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Duration 4 Days 24 CPD hours This course is intended for Security-operations (SecOps), or security, orchestration, automation, and response (SOAR) engineers, managed security service providers (MSSPs), service delivery partners, system integrators, and professional services engineers Overview This training is designed to enable a SOC, CERT, CSIRT, or SOAR engineer to start working with Cortex XSOAR integrations, playbooks, incident-page layouts, and other system features to facilitate resource orchestration, process automation, case management, and analyst workflow. The course includes coverage of a complete playbook-development process for automating a typical analyst workflow to address phishing incidents. This end-to-end view of the development process provides a framework for more focused discussions of individual topics that are covered in the course. The Cortex? XSOAR 6.8: Automation and Orchestration (EDU-380) course is four days of instructor-led training that will help you: Configure integrations, create tasks, and develop playbooks Build incident layouts that enable analysts to triage and investigate incidents efficiently Identify how to categorize event information and map that information to display fields Develop automations, manage content, indicator data, and artifact stores, schedule jobs, organize users and user roles, oversee case management, and foster collaboration This class is powered by Cloud Harmonics. Course Outline Module 1 - Core Functionality and Feature Sets Module 2 - Enabling and Configuring Integrations Module 3 - Playbook Development Module 4 - Classification and Mapping Module 5 - Layout Builder Module 6 - Solution Architecture Module 7 - Docker Module 8 - Automation Development and Debugging Module 9 - The Marketplace and Content Management Module 10 - Indicators and Threat Intelligence Management Module 11 - Jobs and Job Scheduling Module 12 - Users and Role-Based Access Controls (RBAC) Module 13 - Integration Development Additional course details: Nexus Humans Palo Alto Networks: Cortex XSOAR 6.8: Automation and Orchestration(EDU-380) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Palo Alto Networks: Cortex XSOAR 6.8: Automation and Orchestration(EDU-380) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Learn how to use culture for enhancing the employee performance with the Lean Leadership and Change Management Diploma course. The course is designed to teach you Lean leadership and change management. A lean leader will change the way your thinking and the way you lead your organisation. Lean leadership is the approach that teaches you how to improve the overall performance of your organisation by bringing change in its culture. You will learn about the lean culture and lean leadership. The course illustrates the history of lean, the essential principles and practices, and the fundamental functions of the lean leader. There are two ways of lean implementation. You can change and redesign the whole process, or you may acquire the habits of problem-solving and continuous improvement. The course covers these two processes and helps you to choose the right methods for you. The purpose of the course is to prepare you for applying the lean leadership approach of lean culture in your organisation. Who is this Course for? Lean Leadership and Change Management Diploma is 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 background. Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. 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. Assessment: This course does not involve any MCQ exams. Students need to answer 3 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work. Course Curriculum Introduction Why 00:04:00 What 00:04:00 Curriculum 00:05:00 How 00:04:00 What is Culture 00:06:00 Culture Drivers 00:08:00 Resources 00:05:00 Activity 1 00:03:00 The House of Lean House of Lean 00:03:00 Evolution 00:04:00 Shingo 00:09:00 Honda 00:09:00 Activity 2 00:02:00 Lean Culture Principles & Practices JIT 00:07:00 Kanban 00:08:00 Continuous Improvement and Leadership 00:04:00 Waste Intro 00:10:00 Forms of Waste 1 00:06:00 Management Waste 00:07:00 Activity3 00:02:00 Scientific Method 00:07:00 Gemba Walk 00:06:00 Heijunka 00:05:00 Visual Display 00:07:00 Activity 4 00:02:00 Kaizen 00:06:00 The Job of the Lean Leader - To Challenge and To Serve Lean Leadership Intro 00:07:00 The Mind of the Lean Leader 00:04:00 The Mind of the Lean Leader - Transitions 00:07:00 Lean Leadership1. External Challenge 00:05:00 Lean Leadership 2. Internal Challenge 00:06:00 Activity 5 00:02:00 Lead WSA 00:02:00 Be the Model 00:03:00 Coach Others 00:07:00 Motivation 00:04:00 Reinforce Your Strategy 00:04:00 Activity 6 00:01:00 Intrinsic Reinforcement 00:08:00 Getting to Lean - Designing the System for a New Culture Paths to Lean 00:05:00 How You Change 00:03:00 Design Thinking 00:08:00 Design Process 00:08:00 Capability Analysis 00:05:00 Charter 00:05:00 Activity 7 00:02:00 Design Team 00:06:00 Discovery 00:06:00 Discover the Process 00:07:00 Dream 00:07:00 Design technical 00:07:00 Design Structure 00:08:00 Social Design 00:06:00 Activity 8 00:03:00 VON Case Study 00:10:00 WSA Summary 00:04:00 Activity 9 00:02:00 The Habits of Continuous Improvement - The Team Kata Why Teams 00:06:00 Types of Teams 00:06:00 Team Charter 00:05:00 Team Maturity 00:05:00 Team Roles and Responsibilities 00:05:00 Team Agenda 00:05:00 Activity 10 00:02:00 Facilitation 1 00:06:00 Facilitation 2 00:04:00 Team Scoreboard 00:07:00 Activity 11 00:01:00 Map Team's Work 00:03:00 Attitudes 00:05:00 Five Whys 00:03:00 PDSA 1 00:04:00 PDSA 2 00:04:00 PDCA example 00:01:00 Activity 12 00:01:00 A3 00:05:00 Standard Work 00:05:00 Leader Standard Work 00:04:00 Activity 13 00:02:00 Summary 00:03:00 Resource Materials Resource Materials : Lean Leadership and Change Management Diploma 00:00:00 Certificate and Transcript Order Your Certificates or Transcripts 00:00:00
The course 'Deep Learning & Neural Networks Python - Keras' provides a comprehensive introduction to deep learning using the Keras library in Python. It covers topics ranging from basic neural networks to more advanced concepts, such as convolutional neural networks, image augmentation, and performance improvement techniques for various datasets. Learning Outcomes: Understand the fundamental concepts of deep learning and how it differs from traditional machine learning. Gain proficiency in using Keras, a powerful deep learning library, for building and training neural network models. Develop practical skills in creating and optimizing neural network models for different datasets, including image recognition tasks and regression problems. Why buy this Deep Learning & Neural Networks Python - Keras? 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 Deep Learning & Neural Networks Python - Keras 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 Deep Learning & Neural Networks Python - Keras 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 Deep Learning & Neural Networks Python - Keras does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning & Neural Networks Python - Keras 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 Deep Learning & Neural Networks Python - Keras is a great way for you to gain multiple skills from the comfort of your home. 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
Get up to speed with automating repetitive tasks with Python
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