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Unlock your true potential with the Reclaiming Your Masculine and Feminine Toolkit! This comprehensive resource offers transformative exercises, including daily self-awareness prompts, boundary-building tools, emotional regulation techniques, and breathwork practices. Balance your energies, enhance self-awareness, and align with your purpose. Perfect for anyone looking to deepen their personal growth journey. Embrace your power today!
NodeJS allows you to build complex and powerful applications quickly and easily, writing JavaScript code. It also allows you to use JavaScript for web applications with flexibility for a wide range of different purposes. Learn about MongoDB as a database and how to build it as well as Express as a framework to build web apps on top of Node.js.
Stepping into the world of administration requires more than just a tidy desk and a steady hand on the keyboard. This Admin Support Assistant Diploma has been thoughtfully arranged to help learners understand the structure, flow, and expectations of modern office support roles. From managing schedules to handling internal communications with finesse, the course offers well-organised knowledge ideal for building confidence in remote or digital work environments. Whether you're looking to sharpen your organisational toolkit or simply want to gain insight into how administrative operations run behind the scenes, this CPD-accredited course provides the know-how in a flexible, online setting. Learn at your pace, on your schedule, with no unnecessary fluff—just solid, reliable information that makes sense and delivers value. Simple, smart, and structured to fit neatly into your routine. Additionally, you get: Free exam Free assessment Free certificate Free Tutor support Hurry up and enrol, before the offer expires! Course Curriculum: Module 01: Introduction to Admin Support Assistant Module 02: Business Telephone Skills Module 03: Representing Your Boss and Company Module 04: Business Etiquette Module 05: Mail Services and Shipping Module 06: Travel Arrangements Module 07: Organising Meeting and Conferences Module 08: Diary Management and Note taking Module 09: Time Management Module 10: Record Keeping and Filing Systems Module 11: Business Writing Skills Module 12: Organisational Skills Module 13: Communication Skills Module 14: Customer Service Module 15: Effective Planning and Scheduling Module 16: Invoicing/Petty Cash Course Assessment You will immediately be given access to a specifically crafted MCQ test upon completing an online module. For each test, the pass mark will be set to 60%. CPD 10 CPD hours / points Accredited by The CPD Certification Service Who is this course for? The Admin Support Assistant Diploma - CPD Accredited training is ideal for highly motivated individuals or teams who want to enhance their skills and efficiently skilled employees. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Learn the essential skills and knowledge you need to excel in your professional life with the help & guidance from our Admin Support Assistant Diploma - CPD Accredited training.
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
BGP training course description A study of BGP for non engineers working in the Internet. The course starts with a review of the basics of routers and routing tables and then moves on to a simple overview of how BPG works with a focus on BGP metrics influencing the route traffic takes through the Internet. Hands on with routers follow the major sessions to reinforce the theory. Note these hands on sessions are more demonstrations by the trainer but some can be followed along and done by delegates (e.g. looking at Internet routing tables.) What will you learn Explain how routing tables influence Internet traffic. Describe how BGP works. Explain the methods BGP can use to influence Internet traffic. Use traceroute, peeringdb, route collectors and looking glasses to analyse traffic flows. Explain the difference between bi lateral and multilateral peering using a route server. BGP training course details Who will benefit: Non technical staff wishing to know more about BGP. Prerequisites: None. Duration 1 day BGP training course contents Networks, routers and routing tables What is a network, what is a router, routing tables, static routes, routing protocols. When an ISP uses static routes and when they use BGP. IP addresses, subnet masks, groups of IP addresses. IPv6. Hands on: Showing a full routing table. Seeing traceroute being used. Basic BGP What's BGP? BGP versus other routing protocols, ASs, AS numbers. RIPE database, peeringdb. Hands on: Finding AS numbers. Showing simple BGP configuration and routing tables in an EVENG example. How BGP works Simple walk through of BGP incremental updates and how routes change when links go down. Hands on: Showing packets and route changes when a link goes down/comes up. BGP path selection Transit, peering, routing policy and route filtering. Longest matching rule in routing tables, route selection order, Local preference, AS prepend, MEDs. Hands on: Seeing BGP influencing traffic. Looking at peering policies in RIPE and peeringdb. Route servers What are route servers? LINX route servers, route server policy control and communities, What are route collectors, Looking glasses. Hands on: Seeing the LINX route server details in peeringdb, using a looking glass.
3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support
3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support
3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | Plus 10 CPD Courses | Lifetime Access