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Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. 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 00:04:00 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 Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 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 00:06:00 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 - Data Science & Machine Learning with Python 00:00:00
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As a responsible adult, it is your responsibility to protect children and adults from all forms of abuse. ThisCare and Support for Vulnerable Children: Care and Support for Vulnerable Children course will walk you through the fundamentals. This course will also teach you how to perform on unresponsive casualties and how to assist them. You will also learn how to handle common problems and perform basic maintenance, as well as identify vulnerable children, health care, and other areas. In addition, how to work with children and adolescents, and how adults can support children in times of crisis. This Care and Support for Vulnerable Children: Care and Support for Vulnerable Children course will ensure that you stand out from the crowd. [ Note: Free PDF certificate will provide as soon as completing the Care and Support for Vulnerable Children: Care and Support for Vulnerable Children Course] Course Curriculum of Care and Support for Vulnerable Children: Care and Support for Vulnerable Children Module 01: Introduction Module 02: The Rights of Children Module 03: Understanding the Distinction Between Vulnerability and Risk Module 04: Child in Crisis Module 05: Controlling The Issues Module 06: Available Services Module 07: History and Future Developments Assessment Method of Care and Support for Vulnerable Children: Care and Support for Vulnerable Children After completing Care and Support for Vulnerable Children Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. 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Requirements Care and Support for Vulnerable Children: Care and Support for Vulnerable Children Online To enrol in this Care and Support for Vulnerable Children Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Care and Support for Vulnerable Children Course. Be energetic and self-motivated to complete our Care and Support for Vulnerable Children Course. Basic computer Skill is required to complete our Care and Support for Vulnerable Children Course. If you want to enrol in our Care and Support for Vulnerable Children Course, you must be at least 15 years old. Career path Care and Support for Vulnerable Children: Care and Support for Vulnerable Children Online Our Care and Support for Vulnerable Children: Care and Support for Vulnerable Childrencourse is intended to help you land your dream job or even the promotion you've always desired. Learn the necessary skills and knowledge to excel in your professional life with the assistance and guidance of this course.
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Duration 5 Days 30 CPD hours This course is intended for The primary audiences for this course are the following: • Operators of Juniper Networks security solutions, including network engineers, administrators, support personnel, and resellers. Overview After successfully completing this course, you should be able to: Identify security challenges in today's networks. Identify products that are incorporated into the Juniper Connected Security solution. Explain the value of implementing security solutions. Explain how Juniper Connected Security solves the cyber security challenges of the future. Explain SRX Series session management. Explain Junos ALG functions and when to use them. Describe policy logging on the SRX series device. Explain security policy scheduling. Describe application security theory. Explain application signature usage in AppID. Describe the AppTrack service. Describe the AppFW service. Describe the AppQoS service. Configure security policies using the AppSecure suite of services. Explain unified security policies. Describe IPS signatures. Configure an IPS policy using pre-defined templates. Describe how to update the IPS attack object database. Describe IPS rules and rule bases. Configure custom attack objects. Describe Junos Space and Security Director. Configure policy management using Security Director. Describe Security Director objects. Explain the different licensing options for Sky ATP List Sky ATP's features and benefits. Configure Sky ATP profiles and enroll an SRX Series device. Configure file scanning on Sky ATP. Configure Sky ATP to scan email Configure GeoIP on Sky ATP. Describe the JATP features and benefits List the JATP device options. Explain the JATP architecture. List 3rd party support options for JATP. Explain JATP SmartCore analytics processes. Describe Policy Enforcer configuration options. Describe Policy Enforcer integration with Sky ATP. Configure Policy Enforcer to block lateral malware movement. Explain Juniper Secure Analytics features and benefits. Describe JSA log collection. Describe JSA network flow collection. Describe the JSA Offense Management workspace. Explain the JSA Risk Manager features. Configure JSA to collect network and log collection. Explain the features of JIMS. Describe JIMS integration into the current AD network. Describe the Sky Enterprise service and how it can save resources. Explain the Sky Enterprise monitoring service. Explain the vSRX Series device benefits. Describe use cases for the vSRX. Explain the cSRX Series device benefits. Describe use cases for the cSRX. Describe SSL Proxy Concepts. Explain Forward and Reverse Proxy and the limitations of each. Configure both Forward and Reverse Proxy. This five-day course uses the Junos J-Web, CLI, Junos Space, and other user interfaces to introduce students to the concept of Juniper Connected Security. Chapter 1: Course Introduction Course Introduction Chapter 2: CLI Overview User Interface Options Command-Line Interface Initial Configuration Interface Configuration Lab 1: CLI Overview Chapter 3: Advanced Security Policy Session Management Junos ALGs Policy Scheduling Policy Logging Lab 2: Advanced Security Policy Chapter 4: Application Security Theory Application ID Application Signatures App Track App Firewall App QoS App QoE Chapter 5: Application Security Implementation AppTrack Implementation AppFW Implementation AppQos Implementation APBR Implementation Lab 3: Application Security Chapter 6: Intrusion Detection and Prevention IPS Overview IPS Policy Attack Objects IPS Configuration IPS Monitoring Lab 4: Implementing IPS Chapter 7: Security Director Overview Security Director Objects Security Director Policy Management Lab 5: Security Director Chapter 8: Sky ATP Implementation Architecture and Key Components Features and Benefits Configuration Compromised Hosts Command and Control File Scanning E-mail Scanning Geo IP Security Policy Integration Troubleshooting Lab 6: Sky ATP Implementation Chapter 9: Policy Enforcer Policy Enforcer Concepts Configuration Options Policy Enforcer Installation Lab 7: Policy Enforcer Chapter 10: JATP Overview Traffic Inspection Threat Detection Threat Analysis JATP Architecture Chapter 11: JATP Implementation Data Collectors Configure SmartCore Analytics Engine Log Ingestion Incident Management SRX Threat Prevention 3rd Party support for Threat Prevention Reporting Lab 8: JATP Chapter 12: Juniper Secure Analytics (JSA) JSA Overview Data Collection Log Analytics Threat Analytics Vulnerability Management Risk Management Lab 9: JSA Chapter 13: JIMS JIMS Overview JIMS Integration Lab 10: JIMS Chapter 14: vSRX and cSRX vSRX Overview vSRX Supported Features vSRX Use Cases cSRX Overview Lab 11: vSRX Installation Chapter 15: SSL Proxy SSL Proxy Overview SSL Concepts SSL Proxy Configurations Troubleshooting Lab 12: SSL Proxy Chapter 16: Cluster Concepts Chassis Cluster Concepts Chassis Cluster Operation Chapter 17: Chassis Cluster Implementation Chassis Cluster Configuration Chassis Cluster Advanced Options Lab 13: Chassis Cluster Implementation Chapter 18: Chassis Cluster Troubleshooting Chassis Cluster Case Studies Troubleshooting Examples Lab 14: Chassis Cluster Troubleshooting Additional course details: Nexus Humans JSEC - Junos Security 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 JSEC - Junos Security 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 intended for those who provide site collection and site administration and are power users or IT professionals who are tasked with supporting or working within the SharePoint 2016 environment on premise and/or in Office 365. Overview After completing this course, students will be able to: - Design and implement a company portal structure using SharePoint 2016 objects including sites, libraries, lists and pages - Explain the role of security and permissions throughout SharePoint 2016 - Implement guidelines for consistency in building a company portal to aid in the day-to-day administration of content in SharePoint 2016 - Enhance the design and content of a company portal using SharePoint 2016 pages and web parts - Explain the importance of governance for the planning and managing future growth of the - SharePoint 2016 implementation - Identify options to integrate data from other systems such as Microsoft Office, as well as preserve existing data - Explain the role of social networking in SharePoint 2016 and its impact on collaboration This course is intended for power users and IT professionals who are tasked with working within the SharePoint 2016 environment and conduct site collection and site administration. Getting Started with SharePoint 2016 Exploring SharePoint 2016 Site Collection and Site Administrator Roles Defining SharePoint Terminology Navigating a SharePoint Site Interacting with the Ribbon Creating and Editing Basic Content What is Metadata? Versions of SharePoint Standard Enterprise O365 Building a Site Collection with Apps The Structure of SharePoint Creating a Site What does a site template come with? Defining SharePoint Apps Customizing Lists and Libraries Creating/Managing Lists and Libraries through SharePoint Designer Explaining Views on Lists and Libraries Creating Views in Lists and Libraries Modifying Navigation Turning Site Features On/Off Reorganizing a Site using Site Content and Structure feature Lab 1: Creating a Structured Company Portal Lab 2: Creating a List Using SharePoint Designer (Optional) Creating Consistency across Sites Defining Site Columns Defining Content Types Implementing a Taxonomy Using Templates to Promote Consistency Lab 1: Creating Site Columns and Content Types Lab 2: Implementing a Taxonomy Lab 3: Configuring the Content Organizer SharePoint Permissions Explaining Permissions and Security in SharePoint Creating SharePoint Groups Managing Permissions within SharePoint Sharing versus Traditional Security Sharing as different permission levels Lab 1: Managing Permissions in SharePoint Working with Pages and Web Parts Changing the Appearance of the Portal Editing a Page wiki web part Working with Web Parts and App Parts App Parts Content Search Web Part Relevant Documents Content query Table of Contents Pictures Web Part Connections Filter web parts Web parts with Targeting Audience Lab 1: Adding and Configuring Web Parts Lab 2: Connecting Web Parts Lab 3: Applying Themes to Your Company Portal Document and Records Management Basic Content Approval Versioning Check In/Out Holds Retention Policy Document ID Content Organizer Compliance Policy Center Site Template EDiscovery Records Center Lab 1: Working with Advanced Document Management Features Lab 2: Leveraging Records Management to Preserve Data Workflow Alerts Out of the Box Workflow Activating Workflow Features Approval Workflow Creating a Workflow in SharePoint Designer Lab 1: Creating an Approval Workflow from SharePoint Lab 2: Creating a Custom Workflow in SharePoint Designer (Optional) Office Integration Outlook Calendar Contacts Excel Word PowerPoint OneDrive for Business OneNote Access Lab 1: Importing and Exporting Excel Data with SharePoint Lab 2: Linking Outlook and SharePoint Creating Publishing Sites Why use a publishing site? Publishing Pages Enabling Web Content Management Managing the Structure of Web Content Navigating a Site Using Managed Metadata Lab 1: Creating a Rich Publishing Sit Lab 2: Configuring a Publishing Approval Process Lab 3: Implementing a Managed Navigation Site Bridging the Social Gap My Sites Configuring Social Features in SharePoint Posts, Tags and Mentions Creating a Community Site Lab 1: Designing a Social Experience in SharePoint 2016 Lab 2: Creating a Community Site Finding Information Using Search Exploring the Search Features in SharePoint Configuring Search Settings Search Analytics Search Visibility Lab 1: Configuring an Advanced Search Center Planning a Company Portal Using SharePoint Defining SharePoint Governance Working with Information Architecture Implementing Site Hierarchies Discussing the Execution of Governance Site Collection Administrator Settings Exploring Settings for Site Collection Administrators Exploring Settings for Site Administrators Site Closure Policies Additional course details: Nexus Humans 55234 SharePoint 2016 Site Collections and Site Owner Administration 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 55234 SharePoint 2016 Site Collections and Site Owner Administration 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.