Fundamentals of Analytics on AWS – Part 2
This course is the second of two offerings designed to introduce learners to the current market trends in analytics. Building upon the concepts introduced in Part 1, this course introduces learners to an overview of data lakes, data warehouses, and modern data architectures on AWS. You will learn about which AWS services can be used to build a data warehouse, data lakes, and modern data architectures on AWS. You will also see common modern data architecture use cases and a reference architecture. Course level: Fundamental Duration: 1 hour 30 minutes Activities This course includes: lessons, videos, scenarios, and knowledge check questions. Course objectives In this course, you will learn to: Explain data lakes, benefits, and functions. Describe the basic data lake architecture, the AWS services used to build a data lake, and challenges with building a data lake. Explain AWS Lake Formation architecture, features and benefits. Explain data warehousing, challenges with an on-premises data warehouse, and available AWS solutions. Explain modern data architecture pillars and modern data architecture concepts. Explain data movement scenarios. Describe the data mesh architecture pattern, benefits, and available AWS solutions. Identify the available AWS services for building modern data architectures. Identify the components of modern data architecture. Describe common use cases for modern data architecture. Intended audience This course is intended for: Cloud architects Data engineers Data analysts Data scientists Developers Prerequisites We recommend that attendees of this course have: Reviewed AWS Cloud Practitioner Essentials or equivalent Completed Fundamentals of Analytics on AWS – Part 1 Course outline Section 1: Introduction Lesson 1: How to Use This Course Lesson 2: Course Overview Section 2: Architectures Lesson 3: Introduction to Data Lakes Lesson 4: Introduction to Data Warehousing Lesson 5: Introduction to Modern Data Architecture Lesson 6: AWS Services for Modern Data Architecture Section 3: Common Use Cases and Reference Architectures Lesson 7: Common Use Cases Lesson 8: Reference Architectures Section 4: Conclusion Lesson 9: Quiz Lesson 10: Course Summary Lesson 11: Appendix of Resources Lesson 12: Feedback
Fundamentals of Analytics on AWS – Part 1
This course is the first of two offerings designed to introduce learners to the current market trends in analytics. In Part 1, you will learn fundamental concepts such as types of analytics, the 5 V’s of big data, and the challenges associated with processing high volumes of data. This course also maps the 5 V’s of big data to AWS services for analytics and discusses how AWS provides the most comprehensive services on the market. Following completion of this course, learners are encouraged to continue their journey with Fundamentals of Analytics on AWS – Part 2 . Course level: Fundamental Duration: 2 hours Activities This course includes: lessons, videos, scenarios, and knowledge check questions. Course objectives In this course, you will learn to: Explain data analytics, data analysis, analytics types, techniques, and analytics challenges. Define machine learning (ML), ML on AWS, and different levels of AWS for ML services. Define the 5 V’s of big data. Explain common ways to store data, challenges, characteristics of source data storage systems, and available AWS solutions. Explain data transportation, options for different environments, and available AWS solutions. Define data processing, options for each type of processing, and available AWS solutions. Identify different types of data structures, types of data storage, and available AWS solutions. Explain where ETL and ELT fits in multiple places of the analytics pipeline, the elements of an ETL and ELT process, and available AWS solutions. Explain the use of business intelligence tools to gain value from analytics, and available AWS solutions. Intended audience This course is intended for: Cloud architects Data engineers Data analysts Data scientists Developers Prerequisites We recommend that attendees of this course have: Reviewed AWS Cloud Practitioner Essentials or equivalent Course outline Section 1: Introduction Lesson 1: How to Use This Course Lesson 2: Course Overview Section 2: Analytics Concepts Lesson 3: Analytics Lesson 4: Machine Learning Lesson 5: 5 Vs of Big Data Lesson 6: Volume Lesson 7: Variety Lesson 8: Velocity Lesson 9: Veracity Lesson 10: Value Section 3: AWS Services for Analytics Lesson 11: AWS Services for Volume Lesson 12: AWS Services for Variety Lesson 13: AWS Services for Velocity Lesson 14: AWS Services for Veracity Lesson 15: AWS Services for Value Section 4: Conclusion Lesson 16: Quiz Lesson 17: Course Summary Lesson 18: Appendix of Resources Lesson 19: Feedback
Amazon Lex Getting Started
Course description Amazon Lex is a fully managed artificial intelligence (AI) service with advanced natural language models to design, build, test, and deploy conversational interfaces for voice and text. In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and cost of Amazon Lex. You will review an […]
Amazon Bedrock Getting Started
Course description: Amazon Bedrock is a fully managed service that offers leading foundation models (FMs) and a set of tools to quickly build and scale generative AI applications. The service also helps ensure privacy and security. In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and cost of Amazon Bedrock. You will also review an architecture that uses Amazon Bedrock, along with other Amazon Web Services (AWS) offerings, to build a chatbot solution. Through a guided tutorial consisting of a narrated video, step-by-step instructions, and transcript, you will try Amazon Bedrock in your AWS account. ‐ Course level: Fundamental ‐ Duration: 1 hour Activities: This course includes presentations, graphics, and a step-by-step tutorial to follow along. Course objectives: In this course, you will learn to: ‐ Understand how Amazon Bedrock works. ‐ Familiarize yourself with basic concepts of Amazon Bedrock. ‐ Recognize the benefits of Amazon Bedrock. ‐ List typical use cases for Amazon Bedrock. ‐ Describe the typical architecture associated with an Amazon Bedrock solution. ‐ Understand the cost structure of Amazon Bedrock. ‐ Implement a demonstration of Amazon Bedrock in the AWS Management Console. Prerequisites We recommend that attendees of this course have completed the following training: ‐ AWS Technical Essentials Course outline ‐ Introduction to Amazon Bedrock ‐ Architecture and Use Cases ‐ How Do You Use Amazon Bedrock? ‐ Learn More
Amazon CodeWhisperer – Getting Started
Amazon CodeWhisperer, an advanced coding companion powered by generative AI, helps increase coding efficiency and productivity by interactively offering code suggestions while you type. This streamlines your coding experience so you can focus on your intent. CodeWhisperer also scans your code for security vulnerabilities from right within your editor. In this course, you will learn how to install and start using CodeWhisperer in your supported integrated development environment (IDE) or code editor. You will also learn how to use the key features of CodeWhisperer, such as code completion, open-source discovery and attribution, security scans, and prompting to generate useful code suggestions. Finally, you will learn about subscription options, including features and costs. • Course level: Fundamental • Duration: 30 minutes Activities • This course includes presentations of concepts and practices, along with brief video demonstrations. Course objectives In this course, you will learn to: • Install, configure, and start using CodeWhisperer. • Describe key advantages and differentiators of CodeWhisperer. • Use CodeWhisperer in multiple coding scenarios. • Access additional information and resources on CodeWhisperer. Intended audience This course is intended for: • Developers • Data scientists • Architects • Platform engineers • CloudOps engineers • Quality assurance engineers • Front-end developers • Anyone who writes code for applications or infrastructure as code (IaC) Prerequisites We recommend that attendees of this course have: • Prior coding experience using IDEs or code editors supported by CodeWhisperer (Visual Studio Code, PyCharm, and other JetBrains IDEs) is recommended but not required. Course outline Introduction to CodeWhisperer • How CodeWhisperer works • Problems solved by CodeWhisperer • Benefits to individuals and teams • Pricing How Do You Set Up a Coding Environment to Use CodeWhisperer? • Install CodeWhisperer into Visual Studio Code • Install CodeWhisperer into PyCharm • Configure CodeWhisperer in AWS Lambda console How Do You Interact with CodeWhisperer to Generate Code? • Prompting CodeWhisperer for code suggestions • Single-line code completion • Full function generation • Coding interactions with Amazon Web Services (AWS) offerings • Reference tracking of accepted code suggestions Resources
AWS Technical Essentials (Arabic)
تقدم لك AWS Technical Essentials خدمات AWS الأساسية والحلول المشتركة. تغطي هذه الدورة مفاهيم AWS الأساسية المتعلقة بالحوسبة وقاعدة البيانات والتخزين والاتصال الشبكي والعلاقات والمراقبة والأمان. ستبدأ العمل في AWS من خلال تجارب الدورة التدريبية العملية. تغطي الدورة المفاهيم اللازمة لزيادة فهمك لخدمات AWS، بحيث يمكنك اتخاذ قرارات مستنيرة بشأن الحلول التي تلبي متطلبات العمل. خلال الدورة التدريبية، ستحصل على معلومات حول كيفية إنشاء حلول سحابية متاحة بدرجة عالية ومتسامحة مع الأخطاء وقابلة للتطوير وفعالة من حيث التكلفة ومقارنتها وتطبيقها. مستوى الدورة التدريبية: أساسية المدة: 4 ساعات الأنشطة تتضمن هذه الدورة العروض التقديمية والعروض التوضيحية ومقاطع الفيديو وفحوصات المعرفة والتقييم. أهداف الدورة ستتعلم في هذه الدورة التدريبية ما يلي: وصف المصطلحات والمفاهيم المتعلقة بخدمات AWS الانتقال إلى وحدة التحكم في الإدارة في AWS توضيح المفاهيم الأساسية لمقاييس أمان AWS وAWS Identity and Access Management (IAM) التمييز بين العديد من خدمات حوسبة AWS، بما فيها Amazon Elastic Compute Cloud (Amazon EC2) وAWS Lambda وAmazon Elastic Container Service (Amazon ECS) وخدمة Amazon Elastic Kubernetes (Amazon EKS) فهم قاعدة بيانات AWS وعروض التخزين، بما فيها Amazon Relational Database Service (Amazon RDS) وAmazon DynamoDB وAmazon Simple Storage Service (Amazon S3) استكشاف خدمات الاتصال الشبكي في AWS الوصول إلى ميزات مراقبة Amazon CloudWatch وتكوينها الجمهور المستهدف تستهدف هذه الدورة ما يلي: الأفراد المسؤولين عن توضيح الفوائد الفنية لخدمات AWS بالنسبة إلى العملاء الأفراد المهتمين بتعلم كيفية البدء باستخدام AWS مسؤولي SysOps تصميمات الحلول المطورون المتطلبات الأساسية نوصي الحاضرين في هذه الدورة بأن يكون لديهم: خبرة في مجال تكنولوجيا المعلومات المعرفة الأساسية بهياكل ومكونات مركز البيانات الشائعة (الخوادم، والاتصال الشبكي، وقواعد البيانات، والتطبيقات، وما إلى ذلك) لا يلزم وجود خبرة سابقة في الحوسبة السحابية أو AWS مخطط الدورة التدريبية مقدمة إلى الدورة التدريبية الوحدة 1: مقدمة إلى Amazon Web Services مقدمة عن AWS Cloud الأمان في AWS Cloud استضافة تطبيق دليل الموظف في AWS عرض توضيحي: مقدمة إلى AWS Identity and Access Management (IAM) الوحدة 2: AWS Compute الحوسبة كخدمة في AWS مقدمة إلى Amazon Elastic Compute Cloud دورة حياة مثيل Amazon EC2 خدمات حاويات AWS ما المقصود بالخدمات دون خادم؟ مقدمة حول AWS Lambda اختيار خدمة الحوسبة الصحيحة عرض توضيحي: إطلاق تطبيق دليل الموظفين على Amazon EC2 الوحدة 3: الاتصال الشبكي في AWS الاتصال الشبكي في AWS مقدمة إلى Amazon Virtual Private Cloud (Amazon VPC) توجيه Amazon VPC أمان Amazon VPC عرض توضيحي: إنشاء VPC وإعادة إطلاق تطبيق دليل الشركة في Amazon EC2 الوحدة 4: تخزين AWS أنواع تخزين AWS تخزين مثيل Amazon EC2 وAmazon Elastic Block Store (Amazon EBS) تخزين العناصر مع Amazon S3 اختيار خدمة التخزين المناسبة عرض توضيحي: إنشاء Amazon S3 Bucket الوحدة 5: قواعد البيانات استكشاف قواعد البيانات في AWS Amazon Relational Database Service قواعد البيانات المبنية لغرض محدد مقدمة إلى Amazon DynamoDB اختيار خدمة قاعدة بيانات AWS الصحيحة عرض توضيحي: تنفيذ Amazon DynamoDB وإدارتها الوحدة 6: المراقبة والتحسين والخدمات دون خادم المراقبة التحسين هندسة تطبيقات دليل الموظف البديلة دون خادم عرض توضيحي: تكوين التوافر العالي لتطبيقك الوحدة 7: ملخص الدورة التدريبية الوحدة 8: تقييم نهاية الدورة التدريبية
AWS Cloud Economics for Healthcare
This course provides an overview of Amazon Web Services (AWS) resources that are uniquely available to the healthcare industry. It includes a survey of AWS resources especially applicable to healthcare. The course explores special topics, such as rightsizing instances to particular needs and budget-saving tools to control spend. There is an emphasis on the agility provided by the AWS Cloud and its relevance to healthcare providers as they grow into new markets and opportunities. Finally, this course shares case studies of cloud adoption for healthcare so customers can use the learning experiences of others when shaping their own journey. Course level: Fundamental Duration: 80 minutes Activities This course includes interactive learning objects, videos, and knowledge check questions. Course objectives After this course, you will be able to do the following: • Understand AWS and who they are as a company. • Understand Cloud Economics and how you can realize their benefits with AWS. • Explain the compute and storage offerings available to the healthcare industry. • Understand the challenges, solutions, and benefits of using AWS services for analytics and purpose-built artificial intelligence (AI) and machine learning (ML) capabilities for healthcare. • Identify AWS Partners and AWS Professional Services and understand how to use them. Intended audience This course is intended for: • Account and Sales Managers • Solutions Architects • Business Development and Analyst Managers • Business Users • Data Scientists • Decision Makers Prerequisites None Course outline Lesson 1: How to Use This Course • Navigating this course • Guidance to learners of AWS Cloud Economics for Healthcare Lesson 2: Amazon Web Services • The Amazon Culture of Innovation • The AWS healthcare team Lesson 3: Cloud Concepts • Cloud computing overview • Cloud computing deployment models • Reasons to use AWS as a cloud provider • Learning more about cloud computing with AWS Lesson 4: Cloud Economics • Cloud Economics overview • Economic benefits of cloud computing • Benefits of Cloud Economics • Pillars of cost optimization • AWS Cloud Value Framework • AWS Free Tier overview • How AWS Pricing works • Managing your costs • Cost management tools Lesson 5: AWS for Health • AWS for Health overview • AWS for Healthcare & Life Sciences • AWS and AWS Partners purpose-built solutions Lesson 6: Compute Offerings for Healthcare • Amazon EC2 overview • EC2 instance types • Amazon EC2 pricing models • AWS Compute Optimizer • High performance computing (HPC) for healthcare • Compute case studies and customer stories • Serverless computing on AWS Lesson 7: Storage Offerings for Healthcare • Cloud storage overview • How cloud storage works • Benefits of cloud storage • Types of cloud storage • AWS storage services • Storage case studies and customer stories Lesson 8: AWS Services for Analytics • AWS services for analytics • Using AWS analytics for healthcare Lesson 9: Purpose-Built AI/ML Services for Healthcare • Purpose-built AI/ML services • Introduction to Amazon HealthLake Lesson 10: AWS Healthcare Partners and AWS Professional Services • AWS Partners • AWS Marketplace • AWS Data Exchange • AWS Professional Services Lesson 11: Resources • Learn more about AWS for Health • Questions and direct engagement about AWS fo
Getting Started with AWS IoT SiteWise
AWS IoT SiteWise is a managed service that streamlines how you collect, organize, and analyze industrial equipment data. In this Getting Started course, you will learn the technical concepts, benefits, and typical use cases of AWS IoT SiteWise. You will also have an opportunity to try the service through a demonstration using the AWS Command Line Interface (AWS CLI) or AWS CloudFormation template. You will learn how to create assets and a dashboard to represent industrial metrics. • Course level: Fundamental • Duration: 1 hour Activities This course includes presentations, graphics, sample code, and interactive activities. Course objectives In this course, you will learn to: • Understand how AWS IoT SiteWise works • Familiarize yourself with the technical concepts of AWS IoT SiteWise • List typical uses cases for AWS IoT SiteWise • Familiarize yourself with how to use AWS IoT SiteWise and the AWS CLI • Familiarize yourself with how to use AWS IoT SiteWise and CloudFormation • Familiarize yourself with how to use AWS IoT Device SDK for Python • Familiarize yourself with how to create a metrics dashboard with AWS IoT SiteWise Intended audience This course is intended for: • Solutions architects • Developers • Data engineers • System operations engineers Prerequisites • Conceptual knowledge of cloud computing • Getting Started with AWS IoT • Getting Started with AWS IoT Greengrass Course outline • Purpose and functionality of AWS IoT SiteWise • How AWS IoT SiteWise is used in cloud solutions • Typical use cases • Points to keep in mind when using AWS IoT SiteWise • Cost • Using AWS IoT SiteWise with AWS CloudFormation, AWS CLI, and Python • Demo cleanup
Getting Started with Amazon Textract
Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents and goes beyond optical character recognition (OCR) to identify, understand, and extract data from forms and tables. In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and costs of Amazon Textract. You will review an architecture for a text-extraction solution using Amazon Textract that you can further adapt to your use case. Through a guided tutorial, you will also try the service in your own Amazon Web Services (AWS) account. • Course level: Fundamental • Duration: 90 minutes Activities This course includes presentations, graphics, and a step-by-step tutorial to follow along. Course objectives In this course, you will do the following: • Understand how Amazon Textract works. • Familiarize yourself with basic concepts of Amazon Textract. • Recognize the benefits of Amazon Textract. • List typical use cases for Amazon Textract. • Describe the typical architectures associated with an Amazon Textract solution. • Specify what it would take to implement Amazon Textract in a real-world scenario. • Understand the cost structure of Amazon Textract. • Implement a demonstration of Amazon Textract in the AWS Management Console. Prerequisites We recommend that attendees of this course have completed the following trainings: • AWS Technical Essentials We also recommend that you review the following resources, if you are not already familiar with AWS Step Functions and AWS Cloud Development Kit (CDK): • Create a Serverless Workflow with AWS Step Functions and AWS Lambda • Getting started with the AWS CDK Course outline • Amazon Textract Basics • How Is Amazon Textract Used to Architect a Solution? • Amazon Textract Use Cases • Amazon Textract Guidelines and Best Practices • Amazon Textract Costs • Using Amazon Textract to Synchronously and Asynchronously Extract Text from Documents • Learn More about Amazon Textract
The Elements of Data Science
Learn to build and continuously improve machine learning models with Data Scientist Harsha Viswanath, who will cover problem formulation, exploratory data analysis, feature engineering, model training, tuning and debugging, as well as model evaluation and productionizing.
Math for Machine Learning
To understand modern machine learning, you also need to understand vectors and matrices, linear algebra, probability theorems, univariate calculus, and multivariate calculus. This course, led by AWS Machine Learning Instructor Brent Werness, covers it all.
