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Internal Audit Skills Training Course is suitable for anyone aspiring to start working in internal audit. This course will also help anyone looking to learn in-depth about the responsibilities of an internal auditor at work. You can add this qualification to your CV. You'll be able to download your certificate instantly without any cost after completing the Internal Auditor Course. To make this course more accessible for you, we have designed it for both part-time and full-time students. This course is packed into bite-size modules for your convenience. You can study at your own pace or become accredited within hours! If you require support, our experienced tutors are always available to help you throughout the comprehensive syllabus of this course and answer all your queries through email. Who is this Internal Auditor Course for? Internal Auditor Course is suitable for anyone who wants to gain extensive knowledge, potential experience and professional skills in the related field. This course is CPD accredited so you don't have to worry about the quality. Requirements Our Internal Auditor Course is open to all from all academic backgrounds and there is no specific requirements to attend this course. It is compatible and accessible from any device including Windows, Mac, Android, iOS, Tablets etc. 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 This Course opens a new door for you to enter the relevant job market and also gives you the opportunity to acquire extensive knowledge along with required skills to become successful. You will be able to add our qualification to your CV/resume which will help you to stand out in the competitive job industry. Course Curriculum Mastering the Five Levels of Audit Skills Module 01: How to Get the Most from This Course 00:35:00 Module 02: Techniques for Planning Useful Audits 00:30:00 Module 03: Techniques for Detailed Risk and Control Assessment 00:40:00 Module 04: Testing and Sampling Techniques 00:30:00 Module 05: Documentation and Issue Development 00:40:00 Module 06: Core Competencies You Need as an Auditor 00:30:00 Module 07: Techniques for Managing the Audit Team 00:30:00 Module 08: Techniques for Managing the Constituent Relationship 00:40:00 Module 09: Auditing 00:05:00 Module 10: Internal Audit 00:05:00 Module 11: The Audit 00:05:00 Module 12: Audit Checklist 00:05:00 Module 13: Conducting an Audit 00:05:00 Module 14: Noncompliance and Corrective Action 00:05:00 Module 15: Audit Closing 00:05:00 Mock Exam Mock Exam - Internal Audit Skills Training Course 00:20:00 Final Exam Final Exam - Internal Audit Skills Training Course 00:20:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00

This ultimate course to kickstart your Python journey from scratch. This comprehensive course covers all the essential concepts of Python, providing explanations, examples, and practical implementations. Designed with beginners in mind, our goal is to help you learn and master Python by building a variety of projects.

Improve your Self Esteem and Development and feel the change in you You may think of it as your inner voice - the voice that tells you whether you are good enough to do or achieve something. If that is the case then you are suffering from lack of self esteem and self development. Self-esteem is about how we value ourselves, our perceptions and beliefs in who we are and what we are capable of. Our self-esteem can be misaligned with other people's perception of who we are. Self development is a lifelong process. It is a way for people to assess their skills and qualities, consider their aims in life and set goals in order to realise and maximise their potential. Although early life development and early formative experiences within the family, at school, etc. can help to shape us as adults, personal development should not stop later in life. With this course you can learn how to improve on your self esteem and development so that you can tackle day to day situations with more confidence. Course Highlights Self Esteem & Self Development Course is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Self Esteem & Self Development Course into 45 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 1 day, 16 hours  and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose Self Esteem & Self Development Course Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Self Esteem & Self Development Course is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Self Esteem & Self Development Course is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Development of Self Esteem INTRODUCTION FREE 01:00:00 LOW SELF-ESTEEM? Why It Occurs? FREE 01:00:00 YOUR LACK OF SELF-ESTEEM 01:00:00 SELF ESTEEM - GETTING TO THE Root OF THE ISSUE 01:00:00 SELF-ESTEEM AND THE INNER VOICE 01:00:00 YOU GET WHAT YOU PROJECT 01:00:00 SELF-ESTEEM BUILDING EXERCISES 01:00:00 WHERE, WHEN AND HOW TO BUILD SELF-ESTEEM 01:00:00 CONCLUSION 00:30:00 Being Assertive Module One - Getting Started FREE 01:00:00 Module Two - What Does Self-Confidence Mean To You FREE 01:00:00 Module Three - Obstacles to Our Goals 01:00:00 Module Four - Communication Skills 01:00:00 Module Five - The Importance of Goal Setting 01:00:00 Module Six - Feeling the Part 01:00:00 Module Seven - Looking the Part 01:00:00 Module Eight - Sounding the Part 01:00:00 Module Nine - Powerful Presentations 00:30:00 Module Ten - Coping Techniques 01:00:00 Module Eleven - Dealing with Difficult Behavior 00:30:00 Module Twelve - Wrapping Up 00:15:00 Assertiveness Skills Training Diploma- Activities 00:00:00 Development of the Self Self Development through Visualization and Affirmation 01:00:00 Hints in Affirmation and Visualization 01:00:00 Development for Affirmation and Visualization 01:00:00 How to Build Critical Thinking Skills 01:00:00 Visualizing Problems with Affirmations 01:00:00 Development Evaluation in Affirmation and Visualization 00:30:00 Practice Development through Visualization and Affirmation 01:00:00 Self-Development Procedures through Visualization 01:00:00 Development thru Visualization of Problems in Affirmation 01:00:00 Process of Affirmation through Development Visualization 01:00:00 Sense of Development thru Affirmation and Visualization 01:00:00 Natural Development thru Affirmation and Visualization 01:00:00 Visualization through Development Affirmation 01:00:00 Choices in Development thru Affirmation and Visualization 01:00:00 Development thru Argument Affirmation and Visualization 01:00:00 Visualization in Development of Affirmation 01:00:00 Revolutionary Development thru Visualization and Affirmation 00:30:00 Focus for Development thru Visualization and Affirmation 01:00:00 Visualization Music thru Affirmation Development 01:30:00 Energy Development thru Visualization and Affirmation 01:00:00 Relax with Development thru Affirmative Visualization 01:00:00 New Age Development in Affirmative Visualization 01:00:00 Conclusion 00:15:00 Mock Exam Mock Exam- Self Esteem & Self Development Course 00:30:00 Final Exam Final Exam- Self Esteem & Self Development Course 00:30:00

Duration 4 Days 24 CPD hours This course is intended for The course content is aimed at operators of devices running the Junos OS in a NOC environment. These operators include network engineers, administrators, support personnel, and reseller support personnel. Overview After successfully completing this course, you should be able to: Reduce the time it takes to identify and isolate the root cause of an issue impacting your network. Gain familiarity with Junos products as they pertain to troubleshooting. Become familiar with online resources valuable to Junos troubleshooting. Gain familiarity with Junos tools used in troubleshooting. Identify and isolate hardware issues. Troubleshoot problems with the control plane. Troubleshoot problems with interfaces and other data plane components. Describe the staging and acceptance methodology. Troubleshoot routing protocols. Describe how to monitor your network with SNMP, RMON, Junos Traffic Vision (formerly known as JFlow), and port mirroring. Become familiar with JTAC procedures. This instructor-led four-day course is designed to provide introductory troubleshooting skills for engineers in a network operations center (NOC) environment. Chapter 1: Course Introduction Course Introduction Chapter 2: Troubleshooting as a Process Before You Begin The Troubleshooting Process Challenging Network Issues The Troubleshooting Process Lab Chapter 3: Junos Product Families The Junos OS Control Plane and Data Plane Field-Replaceable Units Junos Product Families Lab: Identifying Hardware Components Chapter 4: Troubleshooting Toolkit Troubleshooting Tools Best Practices Lab: Using Monitoring Tools and Establishing a Baseline Chapter 5: Hardware and Environmental Conditions Hardware Troubleshooting Overview Memory and Storage Boot Monitoring Hardware-Related System Logs Chassis and Environmental Monitoring Lab: Monitoring Hardware and Environmental Conditions Chapter 6: Control Plane Control Plane Review System and User Processes Monitoring Routing Tables and Protocols Monitoring Bridging Monitoring the Address Resolution Protocol Lab: Control Plane Monitoring and Troubleshooting Chapter 7: Control Plane Protection Protection Overview DDOS Protection Loopback Filter Lab: Control Plane Monitoring and Troubleshooting Chapter 8: Data Plane ? Interfaces Interface Properties General Interface Troubleshooting Ethernet Interface Troubleshooting Lab: Monitoring and Troubleshooting Ethernet Interfaces Chapter 9: Data Plane ? Other Components Definition of a Data Plane Problem Data Plane Components Data Plane Forwarding Load-Balancing Behavior Firewall Filters and Policers Data Plane Troubleshooting Case Study Lab: Isolate and Troubleshoot PFE Issues Chapter 10: Staging and Acceptance Testing Initial Inspection and Power-on General System Checks Interface Testing Chapter 11: Troubleshooting Routing Protocols Troubleshooting OSPF Troubleshooting BGP Troubleshooting Routing Loops and Route Oscillation Lab: Troubleshooting Routing Protocols Chapter 12: High Availability High Availability Overview Graceful Routing Engine Switchover Graceful Restart Nonstop Active Routing and Bridging Unified In-Service Software Upgrade Chapter 13: Network Monitoring SNMP RMON Telemetry Flow Monitoring Lab: Monitoring the Network Chapter 14: vMX Troubleshooting vMX Overview Troubleshooting Lab: Monitoring vMX Chapter 15: JTAC Procedures Opening a Support Case Customer Support Tools The Content of a PR Transferring Files to JTAC Chapter 16: Automated Support and Prevention Overview Service Now Service Insight Lab: Automated Support and Prevention Additional course details: Nexus Humans JTNOC - Junos Troubleshooting in the NOC 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 JTNOC - Junos Troubleshooting in the NOC 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.

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. 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 00:08:00 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 Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 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 00:07:00 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 - Python Machine Learning & Data Science Fundamentals 00:00:00

Equip educators with essential Autism Awareness Training for Teachers to foster an inclusive classroom environment. Enhance understanding, support, and communication strategies for effectively engaging with autistic students. Enroll now to promote a more inclusive and supportive educational experience for all learners.

Duration 5 Days 30 CPD hours This course is intended for Experienced system administrators and network administrators Network and security professionals who work with enterprise and data center networks Overview By the end of the course, you should be able to meet the following objectives: Use the native tools available in NSX-T Data Center to identify and troubleshoot the problems related to the NSX-T Data Center environment Use VMware vRealize Log Insight™ and VMware vRealize Network Insight™ to identify and troubleshoot the problems related to the NSX-T Data Center environment Explain the NSX-T Data Center infrastructure components and the communications between them Identify, analyze, and troubleshoot problems related to the management, control, and data planes in NSX-T Data Center Identify, analyze, and troubleshoot problems related to infrastructure preparation in NSX-T Data Center Identify, analyze, and troubleshoot problems related to logical switching and logical routing in NSX-T Data Center Identify, analyze, and troubleshoot network security problems related to the NSX-T Data Center Distributed and Gateway firewalls Identify, analyze, and troubleshoot problems related to VPN and the VMware NSX Advanced Load Balancer™ Identify the components and packet flows involved in the NSX-T Data Center datapath and troubleshoot related problems This five-day, hands-on training course provides the advanced knowledge, skills, and tools to achieve competency in operating and troubleshooting the VMware NSX-T? Data Center environment. In this course, you are introduced to workflows of various networking and security constructs along with several operational and troubleshooting tools that help you manage and troubleshoot your NSX-T Data Center environment.In addition, you are presented with various types of technical problems, which you will identify, analyze, and solve through a systematic process. Course Introduction Introduction and course logistics Course objectives NSX-T Data Center Operations and Tools Explain and validate the native troubleshooting tools (dashboards, Traceflow, live traffic analysis, port mirroring) for the NSX-T Data Center environment Configure syslog, IPFIX, and log collections for the NSX-T Data Center environment Integrate NSX-T Data Center with vRealize Log Insight and vRealize Network Insight Validate and review the API methods available to configure the NSX-T Data Center environment Troubleshooting the NSX Management Cluster Describe the NSX Management cluster architecture, components, and communication channels Identify the workflows involved in configuring the NSX Management cluster Validate and troubleshoot the NSX Management cluster formation Troubleshooting Infrastructure Preparation Describe the data plane architecture, components, and communication channels Explain and troubleshoot VMware ESXi? transport node preparation issues Explain and troubleshoot KVM transport node preparation issues Explain and troubleshoot VMware NSX© Edge? transport node preparation issue Troubleshooting Logical Switching Describe the architecture of logical switching List the modules and processes involved in configuring logical switching Explain the importance of N-VDS and VDS in transport nodes Describe the procedure to migrate from N-VDS to VDS Review the architecture and workflows involved in attaching workloads to segments Identify and troubleshoot common logical switching issues Troubleshooting Logical Routing Review the architecture of logical routing and NSX Edge nodes Explain the workflows involved in the configuration of Tier-0 and Tier-1 gateways Explain the high availability modes and validate logical router placements Identify and troubleshoot common logical routing issues using both BGP and OSPF Troubleshooting Security Review the architecture of the Distributed Firewall Explain the workflows involved in configuring the Distributed Firewall Review the architecture of the Gateway Firewall Explain the workflows involved in configuring the Gateway Firewall Identify and troubleshoot common distributed firewall and Gateway Firewall issues Troubleshooting the NSX Advanced Load Balancer and VPN Services Review the NSX Advanced Load Balancer architecture and components Identify and troubleshoot common NSX Advanced Load Balancer issues Review of IPsec and L2 VPN architecture and components Identify and troubleshoot common IPsec and L2 VPN issues Datapath Walkthrough Verify and validate the path of the packet on the NSX datapath (East-West and South-North) Identify and perform packet captures at various points in the datapath Use NSX CLI and native hypervisor commands to retrieve configurations involved in the NSX datapath

Master the art of wildlife rescue and rehabilitation. This course covers safety, health, injuries, and effective interaction with animals.

This accredited course gives you an introduction to mental health and wellbeing - what it is, how to take care of yourself and support others

Stress Management Approved Online Training