27672 Courses

In this competitive job market, you need to have some specific skills and knowledge to start your career and establish your position. This AWS Solutions Architect & SysOps Administrator will help you understand the current demands, trends and skills in the sector. The course will provide you with the essential skills you need to boost your career growth in no time. The AWS Solutions Architect & SysOps Administrator will give you clear insight and understanding about your roles and responsibilities, job perspective and future opportunities in this field. You will be familiarised with various actionable techniques, career mindset, regulations and how to work efficiently. This course is designed to provide an introduction to AWS Solutions Architect & SysOps Administrator and offers an excellent way to gain the vital skills and confidence to work toward a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Learning Objectives Learn the fundamental skills you require to be an expert Explore different techniques used by professionals Find out the relevant job skills & knowledge to excel in this profession Get a clear understanding of the job market and current demand Update your skills and fill any knowledge gap to compete in the relevant industry CPD accreditation for proof of acquired skills and knowledge Who is this Course for? Whether you are a beginner or an existing practitioner, our CPD accredited AWS Solutions Architect & SysOps Administrator is perfect for you to gain extensive knowledge about different aspects of the relevant industry to hone your skill further. It is also great for working professionals who have acquired practical experience but require theoretical knowledge with a credential to support their skill, as we offer CPD accredited certification to boost up your resume and promotion prospects. Entry Requirement Anyone interested in learning more about this subject should take this AWS Solutions Architect & SysOps Administrator. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. The course is open to students from any academic background, as there is no prerequisites to enrol on this course. The course materials are accessible from an internet enabled device at anytime of the day. CPD Certificate from Course Gate At the successful completion of the course, you can obtain your CPD certificate from us. You can order the PDF certificate for £9 and the hard copy for £15. Also, you can order both PDF and hardcopy certificates for £22. Career path The AWS Solutions Architect & SysOps Administrator will help you to enhance your knowledge and skill in this sector. After accomplishing this course, you will enrich and improve yourself and brighten up your career in the relevant job market. Course Curriculum AWS Tutorial | Course Introduction AWS Tutorial Introduction 00:02:00 What You Will Become 00:01:00 Cloud Computing Basics - Introducing IaaS, PaaS & SaaS Service Models Cloud Computing Introduction 00:07:00 Cloud service models 00:10:00 Cloud Deployment Models 00:05:00 Pre-Requisites - Key Skills Required Before Get Started with AWS Linux Basics 00:02:00 AWS Free Tier Account 00:01:00 Desire to adopt Cloud Model 00:01:00 AWS Global Infrastructure AWS Regions 00:03:00 Availability Zones 00:06:00 EC2 Basics- Virtual Servers in AWS Cloud What is Amazon EC2? 00:03:00 How to Create EC2 Instance - Linux 00:13:00 How to Create EC2 Instance - Windows 00:06:00 How to configure EC2 Instance? 00:15:00 Instance States 00:05:00 EC2 Instance Types 00:08:00 EC2 Pricing Models 00:17:00 Networking Basics - Basics of Network Topology and IP address classes Know Networking Terms - IP, Port, Protocol, Service, Daemon 00:15:00 Apache HTTP Server 00:19:00 VPC - Configure Custom Virtual Private Cloud in the AWS Cloud Build Your Own Datacenter 00:04:00 What is AWS VPC? 00:04:00 Create Custom VPC 00:07:00 Create Custom VPC - LAB 00:17:00 Private Subnet Vs Public Subnet 00:08:00 Private Subnet Vs Public Subnet - LAB 00:15:00 VPC Peering Connections 00:04:00 VPC Peering Connections - LAB 00:11:00 Network ACLs Vs Security Groups 00:09:00 Virtual Private Network (VPN) 00:03:00 EC2 Advanced - Virtual Servers in AWS Cloud EC2 Instance Meta Data 00:03:00 How to Manage Instance Settings 00:07:00 BootStrap EC2 instances 00:05:00 AMI - Create, Copy & Manage Permissions 00:10:00 EC2 Placement Groups 00:05:00 Public IP Vs. Elastic IP 00:03:00 EC2 Summary 00:05:00 Introduction to Elastic Block Store - EBS 00:06:00 Instance Store Volumes 00:06:00 EBS Snapshots 00:03:00 Cloud Watch Basics - Monitor AWS Resources & Applications Performance Cloud Watch Metrics 00:04:00 Cloud Watch Dashboards 00:03:00 Cloud Watch Alarms 00:05:00 Simple Notification Service SNS Introduction 00:03:00 Create Topic & Subscriptions to the Topic 00:03:00 Cloud Watch Alarms - LAB 00:11:00 Certificate Manager - Provision, Manage & Deploy SSL/TLS Certificates Data Encryption Introduction & Types 00:04:00 Create SSL/TLS Certificates - LAB 00:05:00 Route 53 - Scalable DNS and Domain Registration What is Route 53? | How DNS works? 00:06:00 How to Create Hosted Zone 00:07:00 DNS Record Types 00:07:00 Route53 Health Checks 00:03:00 Load Balancing - High Availability Solution for the Applications & Servers High Availability & Load Balancer - Architecture 00:16:00 Classic Load Balancer 00:08:00 Application Load Balancer 00:15:00 Network Load Balancer 00:06:00 Auto Scaling - Scale EC2 instances Proportion to Application Load What is Auto Scaling? 00:08:00 Auto Scaling Group - Architecture 00:08:00 Auto Scaling Group with ELB Association 00:08:00 Create launch Configuration 00:03:00 Create Auto Scaling group 00:16:00 S3 - Scalable Object Storage in the AWS Cloud What is S3? 00:08:00 Create First S3 Bucket 00:03:00 Create First S3 Object 00:04:00 S3 Storage Classes 00:06:00 S3 Versioning 00:10:00 S3 Life Cycle Management 00:08:00 IAM - Manage User Access and Encryption Keys What is IAM ? | IAM Architecture 00:12:00 IAM User, IAM Group - LAB 00:11:00 IAM Policy - LAB 00:07:00 IAM Role - LAB 00:04:00 S3 Cross-Region Replication - LAB 00:10:00 IAM MFA & Security Best Practices 00:07:00 AWS CLI - Manage AWS Services & Resources through AWS CLI How to Install AWS CLI on Windows Systems 00:05:00 How to Install AWS CLI on Linux 00:03:00 Explore AWS CLI Real-time Use Cases 00:07:00 Key Management Service - Generate & Manage AWS Encryption Keys KMS Architecture 00:05:00 Key Management Service (LAB) 00:05:00 EBS Volume Encryption 00:02:00 S3 Encryption 00:02:00 EFS - Managed Network File Storage for EC2 EFS Architecture 00:04:00 Create EFS 00:05:00 Mount on EC2 Instances 00:04:00 S3 Glacier - Data Archival Solution in the AWS Cloud What is S3 Glacier? 00:02:00 Create Vault 00:02:00 Retrieval Policies 00:03:00 Cloud Watch Advanced - Monitor AWS Resources & Applications Performance Cloud Watch Logs 00:13:00 Cloud Watch Custom Metrics 00:04:00 Cloud Watch Events 00:07:00 Cloud Front - Global Content Delivery Network Cloud Front Architecture 00:05:00 Create Cloud Front Distribution - LAB 00:05:00 Cloud Trail - Track IAM user activity & API Usage What is Cloud Trail 00:02:00 Create Trail - LAB 00:05:00 Lambda - Run Code without Thinking About Code | Serverless Architecture What is AWS Lambda? 00:06:00 Getting started with AWS Lambda - LAB 00:08:00 RDS RDS Introduction 00:05:00 Get started with RDS - LAB 00:07:00 DynamoDB Create DynamoDB Table 00:02:00 API Gateway - Build, Deploy & Manage APIs API Gateway Architecture 00:06:00 Create an API - LAB 00:06:00 API Gateway Realtime Use Case 00:03:00 Elastic Beanstalk What is Elastic Beanstalk? 00:06:00 Create a web app - LAB 00:06:00 Cloud Formation - Create & Manager resources with Cloud Formation Templates What is Cloud Formation? 00:06:00 Create Stack - LAB 00:11:00 Cloud Formation Designer - LAB 00:07:00 Systems Manager - Session Manager, Run Command, Parameter Store, Patch Manager What is a Systems Manager? 00:09:00 Session Manager 00:03:00 Run Command 00:06:00 Patch Manager 00:03:00 Secrets Manager - Rotate, Manage & Retrieve Secret through their life cycle What is Secrets Manager? 00:03:00 Store a new secret in Secrets Manager - LAB 00:03:00 Secrets Manager Use Cases 00:02:00 Inspector - Analyze Application Security & Report Inspector Architecture 00:05:00 Inspector Install Run Analyze - LAB 00:06:00 LightSail - Launch & Manage Virtual Private Servers LightSail Architecture 00:05:00 Get Started with LightSail! 00:04:00 AWS Limitations AWS Free Tier Limitations 00:04:00 AWS Service Limits 00:04:00 AWS Cost Explorer What is AWS Cost Explorer? How to Analyze Cost Report? 00:04:00 AWS Support AWS Support Plans 00:04:00 How to raise support tickets with AWS? 00:03:00 AWS Trusted Advisor What is AWS Trusted Advisor? 00:06:00 AWS Project - Realtime 3-Tier Architecture AWS Project - 3-Tier Architecture Deep Drive 00:11:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

Duration 4 Days 24 CPD hours Additional course details: Nexus Humans 9000 System Manager 2.9 (4-day) 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 9000 System Manager 2.9 (4-day) 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 5 Days 30 CPD hours Additional course details: Nexus Humans 9000 System Manager 2.8 (3-day) 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 9000 System Manager 2.8 (3-day) 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.

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00

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Duration 3 Days 18 CPD hours This foundational course to Citrix Workspace intelligence ushers you into the new generation of Citrix. You will discover how intelligent features help organize, guide, and automate the future of your work.You will gain an understanding of the fundamentals of web services, APIs, and systems integrations through building microapps designed to boost employee productivity and optimize the end user experience.Through this course, you will learn the fundamentals of Citrix Workspace intelligence features, web services, security considerations and API troubleshooting to help you successfully deploy intelligent workspace features in your environment. This foundational course to Citrix Workspace intelligence ushers you into the new generation of Citrix. You will discover how intelligent features help organize, guide, and automate the future of your work. You will gain an understanding of the fundamentals of web services, APIs, and systems integrations through building microapps designed to boost employee productivity and optimize the end user experience. Through this course, you will learn the fundamentals of Citrix Workspace intelligence features, web services, security considerations and API troubleshooting to help you successfully deploy intelligent workspace features in your environment.

Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for students who have experience using the Windows 10 operating system and need to start using the Windows 11 operating system. Overview In this course, you will use the new and updated features of Windows 11. You will: Navigate the Windows environment. Use apps available in Windows 11. Manage available apps. Configure Windows 11 settings. As an experienced Windows© 10 user, when you are ready to move to Windows 11, you might like some guidance in using the new and updated features. This course will help you identify and use those features efficiently and effectively. Navigating the Windows 11 Environment Topic A: Log in to Windows 11 Topic B: Use the Start Menu Topic C: Use the Taskbar Using Apps Topic A: Use Built-In Apps Topic B: Use the Updated File Explorer Managing Apps Topic A: Use Virtual Desktops Topic B: Obtain Apps from the Microsoft Store Configuring Windows 11 Settings Topic A: Use the Configuration Apps Topic B: Configure Accessibility Features

Duration 1 Days 6 CPD hours This course is intended for To ensure success, students will need to be familiar with using personal computers and should have experience using a keyboard and mouse. Students should also be comfortable working in the Windows 10 environment and be able to manage information on their computers. Overview Upon successful completion of this course, you will be able to understand how Office 365 might be used to increase productivity and collaboration within your organization. This course is intended for students who wish to be introduced to Office 365. This course aims to provide an overview of 365, its applications and tools. Getting Started with Office 365 An Introduction to Office 365 Navigate the Online User Interface Your Account, Personal Profile, Apps Use Help Personal Communications Outlook, Calendar and People Outlook Online Essentials Online Calendar Essentials People Online Essentials Information and File Sharing OneDrive for Business Overview SharePoint Online Overview Creating and Co-authoring using Online Apps Team Communications Skype for Business Yammer