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Top 15 AWS Project Ideas in 2024 for All Levels [with Source Code]
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30th May, 2024
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AWS is one of the topmost cloud platforms that allows us to remotely provision and manage computing resources and applications. It is popular and holds the largest market share because of its affordable and easy-to-use services. One of the reasons why cloud computing got famous worldwide is its simplicity to provision and manage computing resources. To help professionals learn cloud computing, create AWS projects, and become job-ready, we provide various Cloud Computing training courses.
As there are numerous opportunities available in cloud computing, young professionals are seeking to learn AWS. Nowadays, AWS has become a viable choice for professionals and organizations that want to develop highly scalable solutions at a low cost. If you want to gain practical experience that can be added to your profile, working on AWS projects is a great way to achieve your goal. In this blog, we will show some interesting AWS project ideas for all professionals, including beginners, intermediate, and advanced.
List of AWS Projects in 2024
Here is a comprehensive list of AWS projects tailored to every skill level, ranging from novice to expert, providing hands-on experience and learning opportunities for all.
| AWS Project Ideas for Beginners | AWS Project Ideas for Intermediate Professionals | AWS Project Ideas for Advanced Professionals |
| 1. Create a Website on AWS h3+ | 6. Launch a Serverless Web App | 11. Kubernetes Clusters on Amazon EC2 Spot |
| 2. Mass Emailing using AWS Lambda | 7. Use Lex to Create Chatbots | 12. Build a Traffic Monitoring Tool |
| 3. Building Custom Alexa Skills | 8. Creating Real-time Data Processing Application | 13. Orchestrate Redshift ETL using AWS Glue and Step Functions |
| 4. Creating a Text-to-speech Converter | 9. Create Attendance Automation | 14. Serverless Image Recognition Engine |
| 5. Content Recommendation System | 10. Creating a Personalized News Feed | 15. Creating Personalized News Feed |
Top AWS Project Ideas for Beginners/Freshers
Are you an aspiring AWS professional looking for a smooth transition to AWS? If yes, then this will help you in getting your dream job. Students or professionals who are new to AWS can get started with AWS projects for beginners. Final-year students can take up these AWS real-time projects for practice. Some suitable AWS projects for final-year students include:
1. Create a Website on AWS h3+
What could be better than creating a website to get started? Creating a website can be a simple AWS project for students to start experimenting with the AWS platform and services. You can use the Amazon Lightsail service to create a website on the platform. Amazon Lightsail is an AWS-managed virtual private server that can help you create websites.
With Amazon Lightsail, you would get all the important resources required to build a website for free. It provides leading CMSs for hosting websites such as Magneto, WordPress, and Joomla. You can deploy a website (e.g., blog) easily using any of your preferred CMS. This project will help you learn how to choose a CMS and deploy a website without writing its code from scratch. CMSs are pre-configured web development solutions used for managing content for websites. Amazon S3 and EC2 instances can also be used to host a website. Students can do this project as an AWS mini project while studying.
Source code: GitHub
2. Mass Emailing using AWS Lambda
projectpro
This AWS beginner project helps you build an email application using AWS Lambda that can send mass emails to a large audience. AWS Lambda can be utilized with other email or SMS services to create a cost-effective mass mailing solution. You can use AWS SES (Simple Email Service) to send emails and AWS SNS (Simple Notification Service) to trigger the email-sending process.
Amazon Lambda is closely linked to the S3 service in this project. Once you upload a CSV file to S3, an S3 event is triggered. This makes the Lambda function import the file into the database. After the file is imported, the process of mass emailing begins. Students can easily do this AWS projects for practice.
Source Code: Mass Emailing
3. Building Custom Alexa Skills
This AWS sample project for beginners aims to build a virtual assistant like Alexa and replicate its behavior. You can create custom Alexa Skills using AWS Lambda and the Alexa Skills Kit. "Alexa Skills" are the actions that Alexa takes in response to user requests. An Alexa Skill is essentially a voice-activated Alexa app. Alexa handler function, a function of AWS Lambda, can be used in this project. The Lambda service allows you to implement customized logic for invoking the handler function.
Furthermore, this project offers the flexibility to incorporate third-party functions that are hosted outside of Alexa. This means you can explore various possibilities, such as playing music, setting reminders, or executing other specific functions. You can develop voice-enabled applications that can do different tasks like booking a hotel room, ordering food, or playing music. Know more about how to develop Alexa skills to get a detailed picture of how AWS can help you.
Source Code: GitHub
4. Creating a Text-to-speech Converter
This project on AWS involves building a text-to-speech converter using AWS Lambda and AWS Polly (a text-to-speech converter service). The text-to-speech converter is nowadays widely used in modern applications as well as websites. This service converts written text into spoken audio in different languages and voices. You can develop real-life speech synthesis applications using AWS Lambda and AWS Polly. This AWS sample project will help you learn how to use AI-powered AWS services for text-to-speech conversion.
Source Code: GitHub
5. Content Recommendation System
You can build a content recommendation system using Amazon SageMaker, a machine learning service offered by AWS. Most streaming platforms, including Netflix and Amazon Prime Video, already utilize content recommendation systems. This AWS project example is highly relevant nowadays when social media is widely using content recommendation systems to present things of our interest. This project helps you recommend content to end users based on their past online behavior or actions with the help of AI and ML.
You can use Amazon SageMaker to recommend services, products, or content based on the browsing history, purchase behavior, and preferences of users. It comes with in-built ML algorithms that do not require label data and leverages semantic search to simplify tasks. When AWS is used along with nearest-neighbor algorithms, you can get relevant recommendations and accurate results. For accurate and realistic suggestions, use the K Nearest Neighbor algorithm with the content recommendation system for this project.
Source Code: GitHub
Top AWS Project Topics for Intermediate Professionals
If you are someone who has practiced basic projects on AWS and want to practice more AWS projects for resume, the following project ideas can help you:
1. Launch a Serverless Web App
This project involves creating a serverless web application using various AWS services such as Amazon Cognito, DynamoDB, Amplify, API Gateway, and Lambda. These services help in the development of a robust web application that can manage any type of workloads. Launching a serverless web app requires you to have knowledge of technologies like JavaScript, CSS, and HTML. Also, the knowledge of implementing RESTful APIs is required as you need to implement RESTful APIs in this project. Start with a simple web app, for example, a BMI calculator.
Source code: GitHub
2. Use Lex to Create Chatbots
You can use Amazon Lex to create chatbots that can interact with users in a conversational tone like a human agent. As Amazon Lex is a natural language processing service, it can help you develop chatbots that can perform multiple tasks, such as answering customer queries, booking appointments, or providing product information.
With Amazon Lex, you can deploy chatbots in one click and respond to both voice-based and text-based customer queries. Building chatbots will require you to implement AI models to make the chatbot responses automated and conversational. You can easily integrate Amazon Lex with other AWS services for added functionalities. To ensure the responses work as intended, test them by having conversations with them from the perspective of users.
Source code: GitHub
3. Creating Real-time Data Processing Application
projectpro You can build a real-time data processing application using Amazon Kinesis along with Amazon Lambda. The project involves processing large amounts of data to get highly accurate results in real time. Amazon Kinesis helps in capturing and processing streaming data in real time. Use this service to develop an application for analyzing and processing data when it arrives (e.g., streaming data from any social media platform or IoT sensors).
You must create an Amazon Kinesis stream first and then configurqe it to collect data from a web source. You can configure the Lambda function instances to scale up/down automatically with respect to the stream. Location-based data and social media timelines can be used as data sources.
Source Code: GitHub
4. Create Attendance Automation
You can build an attendance automation system using Amazon Rekognition, Amazon Lightsail, and Amazon Cognito. Amazon Rekognition helps recognize and identify faces in images and videos. You can use this service to develop an application that can automate the attendance process, such as scanning the faces of students or employees and marking their attendance. For this, the faces of the users are scanned and added using Amazon Rekognition to server-side containers called Collections. These containers scan and read the identity cards using deep learning algorithms for marking attendance.
Source code: GitHub
5. Creating a Personalized News Feed
You can build a personalized news feed based on your preferences and past browsing and search history. For a personalized delivery platform, you can use AWS Lambda and DynamoDB. Information can be extracted from different touch points and stored in DynamoDB. Later, user profiles can be developed using the stored information. Lambda uses this data to create customized news feeds.
Source Code: GitHub
Top AWS Project Ideas for Advanced Professionals
If you want to work on some high-level AWS real-time projects, consider the following project ideas:
1. Kubernetes Clusters on Amazon EC2 Spot
In this AWS DevOps project, you can build a Kubernetes cluster on Amazon EC2 Spot instances, a cost-effective option for running applications that can handle interruptions. For orchestrating, managing, and scaling containers, Kubernetes is widely used in the industry. You can use either Kubernetes or Amazon EKS for this project to deploy and manage your cluster and use Amazon EC2 Spot instances to save costs on running your applications. While working with spot instances, ensure that best practices for spot instances are followed.
Source Code: GitHub
2. Build a Traffic Monitoring Tool
This AWS IoT project involves creating a Smart Traffic Control framework using AWS IoT. You can use this service along with Amazon Kinesis to gather and analyze traffic from different sources, including web servers, and databases. AWS IoT supports various connection protocols, including HTTPS, MQTT, LoRaWAN, and MQTT over WSS for data transfer between AWS and devices.
Source code: GitHub
3. Orchestrate Redshift ETL using AWS Glue and Step Functions
In this project, build an ETL Big Data pipeline using Amazon Redshift to extract business insights from the stored data. Amazon Redshift is a cloud warehouse service that is fully managed by AWS. With Redshift, you can query structured or unstructured data directly from Amazon S3 even when the data is not deployed in the Redshift cluster. It also helps in running complex analytics queries against data and supports sophisticated query optimization, parallel query execution, and columnar storage.
You can utilize the dataset containing seller and product information from the Amazon E-commerce website for deep learning, machine learning, and natural language processing. For this project, use the Amazon Customer Reviews dataset that contains product reviews from numerous Amazon customers. This dataset can be downloaded in two formats: Parquet and TAV.
Source code: GitHub
4. Serverless Image Recognition Engine
You can build a serverless image recognition app (similar to NatGeo) that can recognize images uploaded to the app automatically using AWS services like AWS Lambda, DynamoDB, and Amazon Rekognition. You can use this service to analyze images and videos in real time and recognize objects, people, and text in them. Lambda functions will identify the patterns in the uploaded image using Rekognition and invoke the metadata in the image. Use DynamoDB for the application back-end maintenance.
Source code: GitHub
5. Creating Personalized News Feed
You can design a personalized news feed that caters to user preferences based on their browsing history and search records. You can use AWS Lambda and DynamoDB for creating this content delivery platform. Extract data from different customer touchpoints and store it within DynamoDB to create user profiles. AWS Lambda will use this data to curate tailored news feeds that cater specifically to each user.
Source code: GitHub
Why You Should Work on AWS Projects?
In this competitive market, it is difficult for professionals who have just a theoretical understanding of AWS to get a job. How can AWS cloud projects help? Well, if you work on a variety of AWS real-time projects, you will understand how to use AWS services in real time and get familiar with the issues that arise while working on the platform.
You can learn how to build scalable and reliable applications, manage infrastructure using automation tools, and create efficient solutions that are cost-effective. Having AWS real-time project examples on your resume can help you get shortlisted and even hired with significantly higher chances. Moreover, you can identify the weak areas where you need to improve, while working on these projects. This would help you strengthen your AWS skills and become an expert.
Source code: GitHub
Why is Learning AWS Important?
AWS provides a flexible solution to emerging and existing businesses that want to minimize the costs of their IT infrastructure without investing in maintenance and capital expenditure. With AWS, they can simply use computing resources whenever they want and can save a lot. Over 95% of new digital workloads will be implemented on the cloud by 2025, according to Gartner's prediction.
You should consider learning AWS for multiple reasons:
- It offers many useful and easy-to-use tools and services at an affordable price.
- You can provision any sort of applications or servers on AWS as its infrastructure is highly scalable and reliable to handle workloads of all types.
- AWS dominates the market and has a large client base, making it a highly sought-after skill these days.
By acquiring this skill, you can be in demand and stay up-to-date with the current industry trends. Top organizations like Adobe, Netflix, Facebook, and Twitter use AWS for providing their services, making it a viable choice for young professionals. Learning AWS can open the door to an ample number of great opportunities in India as well as abroad. As a beginner, start with the AWS Practitioner Certification to get familiar with AWS services.
Wrapping Up
AWS provides numerous services and tools for developers and businesses to build scalable and cost-effective applications. Working on AWS hands-on projects can be a great way to gain practical experience with AWS services and tools and showcase your skills to potential employers. For more clarity, we have included some AWS projects with source code. We hope this blog provided you with some exciting AWS project ideas that you can work on as a beginner, intermediate professional, or advanced user. To start the journey as an AWS professional, enroll in KnowledgeHut's AWS Practitioner Certification.
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Frequently Asked Questions (FAQs)
1. Are AWS skills in demand?
Due to the increasing adoption of cloud computing industry-wide, AWS skills are in high demand. As many organizations are migrating to AWS, the demand for skilled AWS professionals seems to increase further. Gaining AWS skills can open up the doors of opportunities like Cloud Engineers, DevOps Engineers, Security Engineers, etc.
2. How valuable is AWS experience?
Having AWS experience is highly valuable in the current and future scenarios when organizations are moving rapidly to AWS. With hands-on experience on AWS, you will be given more preference in the job market than others. As the demand for AWS professionals is anticipated to increase, you will be more likely to be hired quickly and comfortably.
3. Where can I find AWS Projects for Practice?
You will find many unique and exciting AWS projects for practice on Github.
4. How do I put AWS experience on my resume?
When adding AWS experience to your CV, consider the following points:
- Add specific skills that you are good at. Highlight your strong areas where you are an expert.
- Mention the real-time projects you worked on in detail.
- Show end results; what you achieved via that project (e.g., cost savings or increased productivity)
- Mention your AWS certifications.
5. What are Some Small Projects using AWS will be great for Resume?
These are simple AWS projects that would look great on a resume:
- Develop a serverless web application with API Gateway and AWS Lambda.
- Develop a chatbot using AWS Lex and Lambda.
- Using AWS S3 and CloudFront, create a static webpage.
- Build a database using AWS DynamoDB and Lambda.
- Set up a continuous deployment pipeline with AWS CodePipeline and CodeDeploy.
6. What are the different jobs that I can get with AWS experience?
As AWS is becoming quite popular, many new jobs have emerged in the market that are directly linked to AWS. Multiple streams are available for AWS professionals to choose from, ranging from Solutions Architects to Data Engineers.
- Solutions Architects: Design suitable cloud solutions for client needs.
- SysOps Administrators: Manage cloud infrastructure on AWS.
- Software Developers: Enhance application scalability, security, and performance with AWS integration.
- DevOps Engineers: Streamline development and operations for efficient software delivery.
- ML Engineers: Work on data preprocessing, model training, and model deployment.
- Data Engineers: Handle data storage, processing, and analytics with AWS services.
- Security Engineers: Secure cloud environments from cyber threats using AWS services
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