The Ultimate Dynamodb Course

The most intuitive and practical way to learn DynamoDB

What you’ll learn
DynamoDB is powerful yet complex; finding a clear, complete guide can be overwhelming.
Simplifying DynamoDB terms—Partitioning, Keys, LSI, GSI, WCU, RCU, and Access Patterns.
Data modeling is crucial in DynamoDB; this course helps you get it right for your needs.
I spent a year mastering DynamoDB; with this course, you’ll gain that knowledge in days.

Requirements
This course deal with the practical examples of how to use DynamoDB with NodeJS. So students are expects to atleast know the basics of NodeJS

Description
I’m a self-taught Web Developer with a background in the MERN stack. In 2020, I set a personal challenge to dive into the AWS serverless ecosystem. I was excited to start learning tools like Lambda, DynamoDB, and API Gateway, thinking that it would take me only a month or two to get a solid grasp. I assumed there would be plenty of resources to help me speed up my learning—guides, tutorials, even detailed courses. But I quickly discovered that there were very few clear resources available, and even the AWS documentation was surprisingly difficult to navigate and often left me with more questions than answers.Over the course of a year, I pushed through, figuring things out piece by piece. Most of my time was spent trying to understand DynamoDB, which was not only complex but came with unique challenges around data modeling, partitioning, and managing access patterns. I felt like I was constantly hitting roadblocks with no straightforward guide to follow.That’s why I created this course: to share my journey and offer a comprehensive, practical guide to DynamoDB. What took me a year to learn, you’ll be able to understand in just a few days, bypassing the frustrations I encountered and gaining a clear path to mastery.

Overview
Section 1: Introduction

Lecture 1 Welcome to this course

Section 2: Precursor

Lecture 2 Before you proceed

Lecture 3 A short intro to the module

Lecture 4 History of Databases

Lecture 5 Problems with SQL and why we need NoSQL

Lecture 6 CAP theorem

Lecture 7 Dynamo Paper

Lecture 8 Basics of Entity Relationship Model

Lecture 9 References

Section 3: Basics of DynamoDB

Lecture 10 What is DynamoDB?

Lecture 11 Instances, Managed services, Serverless

Lecture 12 How DynamoDB works internally

Lecture 13 Throughput in DynamoDB – WCU and RCU

Lecture 14 Pricing structure in DynamoDB

Lecture 15 References

Section 4: All about Keys

Lecture 16 Introduction

Lecture 17 Creating DynamoDB Table in Web Console

Lecture 18 Keys in DynamoDB

Lecture 19 Query vs Scan

Lecture 20 Secondary Index – LSI & GSI

Lecture 21 Documentation and setting up Credentials

Lecture 22 References

Section 5: All about Attributes

Lecture 23 Create Table with JavaScript SDK

Lecture 24 Upload Item with SDK

Lecture 25 Attributes and Projection Expression

Lecture 26 Reserved Keywords and Expression Attribute Name

Lecture 27 More examples – Expression Attribute Name

Lecture 28 Condition Expression

Lecture 29 References

Lecture 30 Updating and Filtering

Section 6: Modelling with DynamoDB

Lecture 31 Limits in DynamoDB

Lecture 32 Filtering Strategies

Lecture 33 How to model Spotify in DynamoDB?

Lecture 34 Modelling YouTube Comment Box

Lecture 35 Single Table Design – use it or avoid it?

Lecture 36 References

Section 7: Batch operations in DynamoDB

Lecture 37 Upload CSV file with BatchWriteItem

Lecture 38 Pagination

Lecture 39 References

Section 8: Advanced concepts

Lecture 40 Introduction to Batch Operation

Lecture 41 BatchGetItem Demo

Lecture 42 Time to Live – TTL

Lecture 43 PartiQL

Lecture 44 Backup + Point in Time Recovery (PITR)

Lecture 45 Global Tables

Lecture 46 What is DAX?

Lecture 47 You have reached at the end

Lecture 48 References

Section 9: Additional Information

Lecture 49 Dynobase – Browser for DynamoDB

Lecture 50 Using Serverless framework for deployment + DynamoDB streams

Lecture 51 References

This course is for anyone who is generally curios about DynamoDB or want to use it as a database in their AWS serverless environment