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Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants: Individuals planning to deploy applications and create application environments on Google Cloud Developers, systems operations professionals, and solution architects getting started with Google Cloud. Executives and business decision makers evaluating the potential of Google Cloud to address their business needs. Overview This course teaches participants the following skills: Identify Google Cloud counterparts for AWS IaaS, AWS PaaS, AWS SQL, AWS Blob Storage, AWS Application Insights, and AWS Data Lake Configure accounts, billing, projects, networks, subnets, firewalls, VMs, disks, auto scaling, load balancing, storage, databases, IAM, and more Manage and monitor applications Explain feature and pricing model differences This course with labs introduces AWS professionals to the core capabilities of Google Cloud Platform (GCP) in the four technology pillars: networking, compute, storage, and database. It is designed for AWS Solution Architects and SysOps Administrators familiar with AWS features and setup and want to gain experience configuring GCP products immediately. With presentations, demos, and hands-on labs, participants will get details of similarities, differences, and initial how-tos quickly. Introducing Google Cloud Explain the advantages of Google Cloud. Define the components of Google's network infrastructure,including: Points of presence, data centers, regions, and zones. Understand the difference between Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) Getting Started with Google Cloud Identify the purpose of projects on Google Cloud Platform. Understand how AWS?s resource hierarchy differs from Google Cloud?s. Understand the purpose of and use cases for Identity and Access Management. Understand how AWS IAM differs from Google Cloud IAM. List the methods of interacting with Google Cloud Platform. Launch a solution using Cloud Marketplace. Virtual Machines in the Cloud Identify the purpose and use cases for Google Compute Engine. Understand the basics of networking in Google Cloud Platform. Understand how Amazon VPC differs from Google VPC. Understand the similarities and differences between Amazon EC2 and Google Compute Engine. Understand how typical approaches to load-balancing in Google Cloud differ from those in AWS. Deploy applications using Google Compute Engine. Storage in the Cloud Understand the purpose of and use cases for: Cloud Storage,Cloud SQL, Cloud Bigtable and Cloud Datastore. Understand how Amazon S3 and Amazon Glacier compare to Cloud Storage. Compare Google Cloud?s managed database services with Amazon RDS and Amazon Aurora. Learn how to choose among the various storage options on Google Cloud Platform. Load data from Cloud Storage into BigQuery. Perform a query on the data in BigQuery. Containers in the Cloud Define the concept of a container and identify uses for containers. Identify the purpose of and use cases for Google Container Engine and Kubernetes. Understand how Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS) differ from GKE. Provision a Kubernetes cluster using Kubernetes Engine. Deploy and manage Docker containers using kubectl Applications in the Cloud Understand the purpose of and use cases for Google App Engine. Contrast the App Engine Standard environment with the App Engine Flexible environment. Understand how App Engine differs from Amazon Elastic Beanstalk. Understand the purpose of and use cases for Google Cloud Endpoints. Developing, Deploying and Monitoring in the Cloud Understand options for software developers to host their source code. Understand the purpose of template-based creation and management of resources. Understand how Cloud Deployment Manager differs from AWS CloudFormation. Understand the purpose of integrated monitoring, alerting, and debugging. Understand how Google Monitoring differs from Amazon CloudWatch and AWS CloudTrail. Create a Deployment Manager deployment. Update a Deployment Manager deployment. View the load on a VM instance using Google Monitoring. Big Data and Machine Learning in the Cloud Understand the purpose of and use cases for the products and services in the Google Cloud big data and machine learning platforms. Understand how Google Cloud BigQuery differs from AWS Data Lake. Understand how Google Cloud Pub/Sub differs from AWS Event Hubs and Service Bus. Understand how Google Cloud?s machine-learning APIs differ from AWS's. Load data into BigQuery from Cloud Storage. Perform queries using BigQuery to gain insight into data. Summary and Review Review the products that make up Google Cloud and remember how to choose among them Understand next steps for training and certification Understand, at a high level, the process of migrating from AWS to Google Cloud. Additional course details: Nexus Humans Google Cloud Fundamentals for AWS Professionals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Google Cloud Fundamentals for AWS Professionals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3.5 Days 21 CPD hours This course is intended for This course is for AWS Cloud Architects with expertise in designing and implementing solutions running on AWS who now want to design for Microsoft Azure. Overview After completing this course, students will be able to: Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects who have previously designed for Amazon Web Services how to translate business requirements into secure, scalable, and reliable solutions for Azure. Introduction to Azure Subscriptions and accounts Resource groups and templates in Azure Resource Manager Azure global infrastructure Azure regions Azure Availability Zones Comparison with AWS Implement Azure Active Directory Introduction to Azure Active Directory Domains and custom domains Safety features Guest users in Azure Active Directory Manage multiple directories Comparison with AWS Implement and manage hybrid identities Introduction to Azure AD Connect Comparison with AWS Implement virtual networking Azure Virtual Network and VNet peering VPN and ExpressRoute connections Comparison with AWS Implement VMs for Windows and Linux Configure high availability Comparison with AWS Implement load balancing and network security Implement Azure Load Balancer Implement an Azure Application Gateway Implement Azure Firewall Implement network security groups and application security groups Comparison with AWS Implement container-based applications Configure Azure Kubernetes Service Publish a solution on an Azure Container Instance Comparison with AWS Implement an application infrastructure Create an App Service plan Create and configure Azure App Service Configure networking for an App Service Introduction to Logic Apps and Azure Functions Comparison with AWS Implement storage accounts Azure Storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Comparison with AWS Implement NoSQL databases Introduction to Azure Cosmos DB Consistency Select appropriate CosmosDB APIs Set up replicas in CosmosDB Comparison with AWS DynamoDB Implement Azure SQL databases Configure Azure SQL database settings Implement Azure SQL Database managed instances Configure high availability for an Azure SQL database Comparison with AWS Implement cloud infrastructure monitoring Monitor security Monitor cost Configure a Log Analytics workspace Comparison with AWS Implement and manage Azure governance solutions Assign RBAC roles Configure management access to Azure Implement and configure an Azure Policy Comparison with AWS Manage security for applications Implement Azure Key Vault Implement and configure Azure AD Managed Identities Register and manage applications in Azure AD Comparison with AWS Migration, backup, and disaster recovery management Migrate workloads Implement Azure Backup for VMs Implement disaster recovery Comparison with AWS

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 175 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies, are using AWS to lower costs, become more agile, and innovate faster.

Duration 3 Days 18 CPD hours This course is intended for Data platform engineers Database administrators Solutions architects IT professionals Overview Apply database concepts, database management, and data modeling techniques Evaluate hosting databases on Amazon EC2 instances Evaluate relational database services (Amazon RDS, Amazon Aurora, and Amazon Redshift) and their features Evaluate nonrelational database services (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune, and Amazon QLDB) and their features Examine how the design criteria apply to each service Apply management principles based on the unique features of each service This course will teach you the process of planning and designing both relational and nonrelational database and the planning and design requirements of all 8 of the AWS databases services, their pros and cons, and how to know which AWS databases service is right for your workloads. Day 1 Module 0: Planning and Designing Databases on AWS Module 1: Database Concepts and General Guidelines Module 2: Database Planning and Design Module 3: Databases on Amazon EC2 Module 4: Purpose-Built Databases Module 5: Databases on Amazon RDS Databases in Amazon Aurora Day 2 Module 6: Databases in Amazon Aurora (continued) Module 7: Databases in Amazon DocumentDB (with MongoDB compatibility) Module 8: Amazon DynamoDB Tables Day 3 Module 9: Databases in Amazon Neptune Module 10: Databases in Amazon Quantum Ledger Database (Amazon QLDB) Module 11: Databases in Amazon ElastiCache Module 12: Data Warehousing in Amazon Redshift Module 13: Course Review Additional course details: Nexus Humans Planning and Designing Databases on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Planning and Designing Databases on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Course Overview The comprehensive Cloud Computing on Amazon AWS has been designed by industry experts to provide learners with everything they need to enhance their skills and knowledge in their chosen area of study. Enrol on the Cloud Computing on Amazon AWS today, and learn from the very best the industry has to offer! This best selling Cloud Computing on Amazon AWS has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Cloud Computing on Amazon AWS is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Cloud Computing on Amazon AWS is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Cloud Computing on Amazon AWS is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Cloud Computing on Amazon AWS, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Cloud Computing on Amazon AWS will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Cloud Computing on Amazon AWS to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

Description Register on the AWS Certified Database Specialty Exam Preparation (DBS-C01) today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The AWS Certified Database Specialty Exam Preparation (DBS-C01) course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content Section 01: Introducing Databases Introduction 00:03:00 AWS Database - Specialty Recommended Knowledge 00:04:00 Databases Defined 00:05:00 Relational Databases 00:08:00 Database Management System (DBMS) 00:09:00 Cloud-Based vs. Local Databases 00:07:00 Database Applications 00:07:00 Database Access Languages 00:05:00 Introducing SQL 00:09:00 Reading Data with SQL 00:09:00 Writing Data with SQL 00:06:00 Working with Database Objects 00:07:00 Section 02: Database Services AWS Database Services 00:05:00 Relational Databases (Aurora, Redshift, RDS) 00:10:00 Key-Value (NoSQL) Databases (DynamoDB) 00:07:00 In-Memory Databases (ElastiCache) 00:06:00 Document Databases (Document DB) 00:06:00 Graph Databases (Neptune) 00:04:00 Time Series Databases (Timestream) 00:03:00 Ledger Databases (QLDB) 00:03:00 Instance-Based Database Servers 00:06:00 Access Control and Authentication 00:07:00 Section 03: Database Design Designing Databases 00:07:00 Using an ERD Tool 00:09:00 Designing Database Solutions 00:07:00 Designing for Performance 00:08:00 Designing for Scalability 00:07:00 Designing for Compliance 00:06:00 Planning for Recovery 00:06:00 Planning for High Availability 00:07:00 Planning for Encryption 00:06:00 Section 04: Database Deployment Creating RDS Databases 00:11:00 Connecting to an RDS Database (MySQL Workbench) 00:06:00 Creating DynamoDB Databases 00:07:00 Creating RedShift Databases 00:07:00 Creating DocumentDB Databases 00:07:00 Creating Instance-Based Databases 00:04:00 Creating Databases from the CLI 00:07:00 Automation of Database Creation 00:09:00 Orchestration of Database Creation 00:09:00 Section 05: Database Migration Migration Strategies 00:09:00 Preparing Data for Migration 00:06:00 Preparing the Cloud to Receive Data 00:07:00 Executing Data Migration 00:08:00 Validating Data Migration 00:05:00 Migrating using DMS 00:11:00 Section 06: Managing Databases General Maintenance Processes 00:07:00 Specific Maintenance Tasks 00:08:00 Backup and Restore Strategies 00:06:00 Performing an Unmanaged Database Backup 00:07:00 Performing a Managed Database Backup 00:05:00 Performing a Restoration 00:05:00 Section 07: Managing Database Services Managing RDS 00:08:00 Managing DynamoDB 00:04:00 Managing Redshift 00:05:00 Managing Other Databases 00:06:00 General Operational Environment Management 00:07:00 Section 08: Monitoring Database Solutions Introduction to Monitoring 00:06:00 AWS Alert Services 00:07:00 Using CloudWatch 00:08:00 Using Third-Party Monitoring Tools 00:06:00 Auditing through Monitoring 00:03:00 Special Security Auditing Tools 00:08:00 Improving Database Performance 00:07:00 Section 09: Troubleshooting Database Solutions Data Access Issues 00:09:00 Database Availability Issues 00:08:00 Database Performance Issues 00:06:00 Data Corruption Issues 00:05:00 Database Size Issues 00:06:00 Security Issues 00:08:00 General Troubleshooting Best Practices 00:07:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

This extensive course for beginners provides the basics of chatbots with machine learning, deep learning, AWS, and its applications, building it from scratch with hands-on practice for chatbot development. This course will help you learn basic to advanced mechanisms of developing chatbots using machine learning, deep learning, and AWS with Python.

The course helps you learn Snowflake from scratch and explore a few of its important features. You will build automated pipelines with Snowflake and use the AWS cloud with Snowflake as a data warehouse. You will also explore Snowpark to be worked on the data pipelines.

Throughout our course, we will provide you with an in-depth understanding of the AWS Certified Solutions Architect Associate course and how to put it into practice.