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Introduction to AWS Boto in Python
4.8(216)18k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate Python course breaks through local hardware limitations by integrating Amazon Web Services directly into your data pipelines. Through practical cloud automation examples—such as image recognition and automated SMS notifications—it demonstrates how cloud storage and managed AI services expand data capabilities.
Who It's For
Data scientists, Python engineers, and cloud beginners who want to leverage AWS services like S3, Rekognition, Comprehend, and SNS directly from Python scripts.
Key Takeaways
- Cloud Storage with S3: Learn how to upload, manage, and retrieve datasets seamlessly using AWS S3 storage.
- Automated Messaging via SNS: Configure AWS SNS triggers to send SMS alerts and notifications based on pipeline events.
- Computer Vision & Sentiment Analysis: Utilize AWS Rekognition for object detection in images and AWS Comprehend for automated sentiment scoring.
- End-to-End Cloud Pipelines: Combine cloud storage, machine learning APIs, and notification services into unified Python workflows.
About this course
What if you were no longer constrained by the capabilities of your laptop? What if you could get an SMS when a city garbage truck camera spots a missing a cat? This is all possible with cloud technology. This course will teach you how to integrate Amazon Web Services (AWS) into your data workflow. You’ll learn how to upload data to S3, AWS cloud storage. You’ll use triggers from your analysis to send text messages with AWS SNS. You will use Rekognition to detect objects in an image. And you will use Comprehend to decide if a piece of feedback is negative. By the time you’re done, you will learn how to build a pipeline, subscribe people to it, and send them text messages when an image contains a cat!
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