229 Microsoft Azure courses in Cardiff delivered Online

Course Overview Clear out all your confusion about cloud computing and learn it from the primary level with the Basic Cloud Computing with Cloud Models course. This course is designed to introduce you to cloud computing fundamentals and to give you the opportunity to add a valuable certificate to your resume. This Basic Cloud Computing with Cloud Models course will provide you with a detailed definition of cloud computing. It will introduce you to the five key characteristics of cloud computing. Here, you will learn what SAAS, PAAS and IAAS are. The course will teach you the process of creating a free Azure account. You will become skilled in managing the Azure account with CL and PowerShell. In the easy to follow module, you will receive valuable information on Amazon Web Services. You will understand the techniques of getting free access to AWS and creating free AWS accounts.  This Basic Cloud Computing with Cloud Models course will equip you with the essentials of cloud computing. Enroll in the course and prepare yourself to pursue a career in the relevant industry. Learning Outcomes Learn the definition and importance of cloud computing Familiarize with the five vital characters of cloud computing Understand the process of Azure free account Build the skills to manage Azure with CL and PowerShell Enrich your knowledge of Amazon Web Services Who is this course for? Anyone interested to learn about cloud computing Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path  The Basic Cloud Computing with cloud models course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Cloud Support Engineer Cloud Computing Engineer IT Support and Cloud Engineer Cloud Computing Analyst Cloud Computing Administrator Introduction Introduction 00:01:00 The Need for Cloud Computing 00:13:00 The Definition of Cloud Computing 00:05:00 Evolution of Cloud and Cloud Models 00:05:00 What is SAAS , PAAS and IAAS 00:05:00 Who is responsible for Data in cloud 00:10:00 The Five Key Characteristics of Cloud Computing 00:08:00 Benefits of Cloud Computing 00:09:00 CapEx vs OpEx 00:03:00 Cloud DataCenters : Where are they? 00:02:00 What is Gartner Say About Cloud Providers 00:02:00 Please Read This 00:01:00 Let's Talk Azure How to create Azure Free Account 00:02:00 How to Login to Azure Portal 00:10:00 Managing Azure with CLI 00:04:00 Let's Learn AWS Foot Prints of Amazon Web Services 00:14:00 AWS Console Tour 00:10:00 Free access to AWS 00:03:00 Creating a Free AWS Account 00:03:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

This is a comprehensive course for using HashiCorp Packer in your organization. The course teaches you about using HCL2 to create your Packer templates, the new standard moving forward. Explore the core HashiCorp Packer components and access hands-on labs you can perform in your environment.

This comprehensive course is designed to take you on a journey of mastering React, the popular JavaScript library for building dynamic user interfaces, and combining it with the power of .NET API for seamless back-end integration. This course will provide you with a solid foundation and hands-on experience in building full-stack applications.

Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. In this course, you will learn about the various cloud service models and how to manage Azure with CLI.

Prepare for success with the Microsoft PL-900 Certification Course, covering the fundamentals of Power Platform, including Power BI, Power Apps, Power Automate, Power Virtual Agents, and related topics such as Dataverse, AI Builder, Connectors, Dynamics 365, Teams, Security, and Administration. Suitable for beginners with no prerequisites.

Description Register on the Machine Learning Model Using AWS SageMaker Canvas 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 Machine Learning Model Using AWS SageMaker Canvas 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 Introduction To Machine Learning What is Machine Learning? 00:04:00 Introduction To AWS What is Amazon Web Services (AWS)? 00:01:00 Signing into AWS Console 00:02:00 Introduction To SageMaker What is SageMaker, and how it is used for Machine Learning? 00:03:00 What is SageMaker Canvas? 00:03:00 Setup SageMaker Domain and User Setup 00:04:00 Setup Data in S3 Buckets for use in SageMaker 00:03:00 SageMaker Canvas Interface Walkthrough Navigating in SageMaker Canvas 00:02:00 Project 01: Banknote Authentication Adding Training Data 00:03:00 Building and Using Model for Prediction 00:03:00 Predict Single & Batch Dataset 00:07:00 Validating Accuracy of Batch Predictions 00:02:00 Project 02: Spam SMS Detection Adding Train & Test Data 00:01:00 Building and Using Model for Prediction 00:03:00 Predicting Data and Validating Accuracy 00:02:00 Project 03: Customer Churn Prediction Adding Data 00:02:00 Building Model 00:03:00 Performing & Validating Predictions 00:04:00 Project 04: Wine Quality Prediction Adding & Joining Datasets 00:04:00 Building Model 00:03:00 Predicting Test Data 00:02:00 Assignment White Wine Quality Prediction 00:02:00 Other Important Features In SageMaker Canvas Versioning 00:04:00 Congratulations & Next Steps Getting Datasets for Practice 00:04:00 Getting Help on SageMaker Canvas 00:04:00 Congratulations & Thankyou 00:01:00 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.

Overview This comprehensive course on Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning with Python comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 4 sections • 21 lectures • 01:34:00 total length •Introduction to types of ML algorithm: 00:02:00 •SVM - Python Implementation: 00:06:00 •Introduction to types of ML algorithm: 00:02:00 •Importing a dataset in python: 00:02:00 •Resolving Missing Values: 00:06:00 •Managing Category Variables: 00:04:00 •Training and Testing Datasets: 00:07:00 •Normalizing Variables: 00:02:00 •Normalizing Variables - Python Code: 00:03:00 •Summary: 00:01:00 •Simple Linear Regression - How it works?: 00:04:00 •Simple Linear Regreesion - Python Implementation: 00:07:00 •Multiple Linear Regression - How it works?: 00:01:00 •Multiple Linear Regression - Python Implementation: 00:09:00 •Decision Trees - How it works?: 00:05:00 •Random Forest - How it works?: 00:03:00 •Decision Trees and Random Forest - Python Implementation: 00:04:00 •kNN - How it works?: 00:02:00 •kNN - Python Implementation: 00:10:00 •Decision Tree Classifier and Random Forest Classifier in Python: 00:10:00 •SVM - How it works?: 00:04:00

Managing Successful Machine Learning Projects Machine learning projects are a different beast. You have to secure access to the required data, often from multiple siloed sources. You have to switch back and forth between research mode and execution mode. You have to delicately guide data exploration towards a well-defined machine learning objective. You have to align this machine learning objective with your business objectives. You have to ensure that any sensitive data is adequately protected. How do you tame this beast and lead your project to successful completion? In this presentation, Dr. Neeraj Kashyap will share some practical tips for succeeding at machine learning, gained from his years at Google and in healthcare. We will discuss the life cycles of healthy machine learning projects and unhealthy ones so that you can identify impending disasters and avert them before they get out of hand. Throughout the session, we will emphasize data privacy, because no amount of intelligence is worth compromising your users for.

Discover the thrilling world of artificial intelligence with the 'Machine Learning Course with Python'. Immerse yourself in a voyage from foundational concepts, unveiling the mysteries behind algorithms, to diving deep into the cores of preprocessing, regression, and classification. Crafted meticulously, this course introduces Python as the catalyst, opening doors to data-driven decision-making and predictive analysis, empowering your journey in the ever-evolving field of machine learning. Learning Outcomes Grasp the foundational knowledge of various machine learning algorithms. Attain proficiency in preprocessing data for optimal outcomes. Master the nuances of regression analysis using Python. Delve into the intricacies of classification techniques. Enhance problem-solving abilities with practical Python-driven machine learning applications. Why choose this Machine Learning Course with Python course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Machine Learning Course with Python Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Machine Learning Course with Python course for? Aspiring data scientists eager to harness the power of machine learning. Python enthusiasts aiming to delve into its applications in AI. Professionals in the tech industry seeking a transition into data roles. Academics and researchers wanting to employ machine learning in their work. Business analysts aiming to leverage predictive analytics for better insights. Career path Data Scientist: £40,000 - £70,000 Machine Learning Engineer: £50,000 - £80,000 AI Researcher: £45,000 - £75,000 Data Analyst: £30,000 - £50,000 Python Developer: £35,000 - £65,000 Business Intelligence Developer: £40,000 - £60,000 Prerequisites This Machine Learning Course with Python does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Course with Python was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Module 01: Introduction to Machine Learning Algorithms Introduction to types of ML algorithm 00:02:00 Module 02: Preprocessing Importing a dataset in python 00:02:00 Resolving Missing Values 00:06:00 Managing Category Variables 00:04:00 Training and Testing Datasets 00:07:00 Normalizing Variables 00:02:00 Normalizing Variables - Python Code 00:03:00 Summary 00:01:00 Module 03: Regression Simple Linear Regression - How it works? 00:04:00 Simple Linear Regreesion - Python Implementation 00:07:00 Multiple Linear Regression - How it works? 00:01:00 Multiple Linear Regression - Python Implementation 00:09:00 Decision Trees - How it works? 00:05:00 Random Forest - How it works? 00:03:00 Decision Trees and Random Forest - Python Implementation 00:04:00 Module 04: Classification kNN - How it works? 00:02:00 kNN - Python Implementation 00:10:00 Decision Tree Classifier and Random Forest Classifier in Python 00:10:00 SVM - How it works? 00:04:00 SVM - Python Implementation 00:06:00 Assignment Assignment - Machine Learning Course with Python 00:00:00

Duration 4 Days 24 CPD hours This course is intended for This four-day course is intended for Windows Server Hybrid Administrators who have experience working with Windows Server and want to extend the capabilities of their on-premises environments by combining on-premises and hybrid technologies. Windows Server Hybrid Administrators who already implement and manage on-premises core technologies want to secure and protect their environments, migrate virtual and physical workloads to Azure Iaas, enable a highly available, fully redundant environment, and perform monitoring and troubleshooting. This course teaches IT Professionals to configure advanced Windows Server services using on-premises, hybrid, and cloud technologies. The course teaches IT Professionals how to leverage the hybrid capabilities of Azure, how to migrate virtual and physical server workloads to Azure IaaS, and how to secure Azure VMs running Windows Server. The course also teaches IT Professionals how to perform tasks related to high availability, troubleshooting, and disaster recovery. The course highlights administrative tools and technologies including Windows Admin Center, PowerShell, Azure Arc, Azure Automation Update Management, Microsoft Defender for Identity, Azure Security Center, Azure Migrate, and Azure Monitor. Prerequisites An understanding of the following concepts as related to Windows Server technologies: High availability and disaster recovery Automation Monitoring Troubleshooting 1 - Secure Windows Server user accounts Configure user account rights Protect user accounts with the Protected Users group Describe Windows Defender Credential Guard Block NTLM authentication Locate problematic accounts 2 - Hardening Windows Server Describe Local Password Administrator Solution Configure Privileged Access Workstations Secure domain controllers Analyze security configuration with Security Compliance Toolkit Secure SMB traffic 3 - Windows Server update management Explore Windows Update Outline Windows Server Update Services server deployment options Define Windows Server Update Services update management process Describe the process of Update Management 4 - Secure Windows Server DNS Implement split-horizon DNS Create DNS policies Implement DNS policies Secure Windows Server DNS Implement DNSSEC 5 - Implement Windows Server IaaS VM network security Implement network security groups and Windows IaaS VMs Implement adaptive network hardening Implement Azure Firewall and Windows IaaS VMs Implement Windows firewall with Windows Server IaaS VMs Choose the appropriate filtering solution Deploy and configure Azure firewall using the Azure portal Capture network traffic with network watcher Log network traffic to and from a VM using the Azure portal 6 - Audit the security of Windows Server IaaS Virtual Machines Describe Azure Security Center Enable Azure Security Center in hybrid environments Implement and assess security policies Protect your resources with Azure Security Center Implement Azure Sentinel 7 - Manage Azure updates Describe update management Enable update management Deploy updates View update assessments Manage updates for your Azure Virtual Machines 8 - Create and implement application allowlists with adaptive application control Describe adaptive application control Implement adaptive application control policies 9 - Configure BitLocker disk encryption for Windows IaaS Virtual Machines Describe Azure Disk Encryption and server-side encryption Configure Key Vault for Azure Disk Encryption Encrypt Azure IaaS Virtual Machine hard disks Back up and recover data from encrypted disks Create and encrypt a Windows Virtual Machine 10 - Implement change tracking and file integrity monitoring for Windows IaaS VMs Implement Change Tracking and Inventory Manage Change Tracking and Inventory Manage tracked files Implement File Integrity Monitoring Select and monitor entities Use File Integrity Monitoring 11 - Introduction to Cluster Shared Volumes Determine the functionality of Cluster Shared Volumes Explore the architecture and components of Cluster Shared Volumes Implement Cluster Shared Volumes 12 - Implement Windows Server failover clustering Define Windows Server failover clustering Plan Windows Server failover clustering Implement Windows Server failover clustering Manage Windows Server failover clustering Implement stretch clusters Define cluster sets 13 - Implement high availability of Windows Server VMs Select high-availability options for Hyper-V Consider network load balancing for Hyper-V VMs Implement Hyper-V VM live migration Implement Hyper-V VMs storage migration 14 - Implement Windows Server File Server high availability Explore the Windows Server File Server high-availability options Define Cluster Shared Volumes Implement Scale-Out File Server Implement Storage Replica 15 - Implement scale and high availability with Windows Server VM Describe virtual machine scale sets Implement scaling Implement load-balancing VMs Create a virtual machine scale set in the Azure portal Describe Azure Site Recovery Implement Azure Site Recovery 16 - Implement Hyper-V Replica Define Hyper-V Replica Plan for Hyper-V Replica Configure and implement Hyper-V Replica Define extended replication Define Azure Site Recovery Implement Site Recovery from on-premises site to Azure Implement Site Recovery from on-premises site to on-premises site 17 - Protect your on-premises infrastructure from disasters with Azure Site Recovery Azure Site Recovery overview Workloads supported for protection with Azure Site Recovery Run a disaster recovery drill Failover and failback 18 - Implement hybrid backup and recovery with Windows Server IaaS Describe Azure Backup Implement recovery vaults Implement Azure Backup policies Recover Windows IaaS Virtual Machines Perform file and folder recovery Perform backup and restore of on-premises workloads Manage Azure Virtual Machine backups with Azure Backup service 19 - Protect your Azure infrastructure with Azure Site Recovery What is Azure Site Recovery Prepare for disaster recovery with Azure Site Recovery Run a disaster recovery drill Failover and failback using Azure Site Recovery 20 - Protect your virtual machines by using Azure Backup Azure Backup features and scenarios Back up an Azure virtual machine by using Azure Backup Restore virtual machine data 21 - Active Directory Domain Services migration Examine upgrade vs. migration Upgrade a previous version of Active Directory Domain Services to Windows Server 2022 Migrate to Active Directory Domain Services in Windows Server 2022 from a previous version Explore the Active Directory Migration Tool 22 - Migrate file server workloads using Storage Migration Service Storage Migration Service overview and usage scenarios Storage migration requirements Migrate a server with Storage migration Evaluate storage migration considerations 23 - Migrate Windows Server roles Describe the Windows Server Migration Tools Install the Migration Tools Migrate roles using the Migration Tools 24 - Migrate on-premises Windows Server instances to Azure IaaS virtual machines Plan your migration Describe Azure Migrate Perform server assessment Assess physical servers with Azure Migrate Migrate Windows Server workloads by using Azure Migrate 25 - Upgrade and migrate Windows Server IaaS virtual machines Describe Azure Migrate Migrate Windows Server workloads by using Azure Migrate Describe storage migration Migrate file servers by using Storage Migration Service 26 - Containerize and migrate ASP.NET applications to Azure App Service Azure Migrate App Containerization overview 27 - Monitor Windows Server performance Use Performance Monitor to identify performance problems Use Resource Monitor to review current resource usage Review reliability with Reliability Monitor Implement a performance monitoring methodology Use Data Collector Sets to analyze server performance Monitor network infrastructure services Monitor virtual machines running Windows Server Monitor performance with Windows Admin Center Use System Insights to help predict future capacity issues Optimize the performance of Windows Server 28 - Manage and monitor Windows Server event logs Describe Windows Server event logs Use Windows Admin Center to review logs Use Server Manager to review logs Use custom views Implement event log subscriptions 29 - Implement Windows Server auditing and diagnostics Describe basic auditing categories Describe advanced categories Log user access Enable setup and boot event collection 30 - Troubleshoot Active Directory Recover objects from the AD recycle bin Recover the AD DS database Recover SYSVOL Troubleshoot AD DS replication Troubleshoot hybrid authentication issues 31 - Monitor Windows Server IaaS Virtual Machines and hybrid instances Enable Azure Monitor for Virtual Machines Monitor an Azure Virtual Machine with Azure Monitor Enable Azure Monitor in hybrid scenarios Collect data from a Windows computer in a hybrid environment Integrate Azure Monitor with Microsoft Operations Manager 32 - Monitor your Azure virtual machines with Azure Monitor Monitoring for Azure VMs Monitor VM host data Use Metrics Explorer to view detailed host metrics Collect client performance counters by using VM insights Collect VM client event logs 33 - Troubleshoot on-premises and hybrid networking Diagnose DHCP proble