Top 8 Exciting AWS Projects & Ideas For Beginners [2024]

AWS Projects & Topics

Looking for AWS project ideas? Then you’ve come to the right place because, in this article, we’ve shared multiple AWS projects. The projects are of various sectors and skill-levels so you can choose according to your expertise and interests. The more projects you have in your portfolio, the better. Companies are always on the lookout for skilled AWS Developers who can develop innovative AWS projects. So, if you are a beginner, the best thing you can do is work on some top AWS projects.

We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. In this article, we will be exploring some interesting AWS projects which beginners can work on to put their knowledge to test. In this article, you will find top AWS projects for beginners to get hands-on experience on Java.

Amid the cut-throat competition, aspiring AWS Developers must have hands-on experience with real-world AWS projects. In fact, this is one of the primary recruitment criteria for most employers today. As you start working on AWS projects, you will not only be able to test your strengths and weaknesses, but you will also gain exposure that can be immensely helpful to boost your career.

What is AWS? 

AWS stands for Amazon Web Service, which is among the most popular cloud platforms. AWS provides developers and organizations with cloud services and helps them stay agile. From multi-million startups to government agencies, many organizations are using AWS. If you want to become a cloud-computing professional, you should learn about AWS. AWS provides a variety of services to its clients.

By elevating e-commerce beyond the norms of software development, AWS has completely changed the way business is done online. Fast-paced business and service delivery from remote places are made possible by AWS, which uses cutting-edge technology to create a strong community of customers and service partners.

Whether you’re a BI expert or a web developer, being familiar with AWS will enhance your resume nonetheless. It is the leading cloud platform in the world, and the demand for its experts is evergreen. 

AWS Projects’ Applications

The applications of projects on AWS span a wide spectrum, catering to basic and advanced needs. AWS real time projects can be swiftly developed and deployed, serving cloud computing professionals in creating projects ranging from fundamental to enterprise-level applications. An illustrative instance is Amazon Elastic Compute Cloud (EC2), which facilitates the rental of virtual computing resources for seamless application execution. Complementing this is AWS Lambda, a fundamental service for serverless computing, where code execution becomes effortless, free from concerns about service management or intricate cluster scaling. 

The allure of AWS Lambda projects lies in their administration-free nature. Moreover, as one of the burgeoning technologies, the Internet of Things (IoT) finds fertile ground in AWS resources, offering an array of possibilities in AWS IoT projects.

AWS boasts remarkable versatility, granting the liberty to handpick operating systems, databases, and supplementary services. This virtual environment empowers the incorporation of services and software tailored to match application requisites. The transition from a pre-existing platform to an AWS-based solution is equally straightforward, accompanied by the added attributes of security, dependability, and user-friendliness inherent to AWS projects for beginners and applications.

Consequently, these ventures find relevance in academic pursuits and professional pathways. Students can engage with these AWS mini project concepts to enrich their resumes, spotlighting their adeptness in cloud computing to potential recruiters and securing coveted job roles. Furthermore, AWS projects for students’ seamless infrastructure facilitate the creation of intricate projects catering to the demands of industrial and business domains.

Importance of AWS Projects

As per a 2018 Accenture survey, Amazon Web Services stands out as the platform with the most forward-looking perspective, a sentiment shared by developers. The survey participants also bestowed high marks on AWS for its developer-friendly nature. Several defining characteristics underline AWS’s significance:

AWS Auto Scaling

This functionality empowers developers to adjust resources in response to shifting demands dynamically.

With the help of Amazon Auto Scaling, developers can effortlessly adapt computational resources to meet varying workloads, ensuring that applications function as intended. The cost-effectiveness and performance are both enhanced by this dynamic scaling.

Pay-as-You-Go Model

The budget-friendly pay-as-you-go approach ensures cost-effectiveness, aligning payment with the services used.

By removing upfront capital costs, AWS’s Pay-as-You-Go pricing model promotes cost-effectiveness by enabling businesses to only pay for the resources they use. This adaptability allows costs to be in line with real consumption, providing cost-effectiveness for projects with different resource requirements.

Immediate Service Provisioning

AWS promptly delivers services upon demand, seamlessly deploying additional servers without perceptible delays.

These attributes collectively highlight why AWS is highly regarded and essential in technology.

Because of AWS’s instantaneous service provisioning, more resources can be quickly deployed in response to demand, which makes it easier for applications to quickly adjust to shifting workloads. This flexibility in allocating resources contributes to sustaining peak performance without noticeable lags immediately.

AI and machine learning capabilities:

With the help of machine learning services from AWS like Amazon SageMaker, Rekognition, and Comprehend, students can now incorporate automation, advanced analytics, and predictive modeling into their applications. Developers can use pre-built models or create unique ones to increase the intelligence of their products. 

These AWS projects for students enable the extraction of insightful data, predictions, and automation of procedures through the incorporation of machine learning capabilities.

Integration of the Internet of Things (IoT):

Building scalable and secure Internet of Things applications is made easier with the full range of tools and services offered by AWS. Using AWS IoT Core, projects can easily integrate and manage IoT devices and data. This makes it possible to gather, analyze, and analyze data from devices that are connected, which helps to develop creative and effective Internet of Things solutions.

Computing without a server:

Serverless computing is made possible by AWS Lambda, which frees programmers from the hassle of maintaining servers and lets them respond to events with code. This is beneficial for some backend functions, microservices, or web parts, providing streamlined development cycles, economy, and automated scaling. 

Examining AWS real-time projects examples for practice offers an opportunity to see serverless computing in action and gain insight into its practical applications.

Worldwide Delivery of Content:

Projects may quickly distribute content to users worldwide with the help of AWS’s Content Delivery Network (CDN) services, such as Amazon CloudFront. CloudFront lowers latency, boosts speed, and improves user experience by caching material at edge locations. This is especially important for applications that have users from all over the world.

Hybrid Cloud Configurations:

Projects may effortlessly link cloud resources with on-premises data centers thanks to AWS’s support for hybrid cloud architectures. For companies that have already invested in infrastructure, this flexibility is crucial since it allows for a gradual shift to the cloud while preserving compatibility with on-premises systems.

Flexible Load Distribution:

Elastic load balancing is a service that helps AWS projects by distributing incoming traffic among several instances. By routing traffic to healthy instances, this provides applications with high availability and fault tolerance. It increases project dependability and performance overall while optimizing resource use.

Services for Managed Databases:

Fully managed database services, such as Amazon RDS, DynamoDB, and Aurora, are provided by AWS. Provisioning, patching, and backups are just a few of the database administration activities that these services streamline. Projects can effortlessly expand their databases, guaranteeing peak efficiency, dependability, and performance.

Sturdy Security Services:

Threat detection, encryption, and identity and access management (IAM) are just a few of the security services and tools that AWS offers. By protecting sensitive data during the course of the project and helping to comply with regulations, these services improve the security posture of projects on AWS.

DevSecOps Methods:

AWS integrates security into the development and deployment pipeline to support DevSecOps techniques. This guarantees that, from code development to deployment, security is given top emphasis at every turn. Projects can improve the overall security of their applications by proactively identifying and addressing vulnerabilities through the automation of security operations.

Tools for Cost Monitoring and Optimisation:

Tools like AWS Budgets and Cost Explorer can be used in an AWS project to track and maximize expenses. These tools offer perceptions into how resources are used, cost patterns, and budget compliance. Organizations can ensure cost-effectiveness in resource allocation by using this information to inform their decisions.

Utilizing Amazon ECS with EKS for containerization:

Elastic Kubernetes Service (EKS) and Amazon Elastic Container Service (ECS) are two examples of container services provided by AWS. These services are valuable for AWS projects for final year, facilitating the deployment, scaling, and orchestration of containers. Using containerization improves resource efficiency, speeds up application development, and makes managing complicated, distributed systems on AWS easier.

High Performance Computing (HPC):

For applications requiring a large amount of processing power, AWS offers high-performance computing capabilities. This is especially helpful for fields like financial modeling, engineering simulations, and scientific research. AWS projects for beginners may perform compute-intensive applications effectively and at scale by utilizing AWS’s HPC services.

Associated Ecosystem:

Managed service providers, technology partners, and consulting partners are just a few of the many partners that AWS has. By utilizing this ecosystem, projects can get access to extra services, specialist knowledge, and solutions that meet their unique requirements. This cooperative network helps best practices get adopted and improves the capabilities of an AWS project.

Ongoing Innovation:

Because of AWS’s dedication to ongoing innovation, projects are kept at the forefront of technological breakthroughs. By regularly releasing new features and services, the platform helps businesses prepare their infrastructure and applications for the future. Using the newest technologies allows projects to become more competitive and provide users with innovative solutions.development capabilities pre configured

AWS and Website Development

This project aims to craft a remarkably secure and dependable website using AWS Lightsail as a virtual private server (VPS). Through this endeavor, you will gain hands-on experience in AWS by constructing a website intrinsically linked to a database. The site creation process is streamlined by leveraging AWS EC2 and Lambda services, which furnish SSD-based storage alongside an array of web development capabilities preconfigured within Lightsail’s virtual private server environment.

• Infrastructure and Hosting:

AWS offers a scalable and dependable infrastructure for website hosting. While Amazon EC2 (Elastic Compute Cloud) offers virtual servers for dynamic and scalable web applications, Amazon S3 (Simple Storage Service) enables the affordable and scalable storage of static material. Users all across the world are guaranteed low-latency access to content because of AWS’s global network of data centers.

• Computing without a server:

Serverless computing is made possible by AWS Lambda, which frees programmers from the hassle of maintaining servers and lets them respond to events with code. This is beneficial for some backend functions, microservices, or web parts, providing streamlined development cycles, economy, and automated scaling. Examining AWS real-time projects offers an opportunity to see serverless computing in action and gain insight into its practical applications.

• Delivery of Content:

AWS’s Content Delivery Network (CDN) offering, Amazon CloudFront, speeds up the delivery of website content by caching it at edge locations across the globe. This guarantees quick information delivery to consumers regardless of their location, lowers latency, and improves user experience.

• Database Services:

Amazon RDS (Relational Database Service) and DynamoDB are two examples of managed database services provided by AWS. These services offer scalable and dependable database solutions for websites, making database maintenance responsibilities simpler. Whether they are relational or NoSQL, databases can be selected by developers according to their particular needs.

• Auto-scaling and scalability:

Websites can dynamically modify resource allocation with the help of AWS Auto Scaling, maximizing efficiency during periods of high traffic and cutting expenses during periods of low traffic. Taking on a modest AWS mini project provides hands-on experience with Auto Scaling implementation and optimization for real-world circumstances.

• Safety and Adherence:

In order to guarantee website security and compliance, AWS provides an extensive range of security services, such as DDoS prevention, encryption, and IAM. Although users are ultimately in charge of protecting their data, AWS’s shared responsibility policy ensures a secure cloud architecture. Examining AWS real-time project examples demonstrates how these security services can be used in a variety of contexts.

• Continuous Deployment with DevOps:

To support DevOps methods, AWS provides infrastructure as code, continuous integration, and continuous deployment capabilities. The development lifecycle is accelerated by services like AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy, which automate the build, test, and deployment processes. These skills are essential for learning about the CICD pipeline in AWS and carrying out streamlined and effective AWS cloud projects.

• Analytics and Machine Learning:

AWS offers solutions for adding analytics and machine learning to websites. Amazon Rekognition can analyze photos and videos, Amazon Polly can turn text to speech, and services like Amazon Personalize can improve user experiences by making recommendations for relevant material.

• Registration and Administration of Domains:

Using AWS’s domain registration services, developers may quickly register and manage domain names through the AWS Management Console, which simplifies the deployment of website infrastructure. For people exploring AWS project ideas, integrating domain registration services offers a practical starting point for innovative projects within the AWS environment.

• Monitoring and logging:

With the help of AWS CloudWatch’s logging and monitoring capabilities, developers can keep tabs on website performance, create alerts, and learn more about the condition of their infrastructure. This makes proactive maintenance easier, guaranteeing peak performance and seeing possible problems before they affect users.

AWS offers a whole range of services that cover every facet of developing websites and offer efficiency, security, scalability, and customization. These services can be used by developers to create and launch reliable, fast websites that can adjust to changing customer needs and provide the best possible user experience.

Generating Alexa Functionalities 

This project aims to create a functional replica of Amazon Alexa, complete with its diverse set of skills. This will be achieved using AWS Lambda, incorporating custom Alexa skill sets directly within the AWS Console. The handler function within AWS Lambda will be invoked, and you can also opt to employ the built-in Alexa Handler function, supplemented with personalized logic to execute the handler function.

Furthermore, this project provides the opportunity to harness external third-party functions hosted beyond the Alexa ecosystem. With these enhancements, tasks like playing music or setting reminders can be seamlessly accomplished, empowering users to issue specific commands for the execution of designated tasks.

Engaging with AWS real time project examples and AWS cloud projects facilitates familiarity with cloud technologies. It acquaints you with cutting-edge concepts like Artificial Intelligence and Big Data, which play pivotal roles in numerous project endeavors. As you delve into these projects, you’ll garner enhanced analytical, problem-solving, and risk mitigation skills through hands-on engagement, further enriching your expertise in AWS projects.

Why You Should Work on AWS Projects

The best way to showcase your knowledge of a particular skill or topic is through projects. Projects can help the other person see that you have used the required technology in the past. When you work on projects, you get to discover your weak areas too.

You can work on AWS projects for resume strengthening. If you are new to AWS, then most of the online repositories contain AWS projects for beginners with source code. You can use  AWS projects with source code such as python AWS projects online to get a better understanding of what we’re proceeding with.

An AWS project leverages Amazon Web Services to build, deploy, and manage scalable, secure, and cost-effective cloud applications and infrastructure. It enables businesses to enhance agility, optimize performance, and reduce operational costs through various cloud-based services and tools.

Let’s start looking for AWS projects to build your very own AWS projects!

So, here are a few AWS Projects which beginners can work on:

Top AWS Projects Ideas
 

1. Deploy a Windows Virtual Machine
2. Create a Website on AWS
3. Launch a Serverless Web App
4. Set up Kubernetes Clusters on Amazon EC2 Spot
5. Build a Content Recommendation System
6. Use Rekognition and Identify Famous People
7. Use Lex to Create Chatbots
8. Train a Machine Learning Model with SageMaker

This list of AWS projects for students is suited for beginners, intermediates & experts. These AWS projects will get you going with all the practicalities you need to succeed in your career. You will find most of these AWS projects with source code online.

Further, if you’re looking for AWS projects for final year, this list should get you going. So, without further ado, let’s jump straight into some AWS projects that will strengthen your base and allow you to climb up the ladder.

Here are some AWS project ideas with source code that should help you take a step forward in the right direction.

1. Deploy a Windows Virtual Machine

One of the best ideas to start experimenting you hands-on AWS projects for students is working on deploying a windows virtual machine. Virtual machines are emulations of computer systems. The more sophisticated definition says that a virtual machine is a product abstracted resources of a physical device.

They are isolated environments within the system, which means they operate independently of other virtual machines present within the same network. This is one of the most suitable AWS projects for beginners with source code available on online repositories.

Virtual machines find applications in many areas. They are useful in enhancing the efficiency of an operation. You can deploy a Windows virtual machine through AWS and learn how one works. Getting familiar with VMs will help you in becoming a proficient engineer and is quite a necessary skill. 

To deploy a Windows VM in AWS, you can use Amazon Lightsail, simplifying this task considerably. Amazon Lightsail is a cloud platform that provides you with the required resources to build a website or application. Its UI is straightforward to learn, and completing this project will make you familiar with this software. 

Source Code: Deploy a Windows Virtual Machine

Must Read: Free deep learning course!

After you have created the VM, you can use Lightsail to connect with an RDP client. 

2. Create a Website on AWS

One of the best ideas to start experimenting you hands-on AWS projects for students is creating a website. This is among the most straightforward AWS project ideas for students on this list. Here, you have to create a website by using the AWS cloud platform. You can use Amazon Lightsail in this project to simplify things.

As a virtual private server (VPS) provider, Amazon Lightsail offers developers and other users, a simple entry point into AWS for the purpose of creating and hosting applications in the cloud. Lightsail offers SSD-based storage, and its interface is easy to learn. As a beginner, you wouldn’t have any difficulty using this solution to build your website. 

We recommend Amazon Lightsail in this project because it comes pre-configured with many popular web development solutions such as Joomla and WordPress.

We recommend you build a WordPress website because it’s the most popular CMS out there. You should start by creating a blog. WordPress requires a web server as part of an Internet hosting service to act as a network host. On the other hand, if you have worked with websites before, you can build an eCommerce site or a portfolio site. 

Source Code: Create a Website on AWS

Must Read: Cloud Computing Project Ideas

3. Launch a Serverless Web App

It might be one of the advanced AWS projects in this list; however, once you’ve completed it, you’d be familiar with many concepts of AWS and its services. Here are the technologies we’ll use in this project along with their purpose:

• AWS Amplify – For front-end of the web app and hosting the HTML, CSS, and JS
• Amazon Cognito – For Use management and authentication for the backend API
• Amazon API Gateway and AWS Lambda – For building and using the backed API
• Amazon DynamoDB – For adding a persistence layer for storage

To complete this project, you should be familiar with all of these technologies, including HTML, CSS, and JavaScript. You will also have to implement RESTful APIs in this project, so you should know about their implementations. However, once you’re done, you would know how various Amazon services work together. We recommend building a simple web app first and then making a more complex one. For starters, you can create a BMI calculator or a simple reminder app. Mentioning AWS projects can help your resume look much more interesting than others.

Source Code: Serverless Web App

4. Set up Kubernetes Clusters on Amazon EC2 Spot

This is one of the interesting AWS projects to create. Kubernetes is an open-source solution you can use to automate deployment, management, and scaling of containers. This software enables you to create, manage, and orchestrate containers in cloud computing. It’s among the most significant AWS projects in this list because Kubernetes is a vital skill for cloud-computing professionals. Because Kubernetes is open-source, it’s widely popular in the industry too. This is an excellent AWS projects for beginners.

As you’re working on AWS, you’d have to use Amazon EC2, a service for getting dynamic computing capabilities on the cloud. But we’ll take it a step further and use Amazon EC2 Spot Instances, which allow users to capitalize on most of the capacities of EC2. EC2 Spot Instances and Kubernetes have the same approach towards containers, so you can easily use both of them. Make sure that you adhere to Spot Instances’ best practices while working on this project. You can build multiple node groups and focus on capacity optimization for allocation to ensure the worker nodes function correctly. 

Source Code: Kubernetes Clusters on Amazon EC2

5. Build a Content Recommendation System 

Recommendation systems are among the most popular AI and ML implementations. From Netflix to Flipkart, every major company uses them to enhance user experience and engagement. You can build a recommendation system on the AWS cloud by applying nearest neighbour algorithms. 

In this project, you’d use Amazon SageMaker, an excellent tool for machine learning implementations. It has built-in algorithms that don’t require label data, and it uses semantic search instead of string matching, so using SageMaker will simplify the task considerably. Use the K-Nearest Neighbors algorithm in this project so your recommendation system would provide accurate and practical suggestions to the user. 

Source Code: Content Recommendation System

6. Use Rekognition and Identify Famous People

Computer vision is among the most popular concepts of machine learning and AI. If you’re interested in working on a computer vision project, you should start with this one. If you have some knowledge of Computer vision, you definitely have heard of OpenCV.

With its extensive open-source library for computer vision, machine learning, and image processing, OpenCV has become an integral part of today’s systems’ crucial need for real-time performance. You should be familiar with the basics of computer vision and its related algorithms before you begin working on this project. 

In this project, you have to create a face recognition model that can identify specific people in a picture. Usually, training face recognition takes some time and effort, but because we’re using AWS, things are more comfortable. It is one of the trending AWS projects. You will use Amazon Rekognition in this project to perform face recognition because it allows users to add and analyze images quickly by using deep learning. It is regarded as an API for image analysis, while OpenCV is used for real-time image classification.

This software offers identification of many sorts of objects, activities, people, and text in videos and pictures. This is one of the trending AWS projects. Building and training a facial recognition model will become substantially comfortable with Rekognition. 

In the beginning, you can train your model in identifying a particular famous person, such as MS Dhoni or Robert Dowrey Jr. When you’ve prepared the model, you can test it out and see how well it performs. To make things more complicated, you can train your model to identify multiple people by adding more famous people.  

Source Code: Face Recognition Model

Also Read: Machine Learning Project Ideas

7. Use Lex to Create Chatbots

Chatbots are among the most popular uses of artificial intelligence. They allow companies to enhance customer experience and reduce costs. There are many types of chatbots present, and they all perform different tasks. A chatbot is an application that conducts a conversation with someone else in the place of a person.

Businesses use chatbots to provide quick answers to questions and sometimes to resolve complaints. Around 58% of B2B companies and 42% of B2C companies use chatbots on their sits (source). 

You will use Amazon Lex to build a chatbot in this project. Amazon Lex is a service that simplifies chatbot building for developers. It offers one-click deployment, so when you’ve created the bot, you can add it to multiple platforms. It eases the process of building a chatbot that speaks naturally as you’ll only have to add a few phrases and samples to train the model. 

Moreover, you can easily integrate Amazon Lex with other AWS services (such as AWS Lambda).
Amazon’s AWS Lambda is a serverless, event-driven computing platform. It’s a kind of cloud service that monitors for events and then executes predetermined actions(mainly code execution) in response while handling all of the necessary resource management in the background.

Since most chatbots are created using python, you may look for python AWS projects to look at how other people have integrated python with Amazon Web Services.

Source Code: Use Lex to Create Chatbots

Read: How to make chatbot in Python?

8. Train a Machine Learning Model with SageMaker

The demand for machine learning professionals is soaring, and if you want to enter this sector, you’d have to work on some ML projects too. Amazingly, AWS offers machine learning solutions in its services, and also among which, the most popular is Amazon SageMaker. In this project, you can train a machine learning model by using SageMaker. 

Amazon SageMaker provides you with a unique, integrated development environment for machine learning. The IDE allows you to create notebooks, switch between steps, check the results, and do much more. SageMaker notebooks will enable you to get the compute instances quickly and efficiently. You can also use the Autopilot feature of SageMaker to complete the process with much less effort. 

To work on this project, you should be familiar with machine learning concepts and algorithms. We recommend starting with a simple model if you haven’t worked on an ML project before. You should first begin with a simple question-answering bot with a set of questions present in its options. Then you can work your way up to build a more sophisticated and conversational chatbot. 

Source Code: Train a Machine Learning Model with SageMaker

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Learn More About AWS

These are a few AWS projects that you could try out!

Now go ahead and put to test all the knowledge that you’ve gathered through our data engineering projects guide to build your very own AWS projects!

Working on AWS projects will help you understand its various services and their uses. We hope you found this list of project ideas useful. If you have any questions or suggestions on this article, please let us know in the comments. 

Which AWS project are you going to work on? Which one do you think is the most straightforward project in this list? Share your thoughts.

If you are curious to master Machine learning and AI, boost your career with an our Master of Science in Machine Learning & AI with IIIT-B & Liverpool John Moores University.