2978 Software Development courses in Kempston delivered Online

Course Overview Acquiring an expert hand in JavaScript can be massive support for climbing the career ladder. The JavaScript Data Structures Foundation Course is here to improve your Java skills. In the course, you will learn the essentials of JavaScript data structure and add one more valuable skill set to your list. The JavaScript Data Structures Foundation Course will teach you the fundamentals of JavaScript concepts. There will be extensive lessons on how to list and stack data structures. You will become skilled in implementing content. The modules will cover detailed information about setting data structure and the skills to implement different set features. You will become an expert in creating unique sets. In this step by step process, you will achieve the expertise to build a solid foundation in this subject.  This JavaScript Data Structures Foundation Course will provide you with theoretical knowledge and practical skills on JavaScript data structure. Enroll the course and boost your career in the relevant sector. Learning Outcomes Learn about the essential JavaScript concepts Comprehend the skills to list and stack data structures Understand the process of implementing contents and clear features Enrich your knowledge of queue data structure Identify the challenges and gain the skills to overcome them Know the procedure of creating a unique set Who is this course for? Web Developers, programmers or anyone interested to build their skills in this area. 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. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path  The JavaScript Data Structures Foundation Course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Programmer Web Developer Introduction Welcome to the Course 00:03:00 Essential Concepts Essential Concepts 00:02:00 Constructor Function 00:09:00 Protoype 00:04:00 Class 00:04:00 List Data Structure List Data Structure 00:01:00 Creating Class For List Data Structure 00:03:00 Implementing Add And Remove Feature 00:09:00 Working On Find And Remove Feature 00:08:00 Creating InsertAfter Feature 00:05:00 Implementing Contains And Clear Feature 00:04:00 Challenge - Work On Traverse List Features 00:03:00 Solution - Implementing List Traverse Features 00:08:00 Challenge - Work On DisplayElementNameOnPostion Features 00:01:00 Solution - Implementing DisplayElementNameOnPostion Features 00:06:00 Stack Data Structure Stack Data Structure 00:03:00 Using Object To Create Stack Class 00:04:00 Implementing Push and Pop Feature 00:09:00 Working with Peek and Clear Feature 00:04:00 Challenge - Extend Stack Class Feature 00:01:00 Solution - Extending Stack Class Feature 00:03:00 Challenge - Convert Stack Class From Object To Array Class 00:01:00 Solution - Converting Stack Class From Object To Array Class 00:05:00 Queue Data Structure Queue Data Structure 00:03:00 Using Object To Create Queue Class 00:04:00 Implementing Enqueue Feature 00:03:00 Implementing Tricky Dequeue Feature 00:09:00 Working On PeeK Size and Clear Features 00:03:00 Extending Features With Two Extra Methods 00:06:00 Challenge Convert Queue Class From Object To Array Class 00:01:00 Solution Converting Queue Class From Object To Array Class 00:04:00 Set Data Structure Set Data Structure 00:02:00 Creating Set Class 00:03:00 Implementing Add And Remove Feature 00:09:00 Working On Contains, Show And Size Method 00:05:00 Creating Unique Set 00:09:00 Adding Mutual Members Feature 00:04:00 Challenge Implement Difference Set Feature 00:02:00 Solution Implementing Difference Set Feature 00:03:00 Final Thought Final Thought 00:01:00 Resources Resources - JavaScript Data Structures Foundation Course 00:00:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Overview This comprehensive course on Google Data Studio: Data Analytics will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Google Data Studio: Data Analytics 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? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Google Data Studio: Data Analytics. It is available to all students, of all academic backgrounds. Requirements Our Google Data Studio: Data Analytics 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 4 sections • 17 lectures • 02:32:00 total length •Course Overview: 00:01:00 •Format Data in Google Sheets: 00:08:00 •Sheet Functions 1: Query & Import Range: 00:07:00 •Sheets Function 2: Vlookup & Defined Range: 00:10:00 •Sheets Function 3: Cross Table Calculations: 00:09:00 •Connect Data to Google Data Studio: 00:04:00 •GDS Calculated Fields: 00:08:00 •GDS Theme Customization: 00:07:00 •GDS Page Layout Design: 00:17:00 •GDS Charts: Scorecards: 00:12:00 •GDS Charts: Time Series Graphs: 00:09:00 •GDS Blending and Joining Data Tables: 00:07:00 •GDS Charts: Bar, Donut, and Treemap: 00:17:00 •GDS Charts: Interactive Filters: 00:08:00 •GDS Project Page Completion: 00:17:00 •GDS Client Page Completion: 00:11:00 •Additional Resources - Google Data Studio: Data Analytics: 00:00:00

Overview This comprehensive course on Statistical Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Statistical Analysis 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? At the end of the course there will be an online written 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 Statistical Analysis. It is available to all students, of all academic backgrounds. Requirements Our Statistical Analysis 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 14 sections • 16 lectures • 06:28:00 total length •The Realm Of Statistics: 00:26:00 •Basic Statistical Terms: 00:41:00 •The Center of the Data: 00:07:00 •Data Variability: 00:15:00 •Binomial and Normal Distributions: 00:14:00 •Binomial Probabilities Table: 00:14:00 •Z-Table: 00:04:00 •Introduction to Probability: 00:35:00 •Estimates and Intervals: 00:34:00 •Hypothesis Testing: 00:31:00 •Regression Analysis: 00:11:00 •Algorithms, Analytics and Prediction: 00:47:00 •Learning From Experience: The Bayesian Way: 00:31:00 •Doing Statistics: The Wrong Way: 00:37:00 •How We Can Do Statistics Better: 00:41:00 •Assignment - Statistics Essentials: 00:00:00

Course Overview: According to the World Economic Forum, data analysts will be among the most in-demand professions by 2025. This Basic Google Data Studio course takes you on an enlightening journey, illuminating the intricate world of Google Data Studio from the ground up.The Basic Google Data Studio course is your stepping stone into data visualisation, geo-visualization, and in-depth socio-economic analysis. With four comprehensive modules, this curriculum is crafted to impart the foundational principles and techniques of Google Data Studio, ensuring learners possess the proficiency to translate raw data into meaningful insights.Enrol Today and Start Learning! Key Features of the Course: The Basic Google Data Studio course boasts an array of appealing features, including a CPD certificate upon completion, marking your journey into mastering Google Data Studio. 24/7 Learning Assistance ensures you can absorb the course material at your own pace, whenever it suits you best. Expect exciting learning materials that make mastering data visualisation a stimulating and enjoyable endeavour. Who is This Course For? This Basic Google Data Studio course is designed for anyone inclined towards data and interested in visual storytelling. Whether you're a business owner looking to make informed decisions, a student eyeing a future in data analysis, or a data enthusiast, this course could be the perfect fit. What You Will Learn: Introduction to Google Data Studio and its features. Navigation and interface overview of Google Data Studio. Creating reports using different data sources. Converting data into visually appealing graphs and charts. Exploring geographic data visualisation techniques. Uncovering hidden geographic trends through data visualisation. Applying the learned skills to real-world socio-economic case studies. Why Enrol in This Course: This Basic Google Data Studio course consistently receives top reviews from its participants. Recently updated with the latest trends and practices in data visualisation, this course ensures you stay on top of industry shifts. By enrolling in this course, you will develop indispensable skills in data analysis and visual storytelling. Requirements: This course requires a fundamental understanding of data analysis concepts. Internet access is required to practise Google Data Studio and access course materials. Career Path: Upon completing this Basic Google Data Studio course, you can look forward to opportunities in various data-focused professions. Such as Data Analyst Business Intelligence Developer Marketing Analyst SEO Specialist Data Scientist Data Visualisation Specialist Report Analyst In the UK, these roles offer attractive salary packages ranging from £25,000 for entry-level positions to over £60,000+ for more advanced roles. Certification: Upon successful completion of the Basic Google Data Studio course, you will be awarded a CPD certificate as proof of your proficiency in Google Data Studio. Course Curriculum 1 sections • 4 lectures • 02:41:00 total length •Module 01: Introduction to GDS: 00:36:00 •Module 02: Data Visualization: 01:29:00 •Module 03: Geo-visualization: 00:16:00 •Module 04: A Socio-Economic Case Study: 00:20:00

Duration 2 Days 12 CPD hours This course is intended for This class is intended for network engineers and network admins that are either using Google Cloud Platform or are planning to do so. The class is also for individuals that want to be exposed to software-defined networking solutions in the cloud. Overview Configure Google VPC networks, subnets, and routers Control administrative access to VPC objects Control network access to endpoints in VPCsInterconnect networks among GCP projects Interconnect networks among GCP VPC networks and on-premises or other-cloud networks Choose among GCP load balancer and proxy options and configure them Use Cloud CDN to reduce latency and save money Optimize network spend using Network TiersConfigure Cloud NAT or Private Google Access to provide instances without public IP addresses access to other services Deploy networks declaratively using Cloud Deployment Manager or Terraform Design networks to meet common customer requirements Configure monitoring and logging to troubleshoot networks problems Learn about the broad variety of networking options on Google Cloud. This course uses lectures, demos, and hands-on labs to help you explore and deploy Google Cloud networking technologies, including Virtual Private Cloud (VPC) networks, subnets, and firewalls; interconnection among networks; load balancing; Cloud DNS; Cloud CDN; and Cloud NAT. You'll also learn about common network design patterns and automated deployment using Cloud Deployment Manager or Terraform. Google Cloud VPC Networking Fundamentals Recall that networks belong to projects. Explain the differences among default, auto, and custom networks. Create networks and subnets. Explain how IPv4 addresses are assigned to Compute Engine instances. Publish domain names using Google Cloud DNS. Create Compute Engine instances with IP aliases. Create Compute Engine instances with multiple virtual network. Controlling Access to VPC Networks Outline how IAM policies affect VPC networks. Control access to network resources using service accounts. Control access to Compute Engine instances with tag-based firewall rules. Sharing Networks across Projects Outline the overall workflow for configuring Shared VPC. Differentiate between the IAM roles that allow network resources to be managed. Configure peering between unrelated VPC Networks. Recall when to use Shared VPC and when to use VPC Network Peering. Load Balancing Recall the various load balancing services. Configure Layer 7 HTTP(S) load balancing. Whitelist and blacklist IP traffic with Cloud Armor. Cache content with Cloud CDN. Explain Layer 4 TCP or SSL proxy load balancing. Explain regional network load balancing. Configure internal load balancing. Recall the choices for enabling IPv6 Internet connectivity for Google Cloud load balancers. Determine which Google Cloud load balancer to use when. Hybrid Connectivity Recall the Google Cloud interconnect and peering services available to connect your infrastructure to Google Cloud. Explain Dedicated Interconnect and Partner Interconnect. Describe the workflow for configuring a Dedicated Interconnect. Build a connection over a VPN with Cloud Router. Determine which Google Cloud interconnect service to use when. Explain Direct Peering and Partner Peering. Determine which Google Cloud peering service to use when. Networking Pricing and Billing Recognize how networking features are charged for. Use Network Service Tiers to optimize spend. Determine which Network Service Tier to use when. Recall that labels can be used to understand networking spend. Network Design and Deployment Explain common network design patterns. Configure Private Google Access to allow access to certain Google Cloud services from VM instances with only internal IP addresses. Configure Cloud NAT to provide your instances without public IP addresses access to the internet. Automate the deployment of networks using Deployment Manager or Terraform. Launch networking solutions using Cloud Marketplace. Network Monitoring and Troubleshooting Configure uptime checks, alerting policies and charts for your network services. Use VPC Flow Logs to log and analyze network traffic behavior.

Duration 3 Days 18 CPD hours Overview In this course you?ll learn how to: Containerize and deploy a new Python script Configure the deployment with ConfigMaps, Secrets and SecurityContexts Understand multi-container pod design Configure probes for pod health Update and roll back an application Implement services and NetworkPolicies Use PersistentVolumeClaims for state persistence And more In this vendor agnostic course, you will use Python to build, monitor and troubleshoot scalable applications in Kubernetes. Introduction Objectives Who You Are The Linux Foundation Linux Foundation Training Preparing Your System Course Registration Labs Kubernetes Architecture What Is Kubernetes? Components of Kubernetes Challenges The Borg Heritage Kubernetes Architecture Terminology Master Node Minion (Worker) Nodes Pods Services Controllers Single IP per Pod Networking Setup CNI Network Configuration File Pod-to-Pod Communication Cloud Native Computing Foundation Resource Recommendations Labs Build Container Options Containerizing an Application Hosting a Local Repository Creating a Deployment Running Commands in a Container Multi-Container Pod readinessProbe livenessProbe Testing Labs Design Traditional Applications: Considerations Decoupled Resources Transience Flexible Framework Managing Resource Usage Multi-Container Pods Sidecar Container Adapter Container Ambassador Points to Ponder Labs Deployment Configuration Volumes Overview Introducing Volumes Volume Spec Volume Types Shared Volume Example Persistent Volumes and Claims Persistent Volume Persistent Volume Claim Dynamic Provisioning Secrets Using Secrets via Environment Variables Mounting Secrets as Volumes Portable Data with ConfigMaps Using ConfigMaps Deployment Configuration Status Scaling and Rolling Updates Deployment Rollbacks Jobs Labs Security Security Overview Accessing the API Authentication Authorization ABAC RBAC RBAC Process Overview Admission Controller Security Contexts Pod Security Policies Network Security Policies Network Security Policy Example Default Policy Example Labs Exposing Applications Service Types Services Diagram Service Update Pattern Accessing an Application with a Service Service without a Selector ClusterIP NodePort LoadBalancer ExternalName Ingress Resource Ingress Controller Labs Troubleshooting Troubleshotting Overview Basic Troubleshooting Steps Ongoing (Constant) Change Basic Troubleshooting Flow: Pods Basic Troubleshooting Flow: Node and Security Basic Troubleshooting Flow: Agents Monitoring Logging Tools Monitoring Applications System and Agent Logs Conformance Testing More Resource Labs Additional course details: Nexus Humans Kubernetes for App Developers 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 Kubernetes for App Developers 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 1 Days 6 CPD hours This course is intended for The primary audience for this course is database developers who plan to migrate their MySQL or Postgres DB workloads to Azure SQL DB. The secondary audience for this course is MySQL/Postgres administrators to raise awareness of the features and benefits of Azure SQL DB. Overview At the end of this course, the students will have learned: Migrate on-premises MySQL to Azure SQL DB for MySQL Migrate on-premises PostgreSQL to Azure SQL DB for PostgreSQL This course will enable the students to understand Azure SQL Database, and educate the students on what is required to migrate MySQL and PostgreSQL workloads to Azure SQL Database. Migrate to Azure SQL DB for MySQL & PostgreSQL OSS databases overview Common OSS database workloads Customer challenges in migration Migrate on-premises MySQL to Azure SQL DB for MySQL Configure and Manage Azure SQL DB for MySQL Migrate on-premises MySQL to SQL DB for MySQL Application Migration Post-migration considerations Migrate on-premises PostgreSQL to Azure SQL DB for PostgreSQL Configure and Manage Azure SQL DB for PostgreSQL Migrate on-premises MySQL to SQL DB for PostgreSQL Application Migration Post-migration considerations

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

Unlock the creative potential of your Android Studio with our Create Android Studio Gallery App course. Are you passionate about mobile app development and eager to create a stunning gallery application? This course provides a step-by-step guide to designing a gallery app right from the start. Whether you're a beginner or a developer looking to expand your skills, you'll dive into the essentials of Android Studio. Learn to list and display images with a user-friendly interface, add features to delete, rename, and share images, and display image information. Additionally, you'll gain valuable insights into image resolution and even implement a feature to rotate images. Let your imagination run wild as you master the art of creating a captivating Android gallery app. Learning Outcomes Set up an Android Studio Gallery App. List and display images with a user-friendly interface. Add features to delete, rename, and share images. Display image information, including resolution. Implement a feature to rotate images. Why choose this Create Android Studio Gallery App course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Create Android Studio Gallery App course for? Aspiring app developers interested in Android. Students and beginners looking to enhance their app development skills. Mobile app enthusiasts keen to create their gallery app. Developers who want to expand their Android Studio knowledge. Anyone excited to dive into mobile app development. Career path Android App Developer: £20,000 - £60,000 Mobile Application Developer: £25,000 - £70,000 Software Engineer: £25,000 - £60,000 Java Developer: £25,000 - £60,000 UI/UX Designer: £22,000 - £50,000 Quality Assurance (QA) Tester: £18,000 - £40,000 Prerequisites This Create Android Studio Gallery App does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Create Android Studio Gallery App 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Build an Android Studio Gallery App Module 01: Android Studio Gallery App Setup and General Explanation 00:23:00 Module 02: Listing and Displaying Images to the Ui 00:23:00 Module 03: Displaying Image Name and Adding New Ui Elements 00:24:00 Module 04: Adding Feature to Delete and Rename Images 00:28:00 Module 05: Adding Feature to Share Image and Display Image Information 00:29:00 Module 06: Getting Image Resolution and Setting up Feature to Rotate Image 00:36:00 Module 07: Fixing Rotation Feature, Bug Fixes and General Improvements 00:22:00 Assignment Assignment - Create Android Studio Gallery App 00:00:00

Dive into the world of numbers and patterns with our 'Statistical Analysis Course,' where data tells stories and predictions shape the future. In the first module, you're introduced to the vast landscape of statistics, a toolset essential for deciphering the tales hidden within data. As you progress, familiarise yourself with the fundamental statistical terminology, paving the way for a deeper grasp of how data clusters around central values. The journey through this course is a blend of theory and application, from mastering the intricacies of data variability to the advanced realms of regression analysis and predictive algorithms. Learning Outcomes Gain a solid understanding of statistics and its significance in various fields. Learn to describe and utilise basic statistical terminology and methods. Comprehend and calculate measures of central tendency and data dispersion. Develop skills in probability, distribution analysis, and statistical inference. Apply statistical methods correctly and appreciate the Bayesian approach for learning from data. Why choose this Statistical Analysis Course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Statistical Analysis Course Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Statistical Analysis Course for? Aspiring data analysts seeking a foundation in statistics. Business professionals who require analytical skills for data-driven decision-making. Students of the social sciences, economics, or any field involving data interpretation. Researchers needing a robust grasp of statistical analysis methods. Anyone interested in understanding how to utilise data for predictions and analytics. Career path Data Analyst - £25,000 to £40,000 Market Research Analyst - £23,000 to £35,000 Quantitative Analyst - £35,000 to £70,000 Statistical Researcher - £27,000 to £45,000 Business Intelligence Analyst - £30,000 to £55,000 Econometrician - £30,000 to £60,000 Prerequisites This Statistical Analysis Course does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Statistical Analysis Course 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Module 01: The Realm of Statistics The Realm Of Statistics 00:26:00 Module 02: Basic Statistical Terms Basic Statistical Terms 00:41:00 Module 03: The Center of the Data The Center of the Data 00:03:00 Module 04: Data Variability Data Variability 00:15:00 Module 05: Binomial and Normal Distributions Binomial and Normal Distributions 00:14:00 Binomial Probabilities Table 00:00:00 Z-Table 00:00:00 Module 06: Introduction to Probability Introduction to Probability 00:35:00 Module 07: Estimates and Intervals Estimates and Intervals 00:34:00 Module 08: Hypothesis Testing Hypothesis Testing 00:31:00 Module 09: Regression Analysis Regression Analysis 00:11:00 Module 10: Algorithms, Analytics and Predictions Algorithms, Analytics and Prediction 00:47:00 Module 11: Learning From Experience: The Bayesian Way Learning From Experience: The Bayesian Way 00:31:00 Module 12: Doing Statistics: The Wrong Way Doing Statistics: The Wrong Way 00:37:00 Module 13: How We Can Do Statistics Better How We Can Do Statistics Better 00:41:00 Assignment Assignment - Statistical Analysis Course 00:00:00