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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 CompTIA Network+ Certification (N10-007) 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 CompTIA Network+ Certification (N10-007) for? Aspiring IT professionals seeking to kickstart their careers in networking. Students aiming to enhance their employability with industry-recognized certifications. Career changers looking to transition into the dynamic field of information technology. IT professionals seeking to validate their skills and advance their careers. Anyone passionate about mastering the intricacies of comptia network and carving a niche in the digital landscape. Prerequisites This CompTIA Network+ Certification (N10-007) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This CompTIA Network+ Certification (N10-007) 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 Network Administrator: £20,000 - £45,000 Per Annum Network Engineer: £25,000 - £55,000 Per Annum Systems Administrator: £22,000 - £50,000 Per Annum IT Support Technician: £18,000 - £35,000 Per Annum Cyber Security Analyst: £25,000 - £60,000 Per Annum Cloud Solutions Architect: £30,000 - £80,000 Per Annum Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Network Models What is a Model? 00:02:00 OSI vs. TCP/IP Model 00:07:00 Walking Through OSI and TCP/IP 00:12:00 Meet the Frame 00:06:00 The MAC Address 00:07:00 Broadcast vs. Unicast 00:04:00 Introduction to IP Addressing 00:08:00 Packets and Ports 00:05:00 Section 03: Cabling and Topology Network Topologies 00:10:00 Coaxial Cabling 00:05:00 Twisted Pair Cabling 00:06:00 Cat Ratings 00:06:00 Fiber Optic Cabling 00:09:00 Fire Ratings 00:05:00 Legacy Network Connections 00:07:00 Section 04: Ethernet Basics What is Ethernet? 00:07:00 Ethernet Frames 00:07:00 Early Ethernet 00:08:00 The Daddy of Ethernet, 10BaseT 00:03:00 Terminating Twisted Pair 00:14:00 Hubs vs. Switches 00:13:00 Section 05: Modern Ethernet 100BaseT 00:05:00 Connecting Switches 00:05:00 Gigabit Ethernet and 10-Gigabit Ethernet 00:05:00 Transceivers 00:07:00 Connecting Ethernet Scenarios 00:14:00 Section 06: Installing a Physical Network Introduction to Structured Cabling 00:04:00 Terminating Structured Cabling 00:08:00 Equipment Room 00:07:00 Alternative Distribution Panels 00:04:00 Testing Cable 00:09:00 Troubleshooting Structured Cabling, Part 1 00:05:00 Troubleshooting Structured Cabling, Part 2 00:05:00 Using a Toner and Probe 00:03:00 Wired Connection Scenarios 00:11:00 Section 07: TCP/IP Basics Introduction to IP Addressing and Binary 00:13:00 Introduction to ARP 00:04:00 Classful Addressing 00:10:00 Subnet Masks 00:12:00 Subnetting with CIDR 00:10:00 More CIDR Subnetting Practice 00:10:00 Dynamic and Static IP Addressing 00:18:00 Rogue DHCP Servers 00:07:00 Special IP Addresses 00:07:00 IP Addressing Scenarios 00:15:00 Section 08: Routing Introducing Routers 00:15:00 Understanding Ports 00:05:00 Network Address Translation 00:06:00 Implementing NAT 00:03:00 Forwarding Ports 00:18:00 Tour of a SOHO Router 00:12:00 SOHO vs. Enterprise 00:09:00 Static Routes 00:13:00 Dynamic Routing 00:11:00 RIP 00:04:00 OSPF 00:04:00 BGP 00:06:00 Section 09: TCP/IP Applications TCP and UDP 00:07:00 ICMP and IGMP 00:06:00 Handy Tools 00:07:00 Introduction to Wireshark 00:11:00 Introduction to netstat 00:09:00 Web Servers 00:12:00 FTP 00:12:00 E-mail Servers and Clients 00:09:00 Securing E-mail 00:06:00 Telnet and SSH 00:09:00 Network Time Protocol 00:02:00 Network Service Scenarios 00:10:00 Section 10: Network Naming Understanding DNS 00:12:00 Applying DNS 00:19:00 The Hosts File 00:04:00 Net Command 00:08:00 Windows Name Resolution 00:11:00 Dynamic DNS 00:05:00 DNS Troubleshooting 00:13:00 Section 11: Securing TCP/IP Making TCP/IP Secure 00:04:00 Symmetric Encryption 00:06:00 Asymmetric Encryption 00:03:00 Cryptographic Hashes 00:05:00 Identification 00:12:00 Access Control 00:04:00 AAA 00:05:00 Kerberos/EAP 00:08:00 Single Sign-On 00:10:00 Certificates and Trust 00:14:00 Certificate Error Scenarios 00:08:00 Section 12: Advanced Networking Devices Understanding IP Tunneling 00:06:00 Virtual Private Networks 00:13:00 Introduction to VLANs 00:12:00 InterVLAN Routing 00:03:00 Interfacing with Managed Switches 00:11:00 Switch Port Protection 00:07:00 Port Bonding 00:07:00 Port Mirroring 00:04:00 Quality of Service 00:05:00 IDS vs. IPS 00:04:00 Proxy Servers 00:13:00 Load Balancing 00:09:00 Device Placement Scenarios 00:13:00 Section 13: IPv6 Introduction to IPv6 00:13:00 IPv6 Addressing 00:15:00 IPv6 in Action 00:13:00 IPv4 and IPv6 Tunneling 00:05:00 Section 14: Remote Connectivity Telephony Technologies 00:09:00 Optical Carriers 00:03:00 Packet Switching 00:05:00 Connecting with Dial-up 00:05:00 Digital Subscriber Line (DSL) 00:05:00 Connecting with Cable Modems 00:04:00 Connecting with Satellites 00:03:00 ISDN and BPL 00:04:00 Remote Desktop Connectivity 00:05:00 Advanced Remote Control Systems 00:09:00 Section 15: Wireless Networking Introduction to 802.11 00:12:00 802.11 Standards 00:12:00 Power over Ethernet (PoE) 00:04:00 Antennas 00:09:00 Wireless Security Standards 00:16:00 Implementing Wireless Security 00:07:00 Threats to Your Wireless Network 00:07:00 Retro Threats 00:05:00 Wi-Fi Protected Setup (WPS) 00:05:00 Enterprise Wireless 00:06:00 Installing a Wireless Network 00:15:00 Wireless Scenarios 00:07:00 More Wireless Scenarios 00:09:00 Section 16: Virtualization and Cloud Computing Virtualization Basics 00:07:00 Cloud Ownership 00:03:00 Cloud Implementation 00:12:00 Your First Virtual Machine 00:09:00 NAS and SAN 00:16:00 Platform as a Service (PaaS) 00:09:00 Software as a Service (SaaS) 00:03:00 Infrastructure as a Service (IaaS) 00:10:00 Section 17: Mobile Networking Cellular Technologies 00:05:00 Mobile Connectivity 00:07:00 Deploying Mobile Devices 00:05:00 Mobile Access Control 00:06:00 Section 18: Building a Real-World Network Network Types 00:04:00 Network Design 00:10:00 Power Management 00:06:00 Unified Communications 00:11:00 Network Documentation 00:07:00 Contingency Planning 00:10:00 Predicting Hardware Failure 00:05:00 Backups 00:08:00 Section 19: Managing Risk What is Risk Management? 00:06:00 Security Policies 00:08:00 Change Management 00:07:00 User Training 00:03:00 Standard Business Documentation 00:05:00 Mitigating Network Threats 00:05:00 High Availability 00:05:00 Section 20: Protecting Your Network Denial of Service 00:09:00 Malware 00:10:00 Social Engineering 00:04:00 Access Control 00:08:00 Man-in-the-Middle 00:22:00 Introduction to Firewalls 00:05:00 Firewalls 00:10:00 DMZ 00:06:00 Hardening Devices 00:14:00 Physical Security Controls 00:09:00 Testing Network Security 00:08:00 Network Protection Scenarios 00:14:00 Section 21: Network Monitoring SNMP 00:15:00 Documenting Logs 00:09:00 System Monitoring 00:08:00 SIEM (Security Information and Event Management) 00:07:00 Section 22: Network Troubleshooting Network Troubleshooting Theory 00:05:00
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You don't need any educational qualification or experience to enrol in the Deep Learning & Neural Networks Python - Keras: For Dummies 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 Deep Learning & Neural Networks Python - Keras: For Dummies course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. 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