Cloud Engineering for Python Developers

Become familiar with AWS' foundational services and workflow － writing, deploying, monitoring, and updating applications on AWS.

This is a hands-on course for intermediate Python developers.

Course Overview

The course includes

  • Weekly office hours / "ask me anything" with Eric (Thursdays from 8:00-9:00 AM MDT on Zoom)

  • Help from TA's, Eric, and network of classmates in Discord

  • Lifetime access to

    • self-paced video lessons, labs, and articles and all future improvements

    • the course project codebase

    • private Discord server with your cohort (TA's and instructors can't commit to a response SLA when a cohort isn't in session; TBD - possibly all cohorts could be in one server)

  • Certificate of completion after successfully deploying the course project and passing it off

  • (Optional) complete a <3-week, self-directed solo- or group project and present at a demo day with industry professionals. Past demos here.

  • Refund if <40% of videos watched; just message Eric. So far, not one person has asked for a refund ✨

$400 USD

Note: We have run 3 live cohorts at $500/seat and are now experimenting with a self-paced, lower-priced delivery format through December 2024. We will reevaluate pricing and delivery formats in 2025.

Note: We want this to be accessible to students and folks who are laid off or struggling to get a job.

You can get $100 off tuition if you complete Taking Python to Production first. Learn more here.

You may also apply for an additional scholarship. This will depend on need and whether you have a strong enough background in Python SWE fundamentals to be likely to succeed in the course.

Learning Outcomes

Become an intermediate cloud engineer with a foundation you can build on to learn specialized, advanced areas of AWS or other cloud providers.

  • AWS account management

    • Set up an AWS account in an advanced way to safely grant access to code and collaborators

    • Manage permissions with IAM, following the principle of least privileges

    • Calculate and manage the cost of applications on AWS

  • Cloud-native software design

    • Become comfortable with the AWS console, SDK, and CLI

    • Learn best practices for authoring "cloud-native" applications by writing a REST API

    • Become comfortable writing and testing scripts using the AWS Python SDK (boto3)

    • Minimize vendor lock-in

  • Deployment and "serverless" cloud development

    • Deploy the REST API to AWS using AWS Lambda and AWS API Gateway

    • Iterate quickly by speeding up deployments and developing locally

  • Advanced application observability

    • Track logs, metrics, and traces for the application

    • Set up alerts to notify you of failures and dashboards

    • Perform a root cause analysis to diagnose errors and identify performance bottlenecks

  • General cloud skills

    • Understand how most services in AWS are used such that you feel confident learning new services

    • Feel comfortable exploring and utilizing other clouds. The concepts taught transfer well.

Modules

Section 1: Advanced AWS account setup. Intro to permissions and the AWS SDK

  • Set up your AWS account

  • Create an isolated AWS account just for this course

  • Write and test a script with the AWS SDK

Section 2: Write a cloud-native REST API

  • Deep dive on REST, HTTP, and RFCs

  • Review FastAPI

  • Locally develop and test a FastAPI app that does CRUD operations on S3, making use of OpenAI's endpoints

  • Implement the principles of the 12-factor app and RESTful conventions

  • Rigorously test our API contract

Section 3: Serverless deployments.

  • Deep dive on REST, HTTP, and RFCs

  • Review FastAPI

  • Locally develop and test a FastAPI app that does CRUD operations on S3, making use of OpenAI's endpoints

  • Implement the principles of the 12-factor app and RESTful conventions

  • Rigorously test our API contract

Section 4: Foundations of observability

  • Capture logs, metrics, and traces from our FastAPI.

  • Create alerts from this data to notify when problems arise.

  • Set up a workflow to diagnose errors and identify performance bottlenecks.

Earn the certificate after successfully completing and deploying the project to this point.

(Optional) Self-directed solo- or group project

Plan and build a project that makes use of AWS. Self organize a group or work solo. This is a chance to collaborate with motivated partners at a similar level to you and build something you personally care about.

TBD: will see if TA's can continue to provide office hours during this portion. Looking into pairing groups with a mentor, but not confirmed.

(Optional) Final project demo day

Present on your course project, hold Q&A, and network with an audience of professionals across the industry.

Demo day date TBD.

Non-outcomes

This course does not cover

  • Infrastructure as Code

  • Container orchestration

  • DNS and HTTPS

  • In-depth auth, e.g. OAuth 2.0

  • Advanced CI/CD

  • Networking on AWS

These concepts go beyond intermediate level.

We consider the contents of this course to be prerequisites for these advanced topics and hope to lead a follow-up course covering them in the future.

At the end of lectures, questions on any topic are encouraged--including about these ^^^

Course Delivery

  • Office hours and Q&A over Zoom. Thursdays from 8-9 AM MDT

  • Homework: Complete 1-2 hours of async videos, labs, and readings before each lecture. Access to all released materials is available with in a course portal.

  • Chat with TAs, classmates, and instructors on Discord.

ABOUT YOUR INSTRUCTOR

Eric Riddoch

Former Staff Engineer and ML Platform Lead @ BENlabs

  • 6 years building on AWS (Analytics, Data Engineering, MLOps)

  • Highly-rated Udemy instructor (course here)

  • Creator of ML and data engineering systems handling 2-4 million requests/day and many open-source projects

Built cutting-edge ML Platforms on AWS and presented at Netflix

Authored a bestselling, highest-rated Udemy course

See you in Discord!

FAQs

Is there a refund policy?

TL;DR: Yes. You can request a refund no questions asked.

  1. within 1 week from the start of a cohort

  2. if you have watched <40% of the videos in the self-paced delivery format

I haven't had a single person ask for a refund yet. Here is why:

I take steps to make sure the course is right for you:

The application process is in place for a reason. I think hard about each application to make sure that the students are not under- or overqualified.

The course covers a lot in a short time.

Many applicants do not have a strong background in the software engineering concepts assumed by the course material.

For these, I recommend the mostly free Taking Python to Production course and offer a $100 discount on this one if you complete it. Learn more here. This helps you upskill and decide if you really like me enough as an instructor to enroll in this higher-priced course.

I've seen Taking Python to Production make a huge career difference for folks that do not come from a traditional SWE background.

Are scholarships or discounts available?

Yes.

You can get a $100 discount if you complete Taking Python to Production, including the final course project. I offer this because taking this course de-risks the course two ways: you know you like me as an instructor; I know you are well-prepared with the foundational SWE knowledge assumed by the course material.

If you need more: There is a portion of the application to explain your situation and apply for a needs-based scholarship. These are generally meant for people who have been laid off or are struggling to get a job.

Is there a referral program?

Yes! I (Eric) am a small creator, so the primary way for to teaching to be sustainable is by word-of-mouth referrals.

You can register for the referral program here.

Shoutouts from Students

Click images to view the original posts

Milan, Software Engineer

Casey Wahl

MLE @ Progressive Leasing

I came into this Python Cloud Engineering course with 6 years of industry experience including over 3 years as an MLE.

I expected about 50% of the content to be incrementally useful, but Eric’s course had such depth that it exceeded my expectations and in reality was about 90%.

The abundance of best practices I’ve learned in this course have been transformative!

Why waste years searching for these best practices on your own when Eric has masterfully curated content that nourishes a coder’s soul?

Jordan, MLE @ Nationwide Insurance

Noor, Computer Science grad from BYU

Nemanja, Senior MLOps Engineer

Matt, MLE @ Qlik

Aaron, Senior MLOps Engineer

Mert, GenAI Engineer @ kloia

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