Companies are continually looking for competent AWS developers who can create creative AWS applications. So, if you’re a beginner, the best thing you can do is work on some of the most popular AWS business ideas.
We at Hackemist believe in a practical approach because academic knowledge alone will not be useful in a real-world job situation.
In this article, we will go over several intriguing AWS businesses that beginners can work on to put their knowledge to the test.
Despite the fierce competition, ambitious AWS developers must have hands-on expertise with real-world AWS projects. This is one of the most important recruitment factors for most organizations nowadays.
As you begin working on AWS projects, you will be able to test your skills and limitations while also gaining exposure that will be extremely beneficial to your career.
Top AWS Business Ideas
This selection of AWS business ideas is appropriate for beginners, intermediates, and experts. These AWS businesses will provide you with all of the practical skills you’ll need to advance in your profession. Most of these AWS projects have source code available publicly.
Furthermore, if you’re seeking AWS projects for your final year, this list will get you started. So, without further ado, let’s get started on some AWS projects that will help you build a solid foundation and further your career.
Here are some AWS business ideas with source code that will guide you in the proper direction:
1. Deploy a Windows Virtual Machine
Working on deploying a Windows virtual machine is one of the finest ways to get students started with their hands-on AWS assignments. Virtual machines are simulations of computer systems. The more nuanced definition states that a virtual machine is a product of abstracted resources from physical hardware.
They are isolated environments within the system, which means they function independently of other virtual computers on the same network. This is one of the best AWS projects for beginners, with source code available in online repositories.
Virtual machines have a wide range of uses. They are useful for increasing the efficiency of a process. AWS allows you to deploy a Windows virtual machine and discover how it works. Learning about virtual machines (VMs) will help you become a good engineer and is a vital ability.
You may use Amazon Lightsail to deploy a Windows virtual machine on AWS, which greatly simplifies the process. Amazon Lightsail is a cloud platform that provides the resources you need to create a website or application. Its UI is simple to understand, and finishing this project will familiarize you with the software.
2. Create a Website on AWS
Creating a website is one of the finest ways to get students started with their hands-on AWS projects. This is one of the easiest AWS project ideas for students on the list. Here, you must develop a website using the AWS cloud platform. To simplify this process, you can use Amazon Lightsail.
As a virtual private server (VPS) provider, Amazon Lightsail provides developers and other users with a convenient entry point into AWS for developing and hosting cloud-based applications. Lightsail provides SSD-based storage, and its UI is simple to understand. As a newbie, you’ll have no trouble using this method to create your website.
We chose Amazon Lightsail for this project since it is pre-configured with many popular web development options, including Joomla and WordPress.
We propose that you create a WordPress website because it is the most popular CMS out there. You should begin by starting a blog. WordPress requires a web server as part of its Internet hosting service to function as a network host. If you have previous experience with websites, you can create an eCommerce or portfolio site.
3. Launch a Serverless Web App
It could be one of the more complicated AWS projects on this list, but once it’s accomplished, you’ll be familiar with numerous AWS principles and services. Here are the technologies we’ll be using in this project, along with their purpose:
- AWS Amplify is used to host the HTML, CSS, and JS for the web app’s front end.
- Amazon Cognito – For managing and authenticating the backend API.
- Amazon API Gateway with AWS Lambda – For creating and using the backed API.
- Amazon DynamoDB – Add a persistence layer for storage.
To finish this project, you need to be familiar with all of the following technologies: HTML, CSS, and JavaScript. You will also be implementing RESTful APIs in this project, so you should be familiar with their implementations. However, once completed, you will understand how multiple Amazon services function together.
We propose creating a small web app first, followed by a more complex one. For beginners, you could make a BMI calculator or a simple reminder app. Mentioning AWS projects can make your CV appear more interesting than others.
4. Set up Kubernetes Clusters on Amazon EC2 Spot
This is one of the most fascinating AWS projects to construct. Kubernetes is an open-source technology that automates container deployment, management, and scalability. This software allows you to create, manage, and orchestrate containers in cloud computing.
It’s one of the most crucial AWS projects on this list since Kubernetes is an essential skill for cloud computing experts. Because Kubernetes is open source, it is also widely used in the industry. This is a great AWS project for beginners.
Because you’re working on AWS, you’d need to use Amazon EC2, a service that provides dynamic computing capabilities in the cloud. But we’ll go a step further and employ Amazon EC2 Spot Instances, which enable customers to take advantage of the majority of EC2’s capabilities.
EC2 Spot Instances and Kubernetes both take the same approach to containers, so you can use them interchangeably. When working on this project, make sure to follow Spot Instances’ best practices.
You can create numerous node groups and prioritize capacity optimization for allocation to guarantee that the worker nodes function properly.
5. Create a Content Recommendation System
Recommendation systems are among the most widely used AI and ML applications. From Netflix to Flipkart, every major firm employs them to improve the customer experience and engagement. You can develop a recommendation system on the AWS cloud by using the nearest neighbor.
In this project, you’d use Amazon SageMaker, a fantastic tool for machine learning implementations. SageMaker contains built-in algorithms that do not require label data and employ semantic search rather than string matching; thus, employing them will greatly simplify the work. Use the K-Nearest Neighbors algorithm in this project to ensure that your recommendation system provides accurate and useful choices to the user.
6. Use Rekognition to Identify Famous People
Computer vision is one of the most popular ideas in machine learning and artificial intelligence. If you want to work on a computer vision project, start with this one. If you have any expertise in computer vision, you have undoubtedly heard of OpenCV.
With its vast open-source library for computer vision, machine learning, and image processing, OpenCV has become an essential component of today’s systems, which require real-time performance. Before you start working on this project, you should understand the fundamentals of computer vision and its associated algorithms.
In this project, you must construct a facial recognition model that can identify individual people in a photograph. Normally, training facial recognition takes time and effort, but because we’re using AWS, things are easier. It is one of the most popular AWS projects.
In this project, you will utilize Amazon Rekognition to do facial recognition because it enables users to quickly add and analyze photographs through deep learning. It is classified as an API for image analysis, whereas OpenCV is utilized for real-time picture classification.
This software can identify a variety of objects, activities, persons, and text in movies and photos. This is one of the most popular AWS projects. Building and training a facial recognition model will make you more comfortable with recognition.
Initially, you can train your model to identify a specific renowned person, such as MS Dhoni or Robert Dowrey Jr. Once you’ve completed the model, you can test it to see how well it works. To make things more challenging, you can train your model to recognize numerous people by including more well-known people.
7. Mass Emailing using AWS Lambda
As the name suggests, the goal of this project is to send bulk emails to a company’s existing and new clients. One of the benefits of using AWS Lambda is that it can be readily integrated with other email or SMS services to provide a low-cost mass-mailing solution.
AWS Lambda is an S3 that facilitates the distribution of mass emails to a larger number of recipients. When a CSV file is uploaded, an AWS S3 event is triggered, and the Lambda function imports the data into the database.
Once this is completed, you can begin sending bulk emails to the email addresses provided. The most popular example of a mass emailing bulk service is MoonMail, which is designed using AWS Lambda.
8. Using Amazon Recognition to Identify People
This project uses Amazon Rekognition to explore computer vision, machine learning, and artificial intelligence ideas. To get started on the project, you must first master the fundamentals of computer vision and related techniques.
As part of the project, you will be required to develop a face recognition model capable of identifying specific people in photographs or images. Face recognition training is a time-consuming and stressful procedure, but AWS Lambda makes it easier.
To effectively complete this project, you must use Amazon Recognition to do facial recognition. It simplifies the process by automatically extracting metadata from image and video files, as well as capturing objects, faces, text, and other features using deep learning.
To advance in this assignment, you must teach your model to recognize a renowned individual. After training it for a while and feeding it enough data, you may test your project to see how well it works. To advance the task, you can train your model with more users.
9. Train a Machine Learning Model with SageMaker
Amazon SageMaker is one of Amazon’s most effective machine learning systems. This business’s goal is to train a machine-learning model with SageMaker. It offers an integrated development environment (IDE) for machine learning, allowing you to train your machine-learning model using meaningful data.
You can use the IDE to create notes, switch between phases, check outcomes, and perform other tasks. The best part about working with SageMaker is that it allows you to create computer instances quickly and efficiently. To further reduce the amount of effort required, use SageMaker’s Autopilot feature to complete the procedure with significantly less effort.
10. Website Development using AWS
The goal of this project is to create a website that is both secure and reliable, using AWS Lightsail as a virtual private server. You will gain experience working on AWS by creating a website that is directly tied to a database.
Creating the site should be simple, thanks to AWS EC2 and Lambda services that provide SSD-based storage and numerous web development options preloaded inside Lightsail as a virtual private server.
11. Creating Custom Alexa Skills
Goal of this Project: Alexa Replica The goal of this project is to replicate Alexa and its skills using AWS Lambda with custom Alexa skill sets embedded within AWS Console to invoke the handler function; additionally, you can use the Alexa Handler function found within AWS Lambda with the custom logic for calling the handler function.
As part of this effort, you can also access third-party features hosted outside of Alexa. Starting today, tasks such as playing music or setting reminders may be performed, or instructions may be issued for certain functions to accomplish tasks.
12. Creating a Text-to-Speech Converter
Text-to-speech is an AI-powered feature that is widely utilized in websites and web apps. The primary goal of this project is to construct a text-to-speech converter. AWS Lambda and Amazon Polly are ideal for translating text to speech.
This combo can help you create practical speech synthesis apps. Amazon Polly allows you to employ advanced deep learning algorithms to do correct conversions, while AWS Lambda improves reaction time, which is crucial in real-time applications.
13. Content Recommendation System
The idea is to leverage AI and machine learning in conjunction with AWS to recommend content to end users based on their historical behavior. Almost all streaming services, including Netflix, Amazon Prime Video, and others, offer content recommendation engines. You can work on this project using the AWS cloud and nearest-neighbor techniques.
For this project, use Amazon SageMaker; it will make it easier to incorporate machine learning. It features built-in algorithms that do not require labeling data. It also simplifies tasks by using semantic search rather than string matching. AWS, along with nearest-neighbor algorithms, will produce reliable results and recommendations.
14. Real-Time Data Processing Application
In this project, you will work on processing large amounts of data in real time with high-accuracy results.
Bustle is a real-world example of how to process enormous amounts of site metric data in real-time using AWS. You can utilize Amazon Kinesis Stream and AWS Lambda to complete this project. To proceed, you must first create a Kinesis Stream.
It will be critical that you configure it to capture data from a web source. Several Lambda function instances will be automatically scaled up or down as the stream scales. You may use social media timelines or location-based data as your data sources.
You can link Kinesis with AWS Lambda in one of three ways: stream-based, synchronous invocation, or event structure model.
AWSAWS Business Ideas for Beginners
Here is an overview of the top ten Amazon Web Services (AWS) projects for beginners:
| SN | Project Title | Complexity | Estimated Time | Source Code |
| 1 | Static Website Hosting with S3 | Easy | 5 hours | View Code |
| 2 | Serverless REST API with API Gateway and Lambda | Easy | 5 hours | View Code |
| 3 | Simple Notification Service (SNS) for Email Alerts | Easy | 5 hours | View Code |
| 4 | Deploy a Web Application with Elastic Beanstalk | Easy | 5 hours | View Code |
| 5 | Relational Database with RDS | Easy | 6 hours | View Code |
| 6 | Monitor Resources with CloudWatch | Easy | 6 hours | View Code |
| 7 | AWS Identity and Access Management (IAM) Policies | Easy | 6 hours | View Code |
| 8 | Simple Data Processing with AWS Glue | Medium | 6 hours | View Code |
| 9 | Content Delivery Network (CDN) with CloudFront | Easy | 6 hours | View Code |
| 10 | Simple Chatbot with Lex | Easy | 6 hours | View Code |
Conclusion
Now, put all of your knowledge from our data engineering projects guide to the test by creating your own AWS business.
Working on AWS business ideas can help you better understand the various services and their applications. We hope you find our collection of ideas useful. If you have any questions or recommendations about this article, please leave them in the comments.