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Duration 3 Days 18 CPD hours This course is intended for Storage and virtual infrastructure administrators who are responsible for production support and administration of VMware vSAN 7. Overview By the end of the course, you should be able to meet the following objectives: Define the tasks involved in vSAN node management Updating and upgrading vSAN using VMware vSphere Lifecycle Manager™ Explain vSAN resilience and data availability features Reconfigure vSAN storage policies and observe the cluster-wide impact Perform vSAN cluster scale-out and scale-up operations Describe common vSAN cluster maintenance operations Control vSAN resync operations Configure vSAN storage efficiency and reclamation features Use VMware Skyline™ Health to monitor cluster health, performance, and storage capacity Describe vSAN security operations Configure vSAN Direct for cloud native applications Configure remote vSAN datastore and vSAN native file services Manage two-node cluster and stretched cluster advance operations In this three-day course, you learn about managing and operating VMware vSAN? 7. This course focuses on building the required skills for common Day-2 vSAN administrator tasks such as, vSAN node management, cluster maintenance, security operations and advanced vSAN cluster operations. You also gain practical experience through the completion of instructor-led activities and hands-on lab exercises. Course Introduction Introductions and course logistics Course objectives vSAN Node Management Recognize the importance of hardware compatibility Ensure the compatibility of driver and firmware versioning Use tools to automate driver validation and installation Apply host hardware settings for optimum performance Use vSphere Lifecycle Manager to perform upgrades vSAN Resilience and Data Availability Operations Describe vSAN storage policies Recognize the impact of a vSAN storage policy change Describe and configure the Object Repair Timer advanced option Plan disk replacement in a vSAN cluster Plan maintenance tasks to avoid vSAN object failures Recognize the importance of managing snapshot utilization in a vSAN cluster Configure the vSAN fault domains vSAN Cluster Maintenance Perform typical vSAN maintenance operations Describe vSAN maintenance modes and data evacuation options Assess the impact on cluster objects of entering maintenance mode Determine the specific data actions required after exiting maintenance mode Define the steps to shut down and reboot hosts and vSAN clusters Use best practices for boot devices Replace vSAN nodes vSAN Storage Space Efficiency Discuss deduplication and compression techniques Understand deduplication and compression overhead Discuss compression only mode Configure erasure coding Configure swap object thin provisioning Discuss reclaiming storage space with SCSI UNMAP Configure TRIM/UNMAP vSAN Cluster Performance Monitoring Describe how the Customer Experience Improvement Program (CEIP) enables VMware to improve products and services Use vSphere Skyline Health for monitoring vSAN cluster health Manage alerts, alarms, and notifications related to vSAN in VMware vSphere© Client? Create and configure custom alarms to trigger vSAN health issues Use IO Insight metrics for monitoring vSAN performance Analyse vsantop performance metrics Use a vSAN proactive test to detect and diagnose cluster issues vSAN Security Operations Identify differences between VM encryption and vSAN encryption Perform ongoing operations to maintain data security Describe the workflow of data-in transit encryption Identify the steps involved in replacing Key Management Server (KMS) vSAN Direct Discuss the use cases for vSAN Direct Understand the overall architecture of vSAN Direct Describe the workflow of vSAN Direct datastore creation Explore how vSAN Direct works with storage policy tagging Remote vSAN Discuss the use cases for remote vSAN Understand the high-level architecture Describe remote datastore operations Discuss the network requirement Interoperability between remote vSAN and VMware vSphere© High Availability vSAN Native File Service Discuss the use cases for vSAN file service Understand the high-level architecture of vSAN file service Discuss the authentication model Configure file shares Monitor file share health and capacity utilization Manage Advanced vSAN Cluster Operations Describe the architecture for stretched clusters and two-node clusters Understand the importance of witness node Describe how stretched cluster storage policies affect vSAN objects Create and apply a vSAN stretched cluster policy to meet specific needs Discuss stretched cluster failure scenarios and responses Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSAN: Management and Operations [V7] 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 VMware vSAN: Management and Operations [V7] 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 This comprehensive course on Understand Piping & Instrumentation Diagrams P&IDs will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Understand Piping & Instrumentation Diagrams P&IDs 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? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Understand Piping & Instrumentation Diagrams P&IDs. It is available to all students, of all academic backgrounds. Requirements Our Understand Piping & Instrumentation Diagrams P&IDs 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 14 sections • 119 lectures • 08:26:00 total length •Introduction: 00:04:00 •What's a P&ID ?: 00:03:00 •Why is a P&ID so important ?: 00:02:00 •Who uses P&ID's ?: 00:06:00 •How do P&ID's look like ?: 00:08:00 •Introduction- PID READING: 00:02:00 •Anatomy of a P&ID: 00:01:00 •The title block: 00:03:00 •The drawing scale: 00:03:00 •The grid system: 00:02:00 •The revision block: 00:03:00 •Changes: 00:02:00 •Notes and legends: 00:03:00 •Valve symbols: 00:14:00 •Valve actuator symbols: 00:09:00 •Control valve designations: 00:02:00 •Standards and conventions for valve status: 00:07:00 •Process equipment symbols: 00:12:00 •Piping symbols: 00:03:00 •Pipe fitting symbols: 00:03:00 •Isolating, venting & draining symbols for ease of maintenance: 00:05:00 •Instrumentation: 00:03:00 •Sensing devices and detectors: 00:04:00 •Location symbols: 00:04:00 •Modifiers and transmitters: 00:05:00 •Indicators and recorders: 00:03:00 •Controllers: 00:03:00 •Example #1 : Identifying process equipment and flow paths: 00:05:00 •Example #2 : Identifying valve position and failure mode: 00:03:00 •Example #3 : Identifying the symbols: 00:02:00 •Piping designation code: 00:06:00 •Equipment designation code: 00:03:00 •Instrument designation code: 00:02:00 •Miscellaneous designation codes: 00:02:00 •The process: 00:01:00 •Process control: 00:06:00 •The control loop: 00:02:00 •Process control terms: 00:10:00 •Control loops : Feedback control: 00:02:00 •Pressure control loops: 00:01:00 •Flow control loops: 00:01:00 •Level control loops: 00:01:00 •Temperature control loops: 00:01:00 •Multi-variable loops: 00:02:00 •Feedforward control: 00:02:00 •Feedforward + Feedback: 00:01:00 •Cascade control: 00:08:00 •Split range control: 00:03:00 •Operations on control signals: 00:02:00 •Ratio control: 00:02:00 •Batch control: 00:01:00 •Selective control: 00:01:00 •Do we need to control at all ?: 00:01:00 •Principles of equipment-wise control: 00:10:00 •Pipe control system: 00:02:00 •Control of a single pipe: 00:02:00 •Control of pressure in a pipe: 00:03:00 •Control of flow in a pipe: 00:04:00 •Flow merging: 00:08:00 •Flow splitting: 00:05:00 •Centrifugal pump control: 00:04:00 •Control valve vs Variable Frequency Drive (VFD) for centrifugal pumps: 00:03:00 •Minimum flow control for centrifugal pumps: 00:09:00 •Positive displacement pump control: 00:02:00 •Control by a recirculation pipe for PD pumps: 00:03:00 •Variable Speed Drive (VSD) control for PD pumps: 00:01:00 •Control by stroke adjustment for PD pumps: 00:01:00 •Compressor control system: 00:02:00 •Compressor capacity control: 00:12:00 •Compressor anti-surge control: 00:03:00 •Heat transfer equipment control: 00:02:00 •Heat exchanger direct control system: 00:04:00 •Heat exchanger bypass control system: 00:04:00 •Reactor temperature control: 00:06:00 •Air cooler control: 00:02:00 •Heat exchanger for heat recovery: 00:01:00 •Heat exchanger back pressure control: 00:02:00 •Basic fired heater control: 00:08:00 •Complex fired heater control: 00:05:00 •Container and vessel control: 00:07:00 •Container blanket gas control: 00:02:00 •Safety strategies: 00:01:00 •Concept of Safety Instrumented Systems (SIS): 00:01:00 •SIS actions and types: 00:14:00 •SIS extent: 00:02:00 •SIS requirement: 00:03:00 •Anatomy of a SIS: 00:02:00 •SIS element symbols: 00:01:00 •SIS primary elements : Sensors: 00:03:00 •SIS final elements: 00:04:00 •Switching valve actuator arrangements: 00:02:00 •Valve position validation: 00:02:00 •Merging a switching valve and a control valve: 00:03:00 •SIS logics: 00:01:00 •Showing safety instrumented functions on P&ID's: 00:07:00 •Discrete control: 00:05:00 •Alarm system: 00:02:00 •Anatomy of alarm systems: 00:02:00 •Alarm requirements: 00:06:00 •Alarm system symbology in P&ID's: 00:06:00 •Concept of common alarms: 00:01:00 •Fire and Gas Detection Systems (FGS): 00:03:00 •Electric motor control: 00:07:00 •P&ID representation of commands and responses: 00:05:00 •P&ID representation of inspection and repair: 00:05:00 •P&ID example of electro-motor control: 00:04:00 •P&ID example #1 : Legend and specifications: 00:05:00 •P&ID example #2 : Hydrogen delivery station: 00:16:00 •P&ID example #3 : Acid system: 00:13:00 •P&ID example #4 : Centrifugal pump: 00:09:00 •P&ID example #5 : Utility station: 00:04:00 •P&ID example #6 : Waste water filter: 00:08:00 •P&ID example #7 : Steam separator: 00:15:00 •P&ID example #8 : Flare knock-out drum: 00:14:00 •P&ID example #9 : Centrifugal compressor: 00:05:00 •P&ID example #10 : Hydrogen production from shale gas: 00:11:00 •P&ID example #11 : Fired heater: 00:07:00 •Resources - Understand Piping & Instrumentation Diagrams P&IDs: 00:00:00 •Assignment - Understand Piping & Instrumentation Diagrams P&IDs: 00:00:00

Overview This comprehensive course on Ultimate PHP & MySQL Web Development Course & OOP Coding will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Ultimate PHP & MySQL Web Development Course & OOP Coding 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 Ultimate PHP & MySQL Web Development Course & OOP Coding. It is available to all students, of all academic backgrounds. Requirements Our Ultimate PHP & MySQL Web Development Course & OOP Coding 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 • 133 lectures • 10:06:00 total length •Introduction: 00:02:00 •Setup On Windows: 00:15:00 •Setup On Mac: 00:11:00 •Setup On Linux: 00:12:00 •Online Code Editor: 00:03:00 •Basic File Syntax: 00:05:00 •Printing (echo): 00:06:00 •Comments: 00:05:00 •Variables: 00:06:00 •Variable Data Types: 00:07:00 •Variable Naming: 00:03:00 •Constants: 00:02:00 •Arrays: 00:05:00 •Associative Arrays: 00:06:00 •Multidimensional Arrays: 00:04:00 •if Statement: 00:06:00 •ifelse Statement: 00:02:00 •ifelseifelse Statement: 00:05:00 •Switch Statement: 00:06:00 •while Loop: 00:06:00 •doWhile Loop: 00:03:00 •for Loop: 00:03:00 •foreach Loop: 00:05:00 •Break Statement: 00:02:00 •Continue Statement: 00:02:00 •Basic Function: 00:03:00 •Passing Function Arguments: 00:03:00 •Passing Function Arguments By Reference: 00:04:00 •Default Argument Value: 00:02:00 •Function Returning Values: 00:05:00 •Dynamic Function Calls: 00:03:00 •Variable Scope: 00:04:00 •Simple HTML Form: 00:07:00 •GET vs POST: 00:05:00 •$_SERVER ['PHP_SELF']: 00:07:00 •Validating Form Data With PHP: 00:07:00 •Required Fields: 00:05:00 •Display Error Messages: 00:05:00 •Validate Name: 00:03:00 •Validate Email: 00:03:00 •Validate URL: 00:07:00 •Keep The Values In The Form: 00:04:00 •Read File (readfile()): 00:02:00 •Open, Read & Close A File (fopen(), fread(), fclose()): 00:04:00 •Read Single Line (fgets()): 00:03:00 •Check End-Of-File (feof()): 00:02:00 •Read Single Character (fgetc()): 00:02:00 •Write To File (fwrite()): 00:03:00 •Configure php.ini File For File Uploading: 00:02:00 •Front End HTML Upload Form: 00:04:00 •PHP Upload Script: 00:15:00 •Check If File Exists: 00:03:00 •Limit File Size: 00:05:00 •Limit File Type: 00:04:00 •MySQL vs MySQLi vs PDO: 00:05:00 •Creating A Database & Table (phpMyAdmin): 00:06:00 •Connecting To A Database: 00:06:00 •Get Data Using SELECT Query: 00:10:00 •WHERE Property For Filtering: 00:03:00 •LIKE Property For Pattern Search: 00:02:00 •Sorting Results Using ORDER BY Property: 00:01:00 •Using JOINS: 00:08:00 •Insert Data Using INSERT Query: 00:04:00 •Get ID Of The Last Inserted Row: 00:02:00 •Insert Multiple Rows: 00:05:00 •Update Data Using UPDATE Query: 00:03:00 •Delete Data Using DELETE Query: 00:02:00 •Delete All Rows In A Table Using TRUNCATE Query: 00:02:00 •Delete Table Using DROP Query: 00:02:00 •Limit Data Selections Using LIMIT, ROWNUM: 00:04:00 •Create Table Using CREATE Query: 00:03:00 •Clone/Duplicate Table: 00:03:00 •Alter Table: 00:05:00 •Create Database: 00:02:00 •Drop Database: 00:02:00 •SQL Injection & Prepared Statements: 00:09:00 •What Is XML?: 00:02:00 •What Is SimpleXML?: 00:02:00 •Parse XML String: 00:08:00 •Parse XML File: 00:02:00 •Get Node Values: 00:02:00 •Get Node Values of Specific Elements: 00:03:00 •Get Node Values - Loop: 00:03:00 •Get Attribute Values: 00:02:00 •What Is The XML Expat Parser?: 00:02:00 •Initializing The XML Expat Parser: 00:10:00 •Load and Output XML Using DOM Parser: 00:02:00 •Looping Through XML Using DOM Parser: 00:03:00 •What Is AJAX?: 00:02:00 •Load Simple Data Using AJAX Front End: 00:08:00 •Load Simple Data Using AJAX Back End: 00:05:00 •Load Data From A Database Using AJAX: 00:08:00 •Send A Plain Text Email: 00:04:00 •Send A HTML Email: 00:06:00 •Email Attachments: 00:17:00 •PHPMailer Setup: 00:03:00 •Send Email Using PHPMailer: 00:04:00 •Send HTML Email Using PHPMailer: 00:04:00 •Email Attachments Using PHPMailer: 00:02:00 •What Is Object Oriented Programming (OOP)?: 00:03:00 •Basic Class With Variables: 00:04:00 •Functions: 00:05:00 •Constructor: 00:04:00 •Destructor: 00:02:00 •Inheritance: 00:06:00 •Multi Class Inheritance: 00:03:00 •Function Overriding: 00:03:00 •Public vs Private vs Protected: 00:05:00 •Interfaces: 00:04:00 •Constants: 00:03:00 •Abstract Class: 00:06:00 •Static Keyword: 00:03:00 •Final Keyword: 00:02:00 •Initiating Parent Constructor: 00:02:00 •die() Function: 00:02:00 •Custom Error Handler: 00:04:00 •Triggering An Exception: 00:03:00 •Exception Handling: 00:05:00 •Create Database & Table: 00:04:00 •User Class & Database Connection: 00:15:00 •Register User Form: 00:09:00 •Inserting User Data Into Database: 00:10:00 •Registration Form Field Validation: 00:12:00 •Securing User Password: 00:03:00 •Check If Username or Email Already Exists: 00:11:00 •Retain Data After Failed Registration: 00:03:00 •Validate an Integer Within a Range: 00:04:00 •Validate IPv6 Address: 00:03:00 •Validate URL - Must Contain QueryString: 00:03:00 •Remove Characters With ASCII Value > 127: 00:04:00 •Including & Requiring External PHP Files: 00:05:00 •Resource: 00:00:00 •Assignment - Ultimate PHP & MySQL Web Development Course & OOP Coding: 00:00:00

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the 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. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics 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 Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

Learn modern frameworks and technologies, including JavaScript ES6, Bootstrap 5, Tailwind CSS, React, MongoDB, Express, and Nodejs. It's a step-by-step guide to building powerful web applications using cutting-edge technologies for your start-up or business. Learn powerful skills that will make you invaluable in the job market with no coding knowledge.

Cyber security is the activity of securing systems, networks, and programmes from digital threats. These cyber-attacks are typically designed to gain access to, change, or delete sensitive information, extort money from users, or disrupt normal corporate activities. In the UK, 46% of businesses reported facing cyber breaches or attacks in the last 12 months, underscoring the crucial importance of Cyber Security. As the digital realm expands, so does the frontier of threats, offering a golden opportunity for those skilled in Cyber Security. The "Cyber Security Training Course" is tailored to cater to this pressing need, providing a deep understanding of incident handling and response. Learners will embark on a journey, starting with proactive preparations, identifying threats, mastering containment strategies, and ensuring systematic eradication and recovery. The course culminates with valuable insights to fortify one's Cyber Security acumen. In a world where cyber threats are an ever-looming reality, mastering the art of Cyber Security in the UK's evolving digital space is not just an option - it's a necessity. Join us and stand at the vanguard of digital defence. Learning Outcome: Upon completing the "Cyber Security Training Course", participants will: Understand core principles of Cyber Security and incident handling. Master preparatory measures to anticipate cyber threats. Effectively identify and contain cyber incidents. Apply eradication strategies to eliminate threats. Ensure system recovery post-incident. Reinforce future Cyber Security defences against potential threats. What will make you stand out? On completion of this online course, you will gain: CPD QS Accredited After successfully completing the Course, you will receive a FREE PDF Certificate as evidence of your newly acquired abilities. Lifetime access to the whole collection of learning materials. The online test with immediate results You can study and complete the course at your own pace. Study for the course using any internet-connected device, such as a computer, tablet, or mobile device. The Cyber Security Training Course offers a profound insight into the essential strategies and processes required to handle and respond to cybersecurity incidents adeptly. In an era where cyber threats have become increasingly sophisticated and rampant, ensuring the safety and integrity of digital assets is paramount. This Cyber Security course has been meticulously designed to cater to beginners and seasoned cybersecurity professionals, enriching their knowledge and honing their skills to tackle real-world cyber threats effectively and efficiently. The curriculum dives deep into the nuanced stages of managing cyber incidents, from the early identification of threats to their containment and eventual eradication. This holistic approach ensures a full recovery of systems and fortifies them against future attacks. As you progress, you'll master the technicalities and the strategic mindset required in today's cyber-centric world. Elevate your cyber expertise and become a digital sentinel with this immersive cyber security course. Don't leave your digital realm exposed to potential threats. Equip yourself with the expertise needed to fortify against cyber breaches. Dive into the Cyber Security Training Course and elevate your professional stature in cyber security. Enrol today and be the shield every organisation seeks! Secure your future by mastering Cyber Security now. Join us. Show off your new skills with a certificate of completion Once you complete the Cyber Security course, you will be eligible to request a digital certificate for free. For Printed Transcript & Hardcopy Certificate- 4.99 GBP (Inside the UK Postal Fee) 8.99 GBP (International Delivery Fee) CPD 10 CPD hours / points Accredited by CPD Quality Standards Cyber Security Incident Handling and Incident Response 05:21 1: Course Promo 05:21 Section 01: An Introduction to Incident Handling 06:52 2: Lecture 01: Incident Handling 06:52 Section 02: Preparation for an Incident 13:50 3: Lecture 01: Preparation of People and Policy 07:28 4: Lecture 02: Team Building and Management 06:22 Section 03: Identification 13:25 5: Lecture 01: Where Does Identification Occur? 06:24 6: Lecture 02: What to Check? 07:01 Section 04: Containment 10:03 7: Lecture 01: Deployment and Categorisation 04:42 8: Lecture 02: Short-term and Long-term Actions 05:21 Section 05: Eradication 04:45 9: Lecture 01: Restoring and Improving Defenses 04:45 Section 06: Recovery Phase 05:38 10: Lecture 01: Validation and Monitoring 05:38 Section 07: Final Thoughts 05:25 11: Lecture 01: Meet, Fix, and Share 05:25 Who is this course for? The "Cyber Security Training Course" is ideal for: Aspiring Cyber Security enthusiasts. IT professionals are diversifying into Cyber Security. Business leaders are navigating digital threats. Online business owners prioritise security. Tech aficionados keen on Cyber Security trends. Current practitioners are refining Cyber Security skills. After completing this course, anyone can later enrol in these courses: Cyber Resilience RESILIA Practitioner Cyber Resilience RESILIA Foundation NCFE Level 2 Certificate in the Principles of Cyber Security Requirements Without any formal requirements, you can delightfully enrol in this course. Career path The aim of this exclusive Cyber Security course is to help you toward your dream career. So, complete this course and enhance your skills to explore opportunities in relevant areas. Cyber Security Consultant Penetration Tester IT Business Analyst IT Security Engineer Chief Information Security Officer (CISO) Computer Forensics Investigator Incident Responder

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Overview This comprehensive course on Python for Data Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Python for Data Analysis 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 Python for Data Analysis. It is available to all students, of all academic backgrounds. Requirements Our Python for Data Analysis 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 19 sections • 99 lectures • 00:08:00 total length •Welcome & Course Overview: 00:07:00 •Set-up the Environment for the Course (lecture 1): 00:09:00 •Set-up the Environment for the Course (lecture 2): 00:25:00 •Two other options to setup environment: 00:04:00 •Python data types Part 1: 00:21:00 •Python Data Types Part 2: 00:15:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1): 00:16:00 •Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2): 00:20:00 •Python Essentials Exercises Overview: 00:02:00 •Python Essentials Exercises Solutions: 00:22:00 •What is Numpy? A brief introduction and installation instructions.: 00:03:00 •NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes.: 00:28:00 •NumPy Essentials - Indexing, slicing, broadcasting & boolean masking: 00:26:00 •NumPy Essentials - Arithmetic Operations & Universal Functions: 00:07:00 •NumPy Essentials Exercises Overview: 00:02:00 •NumPy Essentials Exercises Solutions: 00:25:00 •What is pandas? A brief introduction and installation instructions.: 00:02:00 •Pandas Introduction: 00:02:00 •Pandas Essentials - Pandas Data Structures - Series: 00:20:00 •Pandas Essentials - Pandas Data Structures - DataFrame: 00:30:00 •Pandas Essentials - Handling Missing Data: 00:12:00 •Pandas Essentials - Data Wrangling - Combining, merging, joining: 00:20:00 •Pandas Essentials - Groupby: 00:10:00 •Pandas Essentials - Useful Methods and Operations: 00:26:00 •Pandas Essentials - Project 1 (Overview) Customer Purchases Data: 00:08:00 •Pandas Essentials - Project 1 (Solutions) Customer Purchases Data: 00:31:00 •Pandas Essentials - Project 2 (Overview) Chicago Payroll Data: 00:04:00 •Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data: 00:18:00 •Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach: 00:13:00 •Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach: 00:22:00 •Matplotlib Essentials - Exercises Overview: 00:06:00 •Matplotlib Essentials - Exercises Solutions: 00:21:00 •Seaborn - Introduction & Installation: 00:04:00 •Seaborn - Distribution Plots: 00:25:00 •Seaborn - Categorical Plots (Part 1): 00:21:00 •Seaborn - Categorical Plots (Part 2): 00:16:00 •Seborn-Axis Grids: 00:25:00 •Seaborn - Matrix Plots: 00:13:00 •Seaborn - Regression Plots: 00:11:00 •Seaborn - Controlling Figure Aesthetics: 00:10:00 •Seaborn - Exercises Overview: 00:04:00 •Seaborn - Exercise Solutions: 00:19:00 •Pandas Built-in Data Visualization: 00:34:00 •Pandas Data Visualization Exercises Overview: 00:03:00 •Panda Data Visualization Exercises Solutions: 00:13:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1): 00:19:00 •Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2): 00:14:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview): 00:11:00 •Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions): 00:37:00 •Project 1 - Oil vs Banks Stock Price during recession (Overview): 00:15:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2): 00:18:00 •Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3): 00:17:00 •Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview): 00:03:00 •Introduction to ML - What, Why and Types..: 00:15:00 •Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff: 00:15:00 •scikit-learn - Linear Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Linear Regression Model Hands-on (Part 2): 00:19:00 •Good to know! How to save and load your trained Machine Learning Model!: 00:01:00 •scikit-learn - Linear Regression Model (Insurance Data Project Overview): 00:08:00 •scikit-learn - Linear Regression Model (Insurance Data Project Solutions): 00:30:00 •Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc.: 00:10:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 1): 00:17:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 2): 00:20:00 •scikit-learn - Logistic Regression Model - Hands-on (Part 3): 00:11:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Overview): 00:05:00 •scikit-learn - Logistic Regression Model - Hands-on (Project Solutions): 00:15:00 •Theory: K Nearest Neighbors, Curse of dimensionality .: 00:08:00 •scikit-learn - K Nearest Neighbors - Hands-on: 00:25:00 •scikt-learn - K Nearest Neighbors (Project Overview): 00:04:00 •scikit-learn - K Nearest Neighbors (Project Solutions): 00:14:00 •Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging.: 00:18:00 •scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1): 00:19:00 •scikit-learn - Decision Tree and Random Forests (Project Overview): 00:05:00 •scikit-learn - Decision Tree and Random Forests (Project Solutions): 00:15:00 •Support Vector Machines (SVMs) - (Theory Lecture): 00:07:00 •scikit-learn - Support Vector Machines - Hands-on (SVMs): 00:30:00 •scikit-learn - Support Vector Machines (Project 1 Overview): 00:07:00 •scikit-learn - Support Vector Machines (Project 1 Solutions): 00:20:00 •scikit-learn - Support Vector Machines (Optional Project 2 - Overview): 00:02:00 •Theory: K Means Clustering, Elbow method ..: 00:11:00 •scikit-learn - K Means Clustering - Hands-on: 00:23:00 •scikit-learn - K Means Clustering (Project Overview): 00:07:00 •scikit-learn - K Means Clustering (Project Solutions): 00:22:00 •Theory: Principal Component Analysis (PCA): 00:09:00 •scikit-learn - Principal Component Analysis (PCA) - Hands-on: 00:22:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Overview): 00:02:00 •scikit-learn - Principal Component Analysis (PCA) - (Project Solutions): 00:17:00 •Theory: Recommender Systems their Types and Importance: 00:06:00 •Python for Recommender Systems - Hands-on (Part 1): 00:18:00 •Python for Recommender Systems - - Hands-on (Part 2): 00:19:00 •Natural Language Processing (NLP) - (Theory Lecture): 00:13:00 •NLTK - NLP-Challenges, Data Sources, Data Processing ..: 00:13:00 •NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing: 00:19:00 •NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW.: 00:19:00 •NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes : 00:13:00 •NLTK - NLP - Pipeline feature to assemble several steps for cross-validation: 00:09:00 •Resources- Python for Data Analysis: 00:00:00

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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 This course is intended for This course is suitable for anyone responsible for configuring, managing or supporting a Veeam Availability Suite v11 environment. This includes Senior Engineers and Architects responsible for creating architectures for Veeam environments. Overview After completing this course, attendees should be able to: Describe Veeam Availability Suite components usage scenarios and relevance to your environment. Effectively manage data availability in on-site, off-site, cloud and hybrid environments. Ensure both Recovery Time Objectives (RTOs) and Recovery Point Objectives (RPOs) are met. Configure Veeam Availability Suite to ensure data is protected effectively. Adapt with an organization's evolving technical and business data protection needs. Ensure recovery is possible, effective, efficient, secure and compliant with business requirements. Provide visibility of the business data assets, reports and dashboards to monitor performance and risks. Design and architect a Veeam solution in a real-world environment Describe best practices, review an existing infrastructure and assess business/project requirements Identify relevant infrastructure metrics and perform component (storage, CPU, memory) quantity sizing Provide implementation and testing guidelines in line with designs Innovatively address design challenges and pain points, matching appropriate Veeam Backup & Replication features with requirements Veeam Certified Architect is the highest level of Veeam technical certifications. Engineers who complete both Veeam Availability Suite v11: Configuration and Management and Veeam Backup & Replication V11: Architecture and Design programs (courses + exams) will be granted with the 'Veeam Certified Architect' (VMCA) title by Veeam. Introduction Veeam Availability Suite v11: Configuration and Management Describe RTOs and RPOs, what they mean for your business, how to manage and monitor performance against them The 3-2-1 Rule and its importance in formulating a successful backup strategy Identify key Veeam Availability Suite components and describe their usage scenarios and deployment types Building backup capabilities Backup methods, the appropriate use cases and impact on underlying file systems Create, modify, optimize and delete backup jobs, including Agents and NAS Backup jobs. Explore different tools and methods to maximize environment performance Ensure efficiency by being able to select appropriate transport modes while being aware of the impact of various backup functions on the infrastructure Building replication capabilities Identify and describe the options available for replication and impacts of using them Create and modify replication jobs, outline considerations to ensure success Introduce the new Continuous Data Protection (CDP) policy Secondary backups Simple vs. advanced backup copy jobs, how to create and modify them using best practices to ensure efficient recovery Discuss using tapes for backups Advanced repository capabilities Ensure repository scalability using a capability such as SOBR on-premises and off-site including integration with cloud storage Ensure compatibility with existing deduplication appliances Introduce the new hardened repository Protecting data in the cloud Review how Veeam can protect the data of a cloud native application Review how Veeam Cloud Connect enables you to take advantage of cloud services built on Veeam Review how Veeam can be used to protect your Office 365 data Restoring from backup Ensure you have the confidence to use the correct restore tool at the right time for restoring VMs, bare metal and individual content such as files and folders Utilize Secure Restore to prevent the restoration of malware Describe how to use Staged Restore to comply with things like General Data Protection Regulation (GDPR) before releasing restores to production Identify, describe and utilize the different explores and instant recovery tools and features Recovery from replica Identify and describe in detail, failover features and the appropriate usage Develop, prepare and test failover plans to ensure recovery Disaster recovery from replica to meet a variety of real-world recovery needs Testing backup and replication Testing backups and replicas to ensure you can recover, what you need, when you need to Configure and setup virtual sandbox environments based on backup, replicas and storage snapshots Veeam Backup Enterprise Manager and Veeam ONE Introduce the concept of monitoring your virtual, physical and cloud environments with Veeam Backup Enterprise Manager and Veeam ONE? Configuration backup Locate, migrate or restore backup configuration Introduction Veeam Backup & Replication v11: Architecture and Design Review the architecture principles Explore what a successful architecture looks like Review Veeam?s architecture methodology Discovery Analyze the existing environment Uncover relevant infrastructure metrics Uncover assumptions and risks Identify complexity in the environment Conceptual design Review scenario and data from discovery phase Identify logical groups of objects that will share resources based on requirements Create a set of detailed tables of business and technical requirements, constraints, assumptions and risks Review infrastructure data with each product component in mind Create high level design and data flow Logical design Match critical components and features of VBR with requirements Create logical groupings Determine location of components and relationship to logical grouping Aggregate totals of component resources needed per logical grouping Calculate component (storage, CPU, memory) quantity sizing Physical/tangible design Convert the logical design into a physical design Physical hardware sizing Create a list of physical Veeam backup components Implementation and Governance Review physical design and implantation plan Review Veeam deployment hardening Describe the architect?s obligations to the implementation team Provide guidance on implementation specifics that relate to the design Validation and Iteration Provide framework for how to test the design Further develop the design according to a modification scenario