AWS: IoT, Machine Learning and Blockchain from Coursera

AWS: IoT, Machine Learning, and Blockchain is the second course of Exam Prep (SAP-C02): AWS Certified Solutions Architect - Professional Specialization. This course explores key AWS services for building intelligent and connected applications. Learners will gain insights into AWS IoT Core, AWS IoT Events, and IoT Greengrass. The course also covers AI services like Amazon Polly, Translate, Comprehend, Rekognition, Kendra, Personalize, and SageMaker. Additionally, it introduces Managed Blockchain and remote workspace solutions with WorkSpaces and WorkSpaces Web.

This course facilitates learners with approximately 3:00-3:30 Hours of Video lectures that provide both Theory and Hands-On knowledge. Also, Graded and Ungraded Quizzes are provided with every module to test learners' ability.

- Module 1: IoT and Blockchain in AWS

- Module 2: Machine Learning in AWS

This course is designed for professionals seeking to master specialized AWS services beyond core infrastructure. It is ideal for developers, data scientists, architects, and engineers focused on leveraging Artificial Intelligence, Machine Learning, Internet of Things, Blockchain, and End User Computing solutions.

- Senior Solutions Architects

- Enterprise Architects

- Cloud Infrastructure Architects

- Senior DevOps Engineers

By the end of the course, learners will be able to:

- Understand IoT services like AWS IoT Core, IoT Events, and IoT Greengrass.

- Extract data from documents and recognize images using Amazon Textract and Rekognition.

- Discover use cases for Amazon Managed Blockchain and compare virtual desktop solutions with Amazon WorkSpaces vs WorkSpaces Web.

What's inside

Syllabus

Welcome to Week 1 of the AWS: IoT, Machine Learning, and Blockchain course. This week, we'll explore the world of connected devices with AWS IoT Core, including hands-on demos for practical understanding. We'll dive into AWS IoT Events for event-driven automation and AWS IoT Greengrass for local edge computing. Expanding into decentralized technology, we'll introduce Amazon Managed Blockchain to understand secure, scalable blockchain networks. To complete the week, we'll compare Amazon WorkSpaces and WorkSpaces Web, helping you grasp solutions for secure, remote desktop access. By the end of the week, you'll have foundational skills in IoT, blockchain, and virtual workspace solutions, setting the stage for advanced cloud applications.

Career center

Learners who complete AWS: IoT, Machine Learning and Blockchain will develop knowledge and skills that may be useful to these careers:

Cloud Solutions Architect

A Cloud Solutions Architect designs and implements scalable, secure, and cost-effective cloud solutions for organizations. This course is exceptionally well-suited for an aspiring Cloud Solutions Architect as it offers deep insights into specialized AWS services essential for modern architectures. Learners gain practical understanding of integrating IoT devices using AWS IoT Core, building intelligent applications with various Machine Learning services like Amazon SageMaker, and leveraging decentralized systems with Amazon Managed Blockchain. The focus on advanced AWS services goes beyond foundational infrastructure, providing the specialized knowledge required to design innovative solutions that incorporate cutting-edge technologies. This expertise is crucial for crafting robust, intelligent, and future-proof cloud environments. This understanding helps build a foundation to effectively guide clients or internal teams in adopting advanced cloud capabilities.

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Internet of Things Engineer

An Internet of Things Engineer designs, develops, and manages connected devices and their supporting infrastructure. This course serves as an excellent resource for an aspiring Internet of Things Engineer, offering comprehensive coverage of AWS IoT services. Learners will delve into AWS IoT Core for device connectivity, AWS IoT Events for event-driven automation, and AWS IoT Greengrass for edge computing capabilities. The practical and hands-on nature of the course, especially with AWS IoT Core demos, helps build a foundation to confidently implement and manage scalable IoT solutions. Understanding these specific AWS services is crucial for anyone looking to build robust, secure, and intelligent IoT ecosystems within a cloud environment.

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Cloud Infrastructure Architect

A Cloud Infrastructure Architect focuses on designing the foundational cloud environment for an organization, often specifying core services and networking. This course is highly relevant for an aspiring Cloud Infrastructure Architect, as it delves into specialized AWS services crucial for modern infrastructure design. Learners gain insights into structuring environments that support IoT solutions with AWS IoT Core, integrating machine learning capabilities using Amazon SageMaker, and implementing blockchain networks with Amazon Managed Blockchain. The course helps build a foundation to create robust, scalable, and secure cloud infrastructures that underpin advanced applications, including understanding remote workspace solutions with WorkSpaces and WorkSpaces Web. This expertise is vital for architects needing to integrate cutting-edge technologies into their core infrastructure plans.

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Machine Learning Engineer

A Machine Learning Engineer builds, deploys, and maintains machine learning models and systems. For anyone aspiring to be a Machine Learning Engineer, this course provides direct, hands-on exposure to critical AWS AI and ML services. The module on Machine Learning in AWS covers Amazon SageMaker, a powerful platform for building and deploying ML models, alongside services like Amazon Transcribe for speech-to-text, Amazon Lex for chatbots, and Amazon Textract for document processing. This course helps build a foundation to design, implement, and operationalize intelligent applications, giving learners specific tools and knowledge to create scalable and efficient ML solutions within the AWS ecosystem. Understanding these services is paramount for developing production-ready ML systems.

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Enterprise Architect

An Enterprise Architect provides strategic direction and guidance for an organization's entire technology landscape, ensuring alignment with business goals. This course is exceptionally beneficial for an aspiring Enterprise Architect, as it offers a strategic overview of how advanced AWS services like IoT, Machine Learning, and Blockchain can drive digital transformation. Understanding the capabilities of AWS IoT Core, Amazon SageMaker, Amazon Comprehend, and Amazon Managed Blockchain helps build a foundation to identify opportunities for innovation and design holistic, future-proof enterprise solutions. This course helps an Enterprise Architect to effectively advise on technology adoption, integrate cutting-edge capabilities into the broader architectural vision, and lead significant technological shifts. This role often typically requires an advanced degree.

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Computer Vision Engineer

A Computer Vision Engineer develops algorithms and systems that enable computers to interpret and understand visual information. For an aspiring Computer Vision Engineer, this course provides direct exposure to Amazon Rekognition, a powerful AWS service for image and video analysis. Learners will gain an understanding of how to extract data from documents using Amazon Textract and recognize images, which are foundational tasks in computer vision. The course helps build a foundation to leverage cloud-native services for implementing computer vision capabilities without deep algorithmic development, allowing focus on application integration and problem-solving through visual data. This is particularly relevant for deploying scalable vision solutions in the cloud.

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Natural Language Processing Engineer

A Natural Language Processing Engineer develops systems that allow computers to understand, process, and generate human language. This course is highly relevant for an aspiring Natural Language Processing Engineer, as it extensively covers various AWS services central to NLP. Learners will explore Amazon Polly for text-to-speech, Amazon Translate for language translation, Amazon Comprehend for text analytics, Amazon Transcribe for speech-to-text, Amazon Lex for chatbots, and Amazon Textract for document processing. This broad array of services helps build a foundation to design and implement robust NLP solutions, from conversational AI to sophisticated text analysis, all within the scalable AWS ecosystem.

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Artificial Intelligence Specialist

An Artificial Intelligence Specialist focuses on designing and implementing AI-driven solutions across various domains. This course is particularly relevant for an aspiring Artificial Intelligence Specialist, as it provides an extensive exploration of numerous AWS AI services. Learners will gain proficiency with Amazon Polly for text-to-speech, Amazon Translate for language translation, Amazon Comprehend for text analytics, Amazon Rekognition for image and video analysis, Amazon Kendra for intelligent search, and Amazon Personalize for recommendation systems. This broad exposure to ready-to-use AI functionalities on AWS helps build a foundation to integrate sophisticated AI capabilities into diverse applications, enabling the creation of intelligent and responsive systems.

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Blockchain Developer

A Blockchain Developer designs and implements decentralized applications and blockchain networks. This course offers fundamental insights into Amazon Managed Blockchain, making it a valuable starting point for an aspiring Blockchain Developer. Although it may not cover deep smart contract development, understanding a managed service like AWS Managed Blockchain is crucial for leveraging scalable and secure blockchain networks within an enterprise cloud context. The course helps build a foundation to understand the underlying infrastructure and operational aspects of blockchain technology on a leading cloud platform. This knowledge is particularly helpful for integrating blockchain solutions with other cloud services, a common requirement in modern distributed applications.

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Technical Product Manager

A Technical Product Manager defines the strategy, roadmap, and features for technology products, requiring a deep understanding of the underlying technology. For an aspiring Technical Product Manager focusing on IoT, Machine Learning, or Blockchain products, this course is particularly insightful. It provides a detailed overview of the capabilities and limitations of key AWS services like IoT Core, Amazon SageMaker, and Amazon Managed Blockchain. This course helps build a foundation to make informed decisions about product architecture, feature prioritization, and market positioning. Understanding these specialized AWS offerings helps in communicating effectively with engineering teams and identifying innovative solutions for product development. This role often typically requires an advanced degree.

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Research Scientist: Machine Learning

A Research Scientist Machine Learning focuses on developing new algorithms and advancing the state of the art in machine learning. This course may be useful for an aspiring Research Scientist Machine Learning by providing a practical understanding of deploying and experimenting with models using Amazon SageMaker. While its primary focus is not on theoretical research, familiarity with cloud-based ML platforms and integrated AI services helps build a foundation to operationalize research outcomes and leverage scalable computational resources. Understanding services like Amazon Rekognition and Transcribe can also inspire research directions in applied AI. This role typically requires an advanced degree, often a doctorate.

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Data Scientist

A Data Scientist extracts insights from complex datasets, develops predictive models, and applies statistical methods. While the course doesn't cover general statistical theory, it may be useful for an aspiring Data Scientist by providing practical experience with Amazon SageMaker for building and deploying machine learning models. Additionally, the exposure to services like Amazon Comprehend for text insights and Amazon Rekognition for image analysis helps build a foundation to process and derive information from unstructured data types. For a Data Scientist aiming to operationalize models and leverage cloud-native AI tools, this course offers direct experience with the platforms and services critical for deploying data-driven solutions at scale. This role often typically requires an an advanced degree.

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Cloud Engineer

A Cloud Engineer designs, builds, and maintains cloud infrastructure and services. This course may be helpful for an aspiring Cloud Engineer looking to specialize in deploying and managing advanced applications on AWS. Beyond core infrastructure, the course delves into specialized services like AWS IoT Core, Amazon Managed Blockchain, and a suite of Machine Learning services. Understanding these enables a Cloud Engineer to support intelligent applications, connected devices, and decentralized systems. The course helps build a foundation to architect and implement robust cloud environments that can host cutting-edge technologies, crucial for modern cloud deployments. Knowledge of virtual desktop solutions like Amazon WorkSpaces also contributes to a comprehensive skill set for managing diverse cloud environments.

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Data Engineer

A Data Engineer builds and maintains robust data pipelines and infrastructure that support data-driven applications. This course may be useful for an aspiring Data Engineer, especially one focusing on data relevant to IoT deployments or machine learning workflows. Understanding AWS IoT Core provides insight into ingesting data from connected devices, while familiarity with Amazon SageMaker and other AI services helps build a foundation to design data pipelines that prepare and process data for machine learning models. The course helps facilitate the ability to create scalable data infrastructure that feeds intelligent applications and extracts value from diverse data sources, ensuring data quality and availability for downstream analytics and AI initiatives.

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DevOps Engineer

A DevOps Engineer focuses on streamlining the software development lifecycle, emphasizing automation and continuous delivery. This course may be useful for an aspiring DevOps Engineer, particularly those supporting applications that integrate IoT, Machine Learning, or Blockchain technologies on AWS. Understanding these specialized services, from deploying ML models with Amazon SageMaker to managing IoT device fleets via AWS IoT Core, helps build a foundation to implement effective CI CD pipelines and operational monitoring for intelligence-driven solutions. The course helps facilitate the ability to manage the infrastructure and deployment patterns required for cutting-edge cloud applications, ensuring reliability and scalability from a DevOps perspective.

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