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Duration 2 Days 12 CPD hours This course is intended for Security administrators who are responsible for using SaltStack SecOps to manage the security operations in their enterprise Overview By the end of the course, you should be able to meet the following objectives: Describe the architecture of SaltStack Config and SaltStack SecOps Integrate SaltStack Config with directory services. Configure roles and permissions for users and groups to manage and use SaltStack SecOps Use targeting to ensure that the jobs run on the correct minion systems Use remote execution modules to install the packages, transfer files, manage services, and manage users on minion systems Manage configuration control on the minion systems with states, pillars, requisites, and declarations Use Jinja and YAML code to manage the minion systems with the state files Enforce the desired state across minion systems automatically Use SaltStack SecOps to update the compliance and vulnerability content libraries Use SaltStack SecOps to enforce compliance and remediation on the infrastructure with industry standards Use SaltStack SecOps to provide automated vulnerability scanning and remediation on your infrastructure This two-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in using VMware vRealize© Automation SaltStack© SecOps. SaltStack SecOps allows you to scan your system for compliance against security benchmarks, detect system vulnerabilities, and remediate your results. This course enables you to create the SaltStack SecOps custom compliance libraries and use SaltStack SecOps. In addition, this course provides you with the fundamentals of how to use VMware vRealize© Automation SaltStack© Config to install software and manage system configurations. Course Introduction Introductions and course logistics Course objectives SaltStack Config Architecture Identify the SaltStack Config deployment types Identify the components of SaltStack Config Describe the role of each SaltStack Config component SaltStack Config Security Describe local user authentication Describe LDAP and Active Directory authentication Describe the roles and permissions in vRealize Automation for SaltStack Config Describe the roles and permissions in SaltStack Config Describe the SecOps permissions in SaltStack Config Describe the advanced permissions available in SaltStack Config Targeting Minions Describe targeting and its importance Target minions by minion ID Target minions by glob Target minions by regular expressions Target minions by lists Target minions by compound matching Target minions by complex logical matching Remote Execution and Job Management Describe remote execution and its importance Describe functions and arguments Create and manage jobs Use the Activities dashboard Configuration Control Through States, Pillars, Requisites, and Declarations Define the SaltStack states Describe file management in SaltStack Config Create the SaltStack state files Identify the components of a SaltStack state Describe pillar data and the uses of pillar data Configure pillar data on the SaltStack Config master server Use pillar data in variables in the state files Describe the difference between IDs and names in the state files Use the correct execution order Use requisites in the state files Using Jinja and YAML Describe the SaltStack Config renderer system Use YAML in the state files Use Jinja in the state files Use Jinja conditionals, lists, and loops Using SaltStack SecOps Comply Describe the SaltStack SecOps Comply architecture Describe CIS and DISA STIG benchmarks Describe the SaltStack SecOps Comply security library Describe the remediation differences between SaltStack SecOps and VMware Carbon Black© Create and manage the policies Create and manage the custom checks Run assessments on the minion systems Use SaltStack SecOps to remediate the noncompliant systems Manage the SaltStack SecOps Comply configuration options Manage the benchmark content ingestion Using SaltStack SecOps Protect Describe Common Vulnerabilities and Exposures (CVEs) Use the Protect dashboard Create and manage the policies Update the vulnerability library Run the vulnerability scans Remediate the vulnerabilities Manage the vulnerability exemptions

Duration 5 Days 30 CPD hours This course is intended for System administrators System engineer Overview By the end of the course, you should be able to meet the following objectives: Configure and manage complex storage solutions in a vSphere environment (including NFS, iSCSI, and so on) Configure and manage complex, scalable vSphere networking operations (vSphere Standard Switch and Distributed Switches) Deploy, manage, and optimize virtual machines (advanced configuration, content library, latency-sensitive workloads, and more) Manage business continuity and operations in your vSphere environment (VMware vCenter Server Appliance™ file-based backup, VMware vCenter Server profiles, host profiles, and so on) Plan and implement increased vSphere security (use a Key Provider, VM Encryption, CPU scheduler remediations, and so on) Troubleshoot the vSphere environment Use VMware vSphere Lifecycle Manager™ to upgrade to VMware ESXi™ hosts and virtual machines (VUM, image-based clusters, and so on) Implement vSphere cluster solutions (Cluster QuickStart wizard, VMware vSphere Distributed Resource Scheduler™, VMware vSphere High Availability, VMware vSAN™, and so on) Implement resource optimizations to streamline vSphere deployments Create an advanced configuration of vCenter Server (including an identity source) This five-day course provides hands-on training to equip students with a range of skills, from performing routine VMware vSphere© 7 administrative tasks to complex vSphere operations and configurations. Through lab-based activities, students are immersed in real-life situations faced by VMBeans, a fictitious company. These situations expose students to real-life scenarios faced by companies that are building and scaling their virtual infrastructure. Approximately 90% of the class is application-focused and taught through labs. The course aligns fully with the VMware Certified Advanced Professional ? Data Center Virtualization Deploy exam objectives. Course Introduction Introductions and course logistics Course objectives Introduction to fictitious company: VMBeans Configure and Manage Your vSphere Environment Perform various vCenter Server configurations Configure an external identity source Configure virtual networking with advanced options Configure and manage advanced storage configurations Configure vSphere clusters (also using Cluster QuickStart) Management and Operations in Your Data Center Collect vSphere log files Configure vCenter Server file-based backup Working with vCenter Server profiles Configure and manage advanced cluster settings Create and configure advanced host options Create and manage host profiles Manage and remediate clusters using vSphere Lifecycle Manager Create and configure a Content Library Update a managed virtual machine template Configure a central VMware ToolsTM installation repository Manage vSphere roles and permissions Troubleshoot Your Data Center Environment Troubleshoot vSphere configuration issues Troubleshoot resource pool configuration issues Troubleshoot network and storage issues Troubleshoot ESXi host issues Troubleshoot vCenter Server resource issues Increasing Security in Your Data Center Create and manage a Key Management solution Create an encrypted virtual machine Configure CPU scheduler options to achieve security remediations Performance and Optimization in Your Data Center Manage advanced virtual machine configurations Identify and implement vSphere resource optimization opportunities Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSphere: Advanced Administration Workshop [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 vSphere: Advanced Administration Workshop [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.

Increase your cybersecurity capability by learning to perform dynamic and static malware analysis!

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Overview This Deep Learning & Neural Networks Python - Keras: For Dummies course will unlock your full potential and will show you how to excel in a career in Deep Learning & Neural Networks Python - Keras: For Dummies. So upskill now and reach your full potential. Everything you need to get started in Deep Learning & Neural Networks Python - Keras: For Dummies is available in this course. Learning and progressing are the hallmarks of personal development. This Deep Learning & Neural Networks Python - Keras: For Dummies will quickly teach you the must-have skills needed to start in the relevant industry. In This Deep Learning & Neural Networks Python - Keras: For Dummies Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Deep Learning & Neural Networks Python - Keras: For Dummies skills to help you advance your career. 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Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

This course will provide you with practical experience in C++. You will learn the basics and advanced concepts of C++, such as data types, arrays, functions, encapsulation, inheritance, exception handling, object-oriented programming (OOP), and a lot more, by developing interesting real-world applications.

To provide the knowledge and skills required to perform an internal audit of part of a Energy management system based on ISO 50001 and report on the effective implementation and maintenance of the management system in accordance with ISO 19011.

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To provide the knowledge and skills required to perform an internal audit of part of a Energy management system based on ISO 50001 and report on the effective implementation and maintenance of the management system in accordance with ISO 19011.

Gain the skills and credentials to kickstart a successful career in the technology industry and learn from the