1703 Cloud courses

Duration 5 Days 30 CPD hours This course is intended for This class is targeted towards the professional developer new to HTML, self-taught HTML developers, graphics designers and those new to HTML development. Overview After completing this course, you will be able to: Create HTML5 compliant web pages. Test and validate HTML and CSS code. Create CSS for style pages. Work with experimental vendor prefixes. Work with fonts and CSS font effects. Work with color and color tools. Layout pages and content using DIVs, iFrames and Tables. Add and format images and CSS sprites. Create HTML5 forms. Embed and manage video and audio content. This course is an in-depth hands-on study of HTML5, CSS3 and modern web and mobile development. The course includes detailed hands-on labs and Q&A labs. The labs include multiple projects, including one beginning to end web site.This material updates and replaces course Microsoft course 20480 which was previously published under the title Programming in HTML5 with JavaScript and CSS3. Module 1: A Brief History of HTML and the Web Welcome! History Details, Details, Details? The Life of a Web Page HTTP Status Codes Definitions Most Important Things to Know as a Web Developer Module 2: Core HTML Elements HTML and CSS Editors Text, Spaces and Tabs Working with Tags Attributes Comments Non-Standard Tags Every Page Includes? File Extensions Core Page Elements Nesting Testing HTML HTML and Text Module 3: Cascading Style Sheets Before CSS With CSS Cascading Style Sheets (CSS) Adding CSS to a Page Order of CSS Processing Experimental Vendor Prefixes CSS Units The CSS Box Mode Module 4: Fonts and Text Fonts CSS for Text CSS Text Ticks! Working with Lists Upgrading and to Windows 7 Module 5: Colors and Backgrounds Specifying Colors Applying Colors Gradients Module 6: Anchors and Hyperlinks HTML and CSS Hyperlinks with Images and Other Objects Buttons Module 7: Page Layout Page Layout Options Tables for Data DIVs Float SPAN HTML 5 DIV-like Tags IFRAMES Module 8: Images Favicon Preparing Images Image Files The IMG Tag Background Images Image Best Practices CSS Sprites Module 9: HTML Forms A Basic Form POST vs. GET name vs. id Basic Form Elements Basic Form Attribute Select Uploading Files HTML 5 Form Enhancements DataList Module 10: Multimedia Video and Audio HTML 5 Video CSS JavaScript Audio Hosting Videos in the Cloud Working with Animated GIFs

Linux administration and command line

Overview This comprehensive course on Internet of Things will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Internet of Things comes with accredited certification from CPD, 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 Internet of Things. It is available to all students, of all academic backgrounds. Requirements Our Internet of Things 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 15 sections • 65 lectures • 08:53:00 total length •Module 01: Introduction: 00:02:00 •Module 02: Course Agenda: 00:03:00 •Module 01: Introduction to Internet of Things: 00:13:00 •Module 02: Choosing Cloud Services for IoT: 00:05:00 •Module 03: What is Raspberry Pi Part 1?: 00:09:00 •Module 04: What is Raspberry Pi Part 2?: 00:06:00 •Module 01: Downloading OS for Raspberry Pi Noobs-Raspbian: 00:07:00 •Module 02: Install OS using NOOBS: 00:11:00 •Module 03: Remote Control of Raspberry Pi Using VNC Viewer: 00:10:00 •Module 04: Install OS using Raspbian Image part 1: 00:06:00 •Module 05: Install OS using Raspbian Image part 2: 00:02:00 •Module 01: Getting Around Raspbian Operating System part 1: 00:10:00 •Module 02: Getting around Raspbian Operating System part 2: 00:08:00 •Module 03: Getting around Raspbian Operating System part 3: 00:06:00 •Module 04: How To Run Python program On Raspberry Pi: 00:09:00 •Module 01: Raspberry PI GPIO Concepts: 00:07:00 •Module 02: Raspberry Pi GPIO Interfacing Single LED: 00:17:00 •Module 03: Raspberry Pi GPIO Interfacing Multiple LED's: 00:09:00 •Module 04: Rapberry Pi GPIO Interfacing Buzzer: 00:03:00 •Module 01: Raspberry Pi and Transistorized Switching: 00:09:00 •Module 02: Raspberry Pi and Relay part 1: 00:13:00 •Module 03: Raspberry Pi and Relay part 2: 00:08:00 •Module 01: Accepting Digital Input on Raspberry Pi Part 1: 00:13:00 •Module 02: Accepting Digital Inputs on Raspberry Pi Part 2: 00:07:00 •Module 01: Sensor Interfacing With Raspberry Pi LDR1: 00:05:00 •Module 02: Sensor Interfacing With Raspberry Pi LDR 2: 00:10:00 •Module 03: Sensor Interfacing With Raspberry Pi LDR 3: 00:07:00 •Module 04: Sensor Interfacing with Rapberry Pi DHTT11 part 1: 00:10:00 •Module 05: Sensor Interfacing with Rapberry Pi DHTT11 part 2: 00:10:00 •Module 06: Sensor Interfacing with Raspberry pi Using SenseHAT: 00:11:00 •Module 07: Ultrasonic Sensor Interfacing with Raspberry Pi: 00:14:00 •Module 01: BMP180 with Raspberry Pi: 00:07:00 •Module 02: Enabling I2C on Raspberry Pi: 00:05:00 •Module 03: BMP180 Python Code: 00:06:00 •Module 01: Getting Started With IoT: 00:11:00 •Module 02: Getting Started with Microsoft Azure IoT Hub Part 1: 00:04:00 •Module 03: Getting Started with Microsoft Azure IoT Hub Part 2: 00:05:00 •Module 04: Getting Started with Microsoft Azure IoT Hub Part 3: 00:09:00 •Module 05: Create Device inside Azure IoT Hub: 00:06:00 •Module 06: Enable Azure Cloud Shell and enable IoT Extension: 00:08:00 •Module 07: Send Data to Azure IoT Hub Using Python Program: 00:09:00 •Module 08: Send Actual Temperature and Humidity Values to Azure IoT hub: 00:03:00 •Module 09: Storing the Data on Microsoft Azure Using Custom Gateway: 00:13:00 •Module 10: Save data to blob storage using Stream Analytics Job: 00:12:00 •Module 11: Data Visualization with Power BI Part 1: 00:07:00 •Module 12: Data Visualization with Power BI Part 2: 00:12:00 •Module 13: Creating Custom web app with azure for data visualization Part 1: 00:10:00 •Module 14: Creating Custom web app with azure for data visualization Part 2: 00:14:00 •Module 15: Creating Custom web app with azure for data visualization Part 3: 00:12:00 •Module 16: Dealing with password error while pushing your webapp to azure: 00:01:00 •Module 17: Cleaning up Azure Resources: 00:02:00 •Module 18: Remote Monitoring using Azure Logic App Part 1: 00:12:00 •Module 19: Remote Monitoring using Azure Logic App Part 2: 00:10:00 •Module 01: Introduction to Thingspeak: 00:06:00 •Module 02: Create an account and send data to Thingspeak: 00:08:00 •Module 01: Getting started with SaaS IoT Platform io.adafruit.com: 00:08:00 •Module 02: What is MQTT?: 00:10:00 •Module 03: Sending Data to Adafruit Io Using MQTT Part 1: 00:17:00 •Module 04: Sending Data to Adafruit io Using MQTT part 2: 00:14:00 •Module 05: Home automation project with adafruit IO Part 1: 00:15:00 •Module 06: Home Automation Project with Adafruit IO Part 2: 00:02:00 •Module 01: IoT Security: 00:14:00 •Module 02: Conclusion: 00:01:00 •Resources - Internet of Things: 00:00:00 •Assignment - Internet of Things: 00:00:00

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS 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 data warehouse 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 build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake 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 Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Duration 3 Days 18 CPD hours This course is intended for This course is designed for system administrators and implementors interested in learning IBM Security Verify Access. Overview Describe IBM Security Verify Access product and its key features Discuss the architecture and deployment process Configure IBM Security Verify Access users, groups, and domains Introduce concepts of a reverse proxy and how it fits in your web-based infrastructure Describe protected object space and the policy access control model Explain how to set up reverse proxy junctions to handle web requests Discuss and configure authentication mechanisms that are supported by Verify Access Explain and set up logging, auditing, and tracing for Verify Access components IBM Security Verify Access helps you simplify your users' access while more securely adopting web, mobile, IoT, and cloud technologies. It can be deployed on premises, in a virtual or hardware appliance, or containerized with Docker. Verify Access also directly connects with Verify SaaS for a modernized, hybrid IAM approach to enable your organization's migration to identity as a service (IDaaS) at a comfortable pace. Using the skills taught in this course, you learn how to run Verify Access via Docker, configure authentication and authorization mechanisms, implement policy access control, and set up reverse proxy junctions to process web requests. Hands-on exercises reinforce the skills learned. Unit 1 Introduction to IBM Security Verify Access Unit 2 Architecture and deployment Unit 3 Managing users, groups, and domains Unit 4 Reverse Proxy (WebSEAL) concepts Unit 5 Managing access control Unit 6 Configuring junctions for back-end resources Unit 7 Authentication framework and methods Unit 8 Logging, auditing, and tracing Additional course details: Nexus Humans TW108G IBM Security Verify Access Foundations 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 TW108G IBM Security Verify Access Foundations 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 4 Days 24 CPD hours This course is intended for Security-operations (SecOps), or security, orchestration, automation, and response (SOAR) engineers, managed security service providers (MSSPs), service delivery partners, system integrators, and professional services engineers Overview This training is designed to enable a SOC, CERT, CSIRT, or SOAR engineer to start working with Cortex XSOAR integrations, playbooks, incident-page layouts, and other system features to facilitate resource orchestration, process automation, case management, and analyst workflow. The course includes coverage of a complete playbook-development process for automating a typical analyst workflow to address phishing incidents. This end-to-end view of the development process provides a framework for more focused discussions of individual topics that are covered in the course. The Cortex? XSOAR 6.8: Automation and Orchestration (EDU-380) course is four days of instructor-led training that will help you: Configure integrations, create tasks, and develop playbooks Build incident layouts that enable analysts to triage and investigate incidents efficiently Identify how to categorize event information and map that information to display fields Develop automations, manage content, indicator data, and artifact stores, schedule jobs, organize users and user roles, oversee case management, and foster collaboration This class is powered by Cloud Harmonics. Course Outline Module 1 - Core Functionality and Feature Sets Module 2 - Enabling and Configuring Integrations Module 3 - Playbook Development Module 4 - Classification and Mapping Module 5 - Layout Builder Module 6 - Solution Architecture Module 7 - Docker Module 8 - Automation Development and Debugging Module 9 - The Marketplace and Content Management Module 10 - Indicators and Threat Intelligence Management Module 11 - Jobs and Job Scheduling Module 12 - Users and Role-Based Access Controls (RBAC) Module 13 - Integration Development Additional course details: Nexus Humans Palo Alto Networks: Cortex XSOAR 6.8: Automation and Orchestration(EDU-380) 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 Palo Alto Networks: Cortex XSOAR 6.8: Automation and Orchestration(EDU-380) 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 2 Days 12 CPD hours This course is intended for The course is targeted at professionals who have never worked with Microsoft 365 before, or who have yet to move beyond its basic functions. The target audience typically includes individuals, professionals, and organizations who are looking to improve their productivity, collaboration, and communication using the suite of applications and services provided by Microsoft 365. This could include office workers, project managers, IT professionals, and small to large-scale businesses who want to maximize the benefits of cloud-based solutions for their daily operations.  Overview Upon successfully completing this course, students will have confidence in using the Microsoft 365 applications. Students will increase their work productivity and decrease time on completing tasks. In this course, students will learn how to use different tools of Microsoft 365 for better online collaboration, including OneDrive, SharePoint, Teams, Excel, Outlook, Word, and PowerPoint. First Steps in Office 365 The Difference Between Office 365 and Microsoft 365 Pros and cons of Microsoft 365 First Steps on mobile devices OneDrive Introduction - What is Microsoft OneDrive? How To Access Microsoft OneDrive? Upload Files Share Files Sync Files Recycle Bin Using OneDrive How To Access Onedrive On Phone? Teams - Simplify Collaboration within Companies Discover new ways to collaborate and communicate An introduction to your central place in Office 365 How to launch and install Teams The Interface of Microsoft Teams Use the Teams window to structure your organization Use Channels to structure the Teams window Use Tabs to access tools and information Communicate with others via Chat Keep track of activities Meetings, video conferencing and screen sharing Share files effectively Manage teams and permissions for organizational structuring Use Teams effectively on mobile devices Final remarks SharePoint Sites Introduction First Steps Document Library - First Steps Document Library - Set and Manage Alerts Document Library - Understanding Versioning Sync Libraries Share a Site Picture Library Lists Calendar Tasks Discussion Board Outlook First Steps in Mail Improved Search Function Work with Folders Settings Working with the Mail App Calendar People Tasks Excel Online Introduction Open and Edit an Excel Online Workbook Limitations of Excel Online Create a New Workbook with Excel Online Edit a Workbook Simultaneously with another Person Working with the Excel AppUse Excel effectively on mobile devices PowerPoint Online Introduction Open a PowerPoint Online Presentation Edit a Presentation Online Limitations of PowerPoint Online Create a Presentation with PowerPoint Online Working with the PowerPoint App Use Power Point effectively on mobile devices Word Online Introduction Open and Edit a Word Document Online Limitations of Word Online Create a New Document Edit a Document Simultaneously Working with the Word App

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Get ready to tackle one of the most exciting and prominent features of the Go language with the help of this comprehensive course. If you are looking forward to getting started with advanced topics such as concurrency and levelling up your Go(lang) skills, then you are in the right place.