In the AWS Cloud Quest course, you play a role and solve real-world cloud problems in a virtual city. It makes learning fun and hands-on while helping you build useful skills in the Cloud Practitioner, Developer, Security, and Machine Learning tracks.
Level
Advanced
Duration
8 weeks



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The AWS Cloud Quest course is a fun, interactive way to learn AWS skills. Students explore a virtual city and solve problems that are similar to those they would face in the real world when using the cloud. It has specialized tracks like Machine Learning, Developer, Practitioner, and Security. Each quest includes hands-on labs that help you learn how to use AWS services. This course makes learning about the cloud interesting, fun, and useful for all levels.
Working professional who is carrying more then 10 years of industry experience.
Access to updated presentation decks shared during live training sessions.
E-book provided by TechPratham. All rights reserved.
Module-wise assignments and MCQs provided for practice.
Daily Session would be recorded and shared to the candidate.
Live projects will be provided for hands-on practice.
Expert-guided resume building with industry-focused content support.
Comprehensive interview preparation with real-time scenario practice.
AWS Cloud Quest – Cloud Practitioner Track
Through hands-on tasks like launching EC2, hosting a website, and securing access, this course teaches the basics of AWS services, cloud computing, IAM, and cost management.
AWS Cloud Quest: Cloud Developer
Use AWS tools and services to learn how to design, build, and automate cloud-native apps that can grow.
AWS Cloud Quest: Security
Gain practical experience in identity, data, and threat protection to develop your ability to secure AWS environments.
AWS Cloud Quest: Machine Learning
Learn how to create, train, and implement intelligent models with AWS AI and ML services.
Data Protection and Compliance
Discover how to protect data using AWS's automated security features, compliance monitoring, and encryption.
Machine Learning and AI Services
Utilize AWS AI tools to create, train, and implement intelligent models for practical automation.
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Build a Serverless E-Commerce API
Use AWS Lambda, API Gateway, and DynamoDB to make a serverless backend that handles payments, product listings, and user orders. This project is a good way to practice designing scalable applications and serverless architectures.
Secure a Multi-Tier Web Application
Set up a multi-tier web app on Amazon EC2 and RDS, and then protect it with IAM roles, Security Groups, and AWS WAF. You will use CloudWatch to keep an eye on things and GuardDuty to find threats.
Machine Learning Sentiment Analysis
With Amazon SageMaker, you can make a text sentiment analysis model, train it on sample datasets, and put an API endpoint online. This project shows the whole ML process, from preparing the data to making predictions in real time.

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