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Introduction to AWS Boto in Python

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

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4 Hours15 Videos54 Exercises11,405 Learners4550 XPData Engineer Track

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Course Description

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!

  1. 1

    Putting Files in the Cloud!

    Free

    Embark on the world of cloud technology! From learning how AWS works to creating S3 buckets and uploading files to them. You will master the basics of setting up AWS and uploading files to the cloud!

    Play Chapter Now
    Intro to AWS and Boto3
    50 xp
    Your first boto3 client
    100 xp
    Multiple clients
    100 xp
    Removing repetitive work
    50 xp
    Diving into buckets
    50 xp
    Creating a bucket
    100 xp
    Listing buckets
    100 xp
    Deleting a bucket
    100 xp
    Deleting multiple buckets
    100 xp
    Uploading and retrieving files
    50 xp
    Putting files in the cloud
    100 xp
    Spring cleaning
    100 xp
  2. 2

    Sharing Files Securely

    Continue your journey in mastering AWS by learning how to upload and share files securely. You will learn how set files to be public or private, and cap off what you learned by generating web-based reports!

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    Keeping objects secure
    50 xp
    Making an object public
    50 xp
    Uploading a public report
    100 xp
    Making multiple files public
    100 xp
    Accessing private objects in S3
    50 xp
    Generating a presigned URL
    100 xp
    Opening a private file
    100 xp
    Sharing files through a website
    50 xp
    Generate HTML table from Pandas
    100 xp
    Upload an HTML file to S3
    100 xp
    Case Study: Generating a Report Repository
    50 xp
    Combine daily requests for February
    100 xp
    Upload aggregated reports for February
    100 xp
    Update index to include February
    100 xp
    Upload the new index
    100 xp
  3. 3

    Reporting and Notifying!

    Next, you will learn how to automate sharing your findings with the world by building notification triggers for your analysis! You will learn how to harness AWS to send SMS and email notifications to users and cap off what you learned by making custom notifications depending on a user's needs.

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    SNS Topics
    50 xp
    Creating a Topic
    100 xp
    Creating multiple topics
    100 xp
    Deleting multiple topics
    100 xp
    SNS Subscriptions
    50 xp
    Subscribing to topics
    100 xp
    Creating multiple subscriptions
    100 xp
    Deleting multiple subscriptions
    100 xp
    Sending messages
    50 xp
    Sending an alert
    100 xp
    Sending a single SMS message
    100 xp
    Case Study: Building a notification system
    50 xp
    Creating multi-level topics
    100 xp
    Different protocols per topic level
    100 xp
    Sending multi-level alerts
    100 xp
  4. 4

    Pattern Rekognition

    Finally, you will go beyond uploading, sharing and notifying into rekognizing using AWS Rekognition and other AWS machine learning services to recognize cats, translate language and detect sentiment. You will be capping off your learning journey by applying a real-world use case that mixes everything you've learned!

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    Rekognizing patterns
    50 xp
    Cat detector
    100 xp
    Multiple cat detector
    100 xp
    Parking sign reader
    100 xp
    Comprehending text
    50 xp
    Detecting language
    100 xp
    Translating Get It Done requests
    100 xp
    Getting request sentiment
    100 xp
    Case Study: Scooting Around!
    50 xp
    Scooter community sentiment
    100 xp
    Scooter dispatch
    100 xp
    Wrap up
    50 xp

In the following tracks

Data Engineer

Datasets

Get It Done Requests

Collaborators

AAN94
Adel Nehme
hillary-green-lerman
Hillary Green-Lerman

Prerequisites

Python Data Science Toolbox (Part 2)AWS Cloud Concepts
Maksim Pecherskiy Headshot

Maksim Pecherskiy

Data Engineer

Maksim is a Data Engineer at the World Bank, and formerly the Chief Data Officer at the City of San Diego. He also works with tech companies to help them effectively connect technology to government. he came to the US from Ukraine when he was 10 years old, lived in 5 countries and speaks 3 languages.
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