5673 Computing & IT courses in Kirkby delivered Online

Overview This comprehensive course on Transport Planner Course will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Transport Planner Course comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Transport Planner Course. It is available to all students, of all academic backgrounds. Requirements Our Transport Planner Course is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 16 lectures • 10:10:00 total length •An Introduction to Successful Transport Management: 01:00:00 •The UK's Travel Infrastructure - Road and Rail: 00:45:00 •Road Freight and Transport Management: 01:15:00 •Passenger Road Transport and its Management: 01:15:00 •Rail and Transport Management: 00:30:00 •Transport Management for Ports and Inland Waters: 00:30:00 •Transport Management for Airlines: 00:30:00 •Trends, Challenges and Best Practice in Transport Management: 00:15:00 •Transport Management and Health and Safety: 00:30:00 •ECC TM EWM Shipment Integrated Scenario: 00:30:00 •SAP Transportation Domestic Scenario: 00:22:00 •SAP Transportation Management (TM) Integrated Scenario: 00:15:00 •TM Overview + End to End Process Flow: 00:43:00 •SAP TM Uncontrolled Shipment Scenario: 00:28:00 •SAP TM - Air Way bill ID Generation: 00:26:00 •Effective SAP TM for perfect order fulfillment: 00:56:00

Overview Follow your dreams and develop a demanding skill for a better future. Build the practical knowledge, functional skills and high-level confidence to deal with security issues and emergency situations.This Security Guard Course Level 3 course has been crafted to take an in-depth look at key security planning and emergency response practices. It will cover emergency preparations, the responsibilities of the security guard, workplace bullying and harassment, the art of effective conflict resolution, how to develop an effective security plan, and more. Take this opportunity to stand out to prospective employers and boost your earning potential in any security management role. How will I get my certificate? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is this course for? There is no experience or previous qualifications required for enrolment on this Security Guard Course Level 3. It is available to all students, of all academic backgrounds. Requirements Our Security Guard Course Level 3 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 10 lectures • 04:01:00 total length •Definition and Importance of Security: 00:16:00 •Career Prospect of Security Guard in the UK: 00:11:00 •Security Risk Analysis and Risk Reduction: 00:25:00 •Physical and Information Security Protection: 00:36:00 •Response to Immediate Crisis: 00:26:00 •The Use of Technology for Managing Security: 00:25:00 •General Patrol Tactics and Techniques: 00:25:00 •Public Relations and Traffic Control: 00:21:00 •Violence in the Workplace: 00:27:00 •Laws and Regulations: 00:29:00

Overview Learn how to build road safety strategies by enrolling in our exclusively designed Transport Manager Complete Training Level 4 course.This course contains all the knowledge and information you need to plan and implement traffic management plans, providing you with the skills and attributes needed to succeed in the role.This course will teach you everything you need to know about transport infrastructure. After successful completion, you will have strongly developed skills to work for an operator to ensure it's vehicles are street-legal, and that all drivers comply with the traffic and driver hours rule. You will have the knowledge to increase performance, reduce operational cost and make safer highways. Pave your way towards a career in a reputed organisation by gaining an industry-recongised qualification. How will I get my certificate? At the end of the course there will be an online MCQ test which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is this course for? There is no experience or previous qualifications required for enrolment on this Transport Manager Complete Training Level 4. It is available to all students, of all academic backgrounds. Requirements Our Transport Manager Complete Training Level 4 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G.There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 4 sections • 18 lectures • 06:50:00 total length •Module 01: An Introduction to Successful Transport Management: 00:20:00 •Module 02: The UK's Travel Infrastructure - Road and Rail: 00:10:00 •Module 03: Road Freight and Transport Management: 00:30:00 •Module 04: Passenger Road Transport and its Management: 00:30:00 •Module 05: Rail and Transport Management: 00:15:00 •Module 06: Transport Management for Ports and Inland Waters: 00:15:00 •Module 07: Transport Management for Airlines: 00:10:00 •Module 08: Trends, Challenges and Best Practice in Transport Management: 00:10:00 •Module 09: Transport Management and Health and Safety: 00:10:00 •ECC TM EWM Shipment Integrated Scenario: 00:30:00 •SAP Transportation Domestic Scenario: 00:22:00 •SAP Transportation Management (TM) Integrated Scenario: 00:15:00 •TM Overview + End to End Process Flow: 00:43:00 •SAP TM Uncontrolled Shipment Scenario: 00:28:00 •SAP TM - Air Way bill ID Generation: 00:26:00 •Effective SAP TM for perfect order fulfillment!: 00:56:00 •Mock Exam - Transport Manager Complete Training Level 4: 00:20:00 •Final Exam - Transport Manager Complete Training Level 4: 00:20:00

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Description Register on the Deep Learning & Neural Networks Python - Keras today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The Deep Learning & Neural Networks Python - Keras course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content 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 - Data Preparation - Standardization 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 Handwritten Digit Recognition Dataset 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