world logistics logic, such as safety stock and lead time calculation.
  • Automate data workflows using DynamoDB Streams and S3 for audit logging.

"I built an AI model, but I don't know how to apply it to real business problems."

Does this sound familiar? This course is not just a programming tutorial; it is a practical development guide designed to solve real-world logistics challenges using AWS and Python.

We bridge the gap between "theoretical AI" and "practical business systems." You will learn how to integrate messy, real-world constraints—such as "long lead times for overseas procurement" or "reducing inventory during the rainy season to prevent rust"—into your system architecture.


Course Highlights:

  • Browser-Based Development: By using Google Colab and AWS CloudShell, you can complete the entire development flow without complex local environment setups.

  • Serverless AI: We adopt AWS Lambda's Container Image support to run heavy AI libraries (like Scikit-learn/Pandas) in a serverless environment.

  • Business Logic Focus: Learn the design philosophy behind integrating AI predictions with strict business rules.


Course Agenda:

  • Section 1: Introduction - Course overview and system architecture.

  • Section 2: Environment Setup - Setting up Google Colab and AWS CloudShell.

  • Section 3: Data Strategy & Generation - Generating dummy sales data with seasonality and weather correlation using Python.

  • Section 4: Implementing AI Logic (Google Colab) - Building demand forecasting models with Scikit-learn.

  • Section 5: Implementing Business Logic (Google Colab) - Coding rules for "Order Judgment" and "Safety Stock."

  • Section 6: Containerization & AWS Deploy (CloudShell) - Building Docker containers, pushing to ECR, and creating Lambda functions.

  • Section 7: Simulation & Testing - Scenario testing via API integration.

  • Section 8: Summary & Advanced Topics - Audit logging with DynamoDB Streams, weather API implementation, and model expansion.


About the Instructor: Maruchin Tech

After majoring in Information Engineering, I started my career at a Japanese automotive manufacturer. I spent 7.5 years in Supply Chain Management (SCM), handling packaging, procurement, and purchasing. Following that, I worked as an IT Consultant for 6 years, specializing in manufacturing and logistics sectors, focusing on Inventory Management and ERP system development.

Currently, I operate independently in the EdTech sector and create educational content on Cloud and Programming as a Udemy Instructor. Credentials: AWS All Certifications (12 Certifications as of 2025).

Taught by

Maruchin Tech and Maruchin Tech

Reviews

4.6 rating at Udemy based on 11 ratings

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