👨🎓Recommended Courses
A list of required knowledge for the active projects in the Gadet Engineering repositories. This is in order of priority from the runtime language to the deployment architecture.
Last updated
A list of required knowledge for the active projects in the Gadet Engineering repositories. This is in order of priority from the runtime language to the deployment architecture.
Last updated
Before getting started on the courses below, please request access to the gadget business Udemy account from your manager.
If you are starting with a front-end project, skip and move to the front-end courses.
Python basics and object-oriented features.
Get familiar with Restful API services and some databases frameworks, API Method testing. The below course will help you a lot. If you are a complete noob, then go through all the courses below otherwise at least it is wise to get familiar with FastAPI, MongoDB/DynamoDB (NoSQL)/(MySQL).
If you are working on a back-end project, skip this section and go to the Back-End courses.
Prerequisite Courses: Amazon Web Services (AWS)
Now Begin learning AWS Basics: (It is possible to learn the basics of cloud computing from various resources such as Youtube, GeeksforGeeks, and other online resources). If you are familiar with AWS/ any cloud basics then jump to AWS Serverless.
Your EC2 instances are configured with Arm64 architecture! Be sure that when using SAM CLI examples from the internet that you are changing the configuration of Lambda functions to deploy into the arm64 architecture.
Example:
There are many ways and languages that anyone can take for learning AWS serverless application model and its underlying services but Python is the most recommended one. An easy introductory course to serverless concepts is lambda functions.
This course uses JS runtime but is still a great overview of important services commonly used to build an event-driven architecture. Don't get caught up in the runtime, focus on the features of each AWS service and how they might be used in various use-cases.
This is by far one of the most critical concepts to understand in the deployment architecture at Gadget Engineering. SAM CLI is the heart of the development, deployment, and testing for serverless architecture.
Python Library for AWS Services Automation. Study this if you plan on executing automations in runtime (for example, invoking a lambda function or state machine directly from another lamba function).
State Machines help to orchestrate workflows through a series of Step Functions, each containing state (before and after execution). Each Step Function represents an AWS service (lambda, SQS, S3, DynamoDB) or a transform using AWS State Machine syntax.
Skip to learning SAM CLI and SAM templates if you have not already learned those fundamentals. This Step Functions course is for those that have a project that will make use of or is making use of step functions. It is a highly powerful concept worth studying if your project involves this concept.
A simple, powerful document database native to AWS and easily constructed within the SAM templating language.
For those getting into the DevOps team, the basics of DevOps with AWS.
Now buckle up or pull up your socks for AWS Developer:- (You need to have all the basics knowledge until now of all the above courses, including all electives, in order to move forward):-
The topics listed below are not yet concepts integrated directly into any active repositories or are abstracted from the serverless models being implemented. Nonetheless, they might be useful if you are curious to know more and expand your knowledgebase as a developer.
The AWS SAM model essentially handles all of the features of Docker and Kubernetes under the hood; but if you are curious to dig into these concepts, take a look at this course.
For those that have a love for normalized databases and punishment, take a look at this SQL course! While we primarily deploy document-based persistence, SQL still has a place and time and is worth exploring if you are unfamiliar with the concepts of relational databases.
Check out these pages for some great additional content and documentation for AWS and python.
