3054 Software Development courses in Kempston delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Duration 3 Days 18 CPD hours This course is intended for Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform Overview This course teaches participants the following skills: Use best practices for application development. Choose the appropriate data storage option for application data. Implement federated identity management. Develop loosely coupled application components or microservices. Integrate application components and data sources. Debug, trace, and monitor applications. Perform repeatable deployments with containers and deployment services. Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment. Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications. Best Practices for Application Development Code and environment management. Design and development of secure, scalable, reliable, loosely coupled application components and microservices. Continuous integration and delivery. Re-architecting applications for the cloud. Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK. Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials. Overview of Data Storage Options Overview of options to store application data. Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner. Best Practices for Using Cloud Firestore Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling. Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow. Lab: Store application data in Cloud Datastore. Performing Operations on Cloud Storage Operations that can be performed on buckets and objects. Consistency model. Error handling. Best Practices for Using Cloud Storage Naming buckets for static websites and other uses. Naming objects (from an access distribution perspective). Performance considerations. Setting up and debugging a CORS configuration on a bucket. Lab: Store files in Cloud Storage. Handling Authentication and Authorization Cloud Identity and Access Management (IAM) roles and service accounts. User authentication by using Firebase Authentication. User authentication and authorization by using Cloud Identity-Aware Proxy. Lab: Authenticate users by using Firebase Authentication. Using Pub/Sub to Integrate Components of Your Application Topics, publishers, and subscribers. Pull and push subscriptions. Use cases for Cloud Pub/Sub. Lab: Develop a backend service to process messages in a message queue. Adding Intelligence to Your Application Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API. Using Cloud Functions for Event-Driven Processing Key concepts such as triggers, background functions, HTTP functions. Use cases. Developing and deploying functions. Logging, error reporting, and monitoring. Managing APIs with Cloud Endpoints Open API deployment configuration. Lab: Deploy an API for your application. Deploying Applications Creating and storing container images. Repeatable deployments with deployment configuration and templates. Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments. Execution Environments for Your Application Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run. Lab: Deploying your application on App Engine flexible environment. Debugging, Monitoring, and Tuning Performance Application Performance Management Tools. Stackdriver Debugger. Stackdriver Error Reporting. Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting. Stackdriver Logging. Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance.

Duration 5 Days 30 CPD hours This course is intended for Anyone who plans to work with Kubernetes at any level or tier of involvement Any company or individual who wants to advance their knowledge of the cloud environment Application Developers Operations Developers IT Directors/Managers Overview All topics required by the CKAD exam, including: Deploy applications to a Kubernetes cluster Pods, ReplicaSets, Deployments, DaemonSets Self-healing and observable applications Multi-container Pod Design Application configuration via Configmaps, Secrets Administrate cluster use for your team A systematic understanding of Kubernetes architecture Troubleshooting and debugging tools Kubernetes networking and services Kubernetes is a Cloud Orchestration Platform providing reliability, replication, and stability while maximizing resource utilization for applications and services. By the conclusion of this hands-on training, you will go back to work with all necessary commands and practical skills to empower your team to succeed, as well as gain knowledge of important concepts like Kubernetes architecture and container orchestration. We prioritize covering all objectives and concepts necessary for passing the Certified Kubernetes Application Developer (CKAD) exam. You will command and configure a high availability Kubernetes environment (and later, build your own!) capable of demonstrating all ?K8s'' features discussed and demonstrated in this course. Your week of intensive, hands-on training will conclude with a mock CKAD exam that matches the real thing. Kubernetes Architecture Components Understand API deprecations Containers Define, build and modify container images Pods Master Services Node Services K8s Services YAML Essentials Creating a K8s Cluster kubectl Commands Kubernetes Resources Kubernetes Namespace Kubernetes Contexts Pods What is a Pod? Create, List, Delete Pods How to Access Running Pods Kubernetes Resources Managing Cloud Resource Consumption Multi-Container Pod Design Security Contexts Init Containers Understand multi-container Pod design patterns (e.g. sidecar, init and others) Pod Wellness Tracking Networking Packet Forwarding ClusterIP and NodePort Services Provide and troubleshoot access to applications via services Ingress Controllers Use Ingress rules to expose applications NetworkPolicy resource Demonstrate basic understanding of NetworkPolicies Network Plugins Defining the Service Mesh Service mesh configuration examples ReplicaSets Services ReplicaSet Function Deploying ReplicaSets Deployments Deployment Object Updating/Rolling Back Deployments Understand Deployments and how to perform rolling updates Deployment Strategies Use Kubernetes primitives to implement common deployment strategies (e.g. blue/green or canary) Scaling ReplicaSets Autoscaling Labels and Annotations Labels Annotations Node Taints and Tolerations Jobs The K8s Job and CronJob Understand Jobs and CronJobs Immediate vs. scheduled internal use Application Configuration Understanding and defining resource requirements, limits and quotas Config Maps Create & consume Secrets Patching Custom Resource Definition Discover and use resources that extend Kubernetes (CRD) Managing ConfigMaps and Secrets as Volumes Storage Static and dynamic persistent volumes via StorageClass K8s volume configuration Utilize persistent and ephemeral volumes Adding persistent storage to containers via persistent volume claims Introduction to Helm Helm Introduction Charts Use the Helm package manager to deploy existing packages Application Security Understand authentication, authorization and admission control Understand ServiceAccounts Understand SecurityContexts Application Observability and Maintenance Use provided tools to monitor Kubernetes applications How to Troubleshoot Kubernetes Basic and Advanced Logging Techniques Utilize container logs Accessing containers with Port-Forward Debugging in Kubernetes Hands on Labs: Define, build and modify container images Deploy Kubernetes using Ansible Isolating Resources with Kubernetes Namespaces Cluster Access with Kubernetes Context Listing Resources with kubectl get Examining Resources with kubectl describe Create and Configure Basic Pods Debugging via kubectl port-forward Imperative vs. Declarative Resource Creation Performing Commands inside a Pod Understanding Labels and Selectors Insert an Annotation Create and Configure a ReplicaSet Writing a Deployment Manifest Perform rolling updates and rollbacks with Deployments Horizontal Scaling with kubectl scale Implement probes and health checks Understanding and defining resource requirements, limits and quotas Understand Jobs and CronJobs Best Practices for Container Customization Persistent Configuration with ConfigMaps Create and Consume Secrets Understand the Init container multi-container Pod design pattern Using PersistentVolumeClaims for Storage Dynamically Provision PersistentVolumes with NFS Deploy a NetworkPolicy Provide and troubleshoot access to applications via services Use Ingress rules to expose applications Understand the Sidecar multi-container Pod design pattern Setting up a single tier service mesh Tainted Nodes and Tolerations Use the Helm package manager to deploy existing packages A Completed Project Install Jenkins Using Helm and Run a Demo Job Custom Resource Definitions (CRDs) Patching Understanding Security Contexts for Cluster Access Control Utilize container logs Advanced Logging Techniques Troubleshooting Calicoctl Deploy a Kubernetes Cluster using Kubeadm Monitoring Applications in Kubernetes Resource-Based Autoscaling Create ServiceAccounts for use with the Kubernetes Dashboard Saving Your Progress With GitHub CKAD Practice Drill Alta Kubernetes Course Specific Updates Sourcing Secrets from HashiCorp Vault Example CKAD Test Questions

Duration 2 Days 12 CPD hours This course is intended for The audience for this course is data professionals and data architects who want to learn about migrating data platform technologies that exist on Microsoft Azure and how existing SQL based workloads can be migrated and modernized. The secondary audience for this course is individuals who manage data platforms or develop applications that deliver content from the existing data platform technologies. Overview Understand Data Platform Modernization Choose the right tools for Data Migration Migrate SQL Workloads to Azure Virtual Machines Migrate SQL Workloads to Azure SQL Databases Migrate SQL Workloads to Azure SQL Database Managed Instance In this course, the students will explore the objectives of data platform modernization and how it is suitable for given business requirements. They will also explore each stage of the data platform modernization process and define what tasks are involved at each stage, such as the assessment and planning phase. Students will also learn the available migration tools and how they are suitable for each stage of the data migration process. The student will learn how to migrate to the three target platforms for SQL based workloads; Azure Virtual Machines, Azure SQL Databases and Azure SQL Database Managed Instances. The student will learn the benefits and limitations of each target platform and how they can be used to fulfil both business and technical requirements for modern SQL workloads. The student will explore the changes that may need to be made to existing SQL based applications, so that they can make best use of modern data platforms in Azure. Introducing Data Platform Modernization Understand Data Platform Modernization Understanding the stages of migration Data Migration Paths Choose the right tools for Data Migration Discover the Database Migration Guide Build your data estate inventory using Map Toolkit Identify Migration candidates using Data Migration Assistant Evaluate a Data workload using Database Experimentation Assistant Data Migration using Azure Database Migration Service Migrate non-SQL Server workloads to Azure using SQL Migration Assistant Migrating SQL Workloads to Azure Virtual Machines Considerations of SQL Server to Azure VM Migrations SQL Workloads to Azure VM Migration Options Implementing High Availability and Disaster Recovery Scenarios Migrate SQL Workloads to Azure SQL Databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL DB offline Migrate SQL Server to Azure SQL DB online Load and Move data to Azure SQL Database Migrate SQL Workloads to Azure SQL Database Managed Instance Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed instance Load and Move data to SQL Database Managed instance Application Configuration and Optimization

Overview This comprehensive course on C++ Complete Coding Course will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This C++ Complete Coding 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? 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 C++ Complete Coding Course. It is available to all students, of all academic backgrounds. Requirements Our C++ Complete Coding 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 14 sections • 79 lectures • 05:33:00 total length •Introduction: 00:04:00 •What Is C++?: 00:03:00 •Setting up A Project: 00:07:00 •Console Out: 00:04:00 •Data Types: 00:03:00 •Variables: 00:04:00 •Console In: 00:03:00 •Strings: 00:04:00 •Constants: 00:05:00 •Assignment Operator: 00:03:00 •Arithmetic Operators: 00:04:00 •Compound Assignment Operator: 00:03:00 •Increment & Decrement Operators: 00:04:00 •Relation & Comparison Operators: 00:06:00 •Logical Operators: 00:07:00 •Conditional Ternary Operator: 00:04:00 •Comma Operator: 00:03:00 •Type Casting Operator: 00:02:00 •Bitwise Operators: 00:12:00 •Size of Operator: 00:03:00 •Operator Precedence: 00:05:00 •String Streams: 00:04:00 •Conditional Statements: 00:07:00 •For Loop: 00:04:00 •While Loop: 00:03:00 •Do While Loop: 00:04:00 •Range-Based For Loop: 00:03:00 •GoTo Statement: 00:04:00 •Switch Statement: 00:05:00 •Functions: 00:03:00 •Function Return Statement: 00:04:00 •Function Arguments Passed By Value: 00:05:00 •Function Arguments Passed By Reference: 00:05:00 •Function Parameter Default Values: 00:03:00 •Overloaded Functions: 00:04:00 •Function Templates: 00:04:00 •Namespaces: 00:06:00 •Arrays: 00:03:00 •Multidimensional Arrays: 00:03:00 •References: 00:02:00 •Pointers: 00:04:00 •Delete Operator: 00:02:00 •Struct: 00:04:00 •Type Aliasing: 00:03:00 •Unions: 00:04:00 •Enumerators: 00:04:00 •Introduction to Classes: 00:05:00 •Class Access: 00:04:00 •Class Constructor: 00:05:00 •Class Pointers: 00:04:00 •Overloading Operators: 00:06:00 •This Keyword: 00:04:00 •Constant Objects: 00:03:00 •Getters and Setters: 00:05:00 •Static Variables: 00:04:00 •Static Functions: 00:06:00 •Template Classes: 00:05:00 •Class Destructor: 00:04:00 •Class Copy Constructor: 00:03:00 •Friend Function: 00:06:00 •Friend Class: 00:06:00 •Class Inheritance: 00:07:00 •Multiple Class Inheritance: 00:05:00 •Virtual Methods: 00:04:00 •Abstract Base Class: 00:03:00 •Error Handling: 00:04:00 •Preprocessor Macro Definitions: 00:04:00 •Preprocessor Conditional Directives: 00:05:00 •Preprocessor Line Directive: 00:04:00 •Preprocessor Error Directive: 00:03:00 •Preprocessor Source File Inclusion: 00:02:00 •Opening A File: 00:06:00 •Writing to a File: 00:04:00 •Commenting: 00:04:00 •Class Header and Implementation: 00:09:00 •Lists: 00:04:00 •Vectors: 00:05:00 •Resource - C++ Complete Coding Course: 00:00:00 •Assignment - C++ Complete Coding Course: 00:00:00

Overview This comprehensive course on C++ Development: The Complete Coding Guide will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This C++ Development: The Complete Coding Guide 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 C++ Development: The Complete Coding Guide. It is available to all students, of all academic backgrounds. Requirements Our C++ Development: The Complete Coding Guide 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 • 79 lectures • 05:35:00 total length •Introduction: 00:04:00 •What Is C++?: 00:03:00 •Setting up A Project: 00:07:00 •Console Out: 00:04:00 •Data Types: 00:03:00 •Variables: 00:04:00 •Console In: 00:03:00 •Strings: 00:04:00 •Constants: 00:05:00 •Assignment Operator: 00:03:00 •Arithmetic Operators: 00:04:00 •Compound Assignment Operator: 00:03:00 •Increment & Decrement Operators: 00:04:00 •Relation & Comparison Operators: 00:06:00 •Logical Operators: 00:07:00 •Conditional Ternary Operator: 00:04:00 •Comma Operator: 00:03:00 •Type Casting Operator: 00:02:00 •Bitwise Operators: 00:12:00 •Size of Operator: 00:03:00 •Operator Precedence: 00:05:00 •String Streams: 00:04:00 •Conditional Statements: 00:07:00 •For Loop: 00:04:00 •While Loop: 00:03:00 •Do While Loop: 00:04:00 •Range-Based For Loop: 00:03:00 •GoTo Statement: 00:04:00 •Switch Statement: 00:05:00 •Switch Statement: 00:05:00 •Functions: 00:03:00 •Function Return Statement: 00:04:00 •Function Arguments Passed By Value: 00:05:00 •Function Arguments Passed By Reference: 00:05:00 •Function Parameter Default Values: 00:03:00 •Overloaded Functions: 00:04:00 •Function Templates: 00:04:00 •Namespaces: 00:06:00 •Arrays: 00:03:00 •Multidimensional Arrays: 00:03:00 •References: 00:02:00 •Pointers: 00:04:00 •Delete Operator: 00:02:00 •Struct: 00:04:00 •Type Aliasing: 00:03:00 •Unions: 00:04:00 •Enumerators: 00:04:00 •Introduction to Classes: 00:05:00 •Class Access: 00:04:00 •Class Constructor: 00:05:00 •Class Pointers: 00:04:00 •Overloading Operators: 00:06:00 •This Keyword: 00:04:00 •Constant Objects: 00:03:00 •Getters and Setters: 00:05:00 •Static Variables: 00:04:00 •Static Functions: 00:06:00 •Template Classes: 00:05:00 •Class Destructor: 00:04:00 •Class Copy Constructor: 00:03:00 •Friend Function: 00:06:00 •Friend Class: 00:06:00 •Class Inheritance: 00:07:00 •Multiple Class Inheritance: 00:05:00 •Virtual Methods: 00:04:00 •Abstract Base Class: 00:03:00 •Error Handling: 00:04:00 •Preprocessor Macro Definitions: 00:04:00 •Preprocessor Conditional Directives: 00:05:00 •Preprocessor Line Directive: 00:04:00 •Preprocessor Source File Inclusion: 00:02:00 •Opening A File: 00:06:00 •Writing to a File: 00:04:00 •Commenting: 00:04:00 •Class Header and Implementation: 00:09:00 •Lists: 00:04:00 •Vectors: 00:05:00 •Resource: 00:00:00 •Assignment - C++ Development: The Complete Coding Guide: 00:00:00

Overview This comprehensive course on Android Studio Admob Integration: Start Showing Ads in Your Mobile App Today! will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Android Studio Admob Integration: Start Showing Ads in Your Mobile App Today! 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 Android Studio Admob Integration: Start Showing Ads in Your Mobile App Today!. It is available to all students, of all academic backgrounds. Requirements Our Android Studio Admob Integration: Start Showing Ads in Your Mobile App Today! 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 1 sections • 3 lectures • 00:50:00 total length •Module 01: Banner Ads Tutorial: 00:24:00 •Module 02: Interstitial Ads Tutorial: 00:16:00 •Module 03: Rewarded Video Ads Tutorial: 00:10:00

The Linux for Cloud and DevOps Engineers is all you need to advance your career in the relevant fields. Enrol now to discover everything you need to know about the Linux for Cloud and DevOps Engineers and the skills to improve your talents in this field and be confident in your knowledge bucket with One Education as your right hand! Meet the Accreditation CPD Quality Standards (CPD QS) accreditation assure the Linux for Cloud and DevOps Engineers course training and learning activities are relevant, reliable, and upto date. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Course Curriculum: Here is a curriculum breakdown of the Linux for Cloud and DevOps Engineers course: ***Linux for Cloud and DevOps Engineers*** Introduction Files and Directories Manage Files and Directories User Management System Management Networking Services Process Management Other Topics Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Linux for Cloud and DevOps Engineers course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Linux for Cloud and DevOps Engineers course is open to all, with no formal entry requirements. Career path Upon successful completion of the Linux for Cloud and DevOps Engineers Course, learners will be equipped with many indispensable skills and have the opportunity to grab.

Description: Programming is the language used by computer programmers to define relationship, semantics, and grammar to be able to make the computer and other digital machines work. In web development, it is used to allow new interactive applications and software to have a control through accessing different system resources. Learn the basics of Programming and Database by enrolling in this course. Who is the course for? Beginner to advanced level users can want to acquire or upgrade their programming skills People who have an interest in learning about programming and database 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. Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. Certification: After you have successfully passed the test, 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 hard copy 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 recognised 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 Programming and Database Course will be very helpful to have especially for these careers: Computer Maintenance Staff IT Department Manager IT Specialists Computer Engineer Computer Specialist Programmers. Beginners Programming Introduction To Programming 01:00:00 How To Write A Program 01:00:00 The List Of Programming Languages 00:30:00 Selecting The Right Compiler 00:30:00 What Is An Interpreter 00:30:00 How To Write A Program With An Editor 01:00:00 The Functions Of A Debugger 01:00:00 Build Strong Components For Programming 00:15:00 Profiling And Optimizing Your Program 01:00:00 Installing Your Program 00:15:00 BASIC Programming Language 01:00:00 Getting Started with BASIC Programming Language 01:00:00 BASIC Overview of BASIC Components 01:00:00 BASIC Special Variables 01:00:00 BASIC Probability Functions 01:00:00 Filtering the Data Set or Splitting the Data Set 01:00:00 DATA Blocks 01:00:00 DELETE Statement 01:00:00 FORNEXT Statement 01:00:00 IF. . . THEN Statement 01:00:00 Wrapping Up 00:30:00 Database Basics What is a Database 01:00:00 Definition of Terms 01:00:00 Database Users and Languages 01:00:00 Components of a Database System 01:00:00 Basic Set Concepts 01:00:00 Relations as a Database 01:00:00 Relational Database Operators 01:00:00 Database keys 01:00:00 Mock Exam Mock Exam- Programming and Database Course 00:30:00 Final Exam Final Exam- Programming and Database Course 00:30:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

This ChatGPT for Marketing and Productivity with AI Tools course is your guide to using AI to boost your marketing results. Boost your marketing skills and productivity to the next level with our comprehensive ChatGPT for Marketing and Productivity with AI Tools course. Dive deep into the world of Artificial Intelligence (AI), its applications, and how it can revolutionise the way you work. This course is meticulously designed to empower marketing professionals, content creators, entrepreneurs, and anyone intrigued by the power of AI.  It's a blend of theoretical understanding, practical exposure, and foresight into the future of AI, particularly in the field of marketing and productivity. In Section 01, we unpack the 'AI Marketing Playbook'. Starting with an introduction to OpenAI's ChatGPT, its possibilities, and its limitations, you'll gain a fundamental understanding of AI capabilities. Following this, delve into practical aspects of using ChatGPT, from generating innovative ideas and content to cross-posting queries and simplifying complex information. Our experts will also guide you on how to leverage AI for business problem-solving and developing methodologies, wrapping up with insights on the future of ChatGPT. In Section 02 get teaching on how to use ChatGPT and other AI tools for effective marketing. Learn to work with Autonomous AI Agents and a variety of AI tools such as Durable, Eightify, Genei, and Ellicit, to name a few. By the end of this section, you'll be equipped with the skills to carry out high-quality research, build AI-based websites, determine research credibility, and clone voices. You'll also get an interesting perspective on the future of AI. Finally, Section 03 is all about enhancing your productivity with ChatGPT and AI tools. From meta-search sites to speech-to-text services, AI design tools, content improvement techniques, and more, this section aims to streamline your work processes. Learn to use tools like Microsoft Bing Search, Google Bard, Speechify, and Adobe for audio enhancements. Wrap up this course with an exploration of generative AI and a glance into the future of this exciting field. Whether you're a beginner or an experienced professional, this course promises to expand your horizons and make you proficient in harnessing AI's power for marketing and productivity. Unleash the potential of AI and transform your work efficiency with this ChatGPT for Marketing and Productivity with AI Tools course. Enrol today and start your AI journey with us! Learning Outcomes Upon completion of the ChatGPT for Marketing course, you will be able to: Understand the fundamentals of OpenAI's ChatGPT and its capabilities. Generate and qualify ideas effectively using ChatGPT. Learn to apply ChatGPT for solving specific business problems. Develop skills to connect with various Autonomous AI Agents. Learn to use AI tools for enhanced research and content creation. Understand how to determine research credibility using AI. Gain proficiency in utilising AI for website creation and voice cloning. Develop skills to leverage AI tools for improved productivity. Understand the future scope of generative AI in marketing. Master the use of various AI design and content improvement tools. Who is this course for? This ChatGPT for Marketing course is ideal for: Marketing professionals seeking to leverage AI in their strategies. Content creators interested in AI-powered idea generation and curation. Business owners looking to integrate AI into their operational processes. Individuals interested in exploring AI applications in marketing and productivity. Any tech enthusiast keen on understanding and applying AI tools. Career Path Our ChatGPT for Marketing course will help you to pursue a range of career paths, such as: AI Marketing Specialist: £45,000 - £70,000 Content Strategist: £35,000 - £55,000 Business Intelligence Analyst: £40,000 - £65,000 Productivity Consultant: £45,000 - £75,000 AI Research Analyst: £50,000 - £80,000 AI Application Developer: £55,000 - £90,000 Digital Transformation Consultant: £60,000 - £100,000 AI Solutions Architect: £65,000 - £110,000 Prerequisites This Photoshop Training for Beginners does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Photoshop Training for Beginners 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 of the Photoshop Training for Beginners 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. Course Curriculum Section 01: The AI Marketing Playbook Unit 01: Start an Account with ChatGPT 00:02:00 Unit 02: What the Company OpenAI Say About Itself 00:02:00 Unit 03: What OpenAI Say About The Limitations of the Chatbot 00:02:00 Unit 04: Chatbot Prompt Examples Given By Open AI 00:02:00 Unit 05: Will Chat GPT Be a Paid Application 00:01:00 Unit 06: Chat GPT Idea Generation 00:02:00 Unit 07: Chat GPT - Idea Qualification and Accuracy 00:03:00 Unit 08: ChatGPT - Accuracy and Citations 00:02:00 Unit 09: Chat GPT - Creating HTML Instances 00:01:00 Unit 10: Chat GPT - How to Solve Specific Business Problems 00:02:00 Unit 11: Chat GPT - Statistical Verification of Information 00:01:00 Unit 12: Chat GPT - Rewrite Content for Different Contexts 00:02:00 Unit 13: ChatGPT - Content Checked With AI 00:02:00 Unit 14: ChatGPT - Simplifying Information 00:01:00 Unit 15: ChatGPT - How to Ask the Chatbot about Context 00:01:00 Unit 16: ChatGPT - How to Cross-Post Queries 00:01:00 Unit 17: ChatGPT - How to Narrow Down the Context of Your Query 00:02:00 Unit 18: ChatGPT - How to Solve a Business Process 00:02:00 Unit 19: ChatGPT - Developing a Methodology From Experts 00:01:00 Unit 20: The Future of ChatGPT 00:01:00 Section 02: How to Use ChatGPT and AI for Marketing Unit 01: Autonous AI Agents 00:01:00 Unit 02: Connecting to Open AI 00:01:00 Unit 03: Getting an OpenAI Key 00:01:00 Unit 04: Agent GPT - Autonomous AI 00:02:00 Unit 05: GoalGPT - Autonomous Agents 00:01:00 Unit 06: Cognosis - Autonomous AI 00:02:00 Unit 07: Aomni - Autonomous Agent 00:01:00 Unit 08: Durable - Build a Website with AI 00:01:00 Unit 09: Eightify Summaries 00:02:00 Unit 10: Genei - Do Higher Quality Research with AI 00:01:00 Unit 11: Ellicit - Do Higher Quality Research with AI 00:01:00 Unit 12: Inciteful - Do Higher Quality Research with AI 00:02:00 Unit 13: SciteAI Determine the Credibility of Your Research 00:01:00 Unit 14: Eleven Labs - Voice Cloning 00:02:00 Unit 15: AgentGPT - Wrap Up and Return 00:01:00 Unit 16: Cognosys - Wrap Up and Return 00:01:00 Unit 17: Aomni - Wrap Up and Return 00:01:00 Unit 18: Goal GPT - Wrap Up and Return 00:01:00 Unit 19: Uploading Research Reports to Summarization Applications 00:01:00 Unit 20: Perspective on The Future of AI 00:01:00 Section 03: Productivity with AI Tools Unit 01: Meta Search Sites 00:02:00 Unit 02: SMMRY for Summarzing 00:01:00 Unit 03: ChatGPT Plugins Waitlist 00:01:00 Unit 04: Using Microsoft Bing Search 00:02:00 Unit 05: Using Google Bard 00:01:00 Unit 06: Microsoft Word Speech To Text 00:01:00 Unit 07: Transcribe Audio in Microsoft Word 00:02:00 Unit 08: Speechify 00:02:00 Unit 09: Exact Image Creation 00:01:00 Unit 10: AI Design Tools 00:02:00 Unit 11: Learn How to Prompt 00:01:00 Unit 12: Content Improvement 00:01:00 Unit 13: Idea Generation 00:01:00 Unit 14: Audio Enhancement with Adobe 00:02:00 Unit 15: Clean up Audio With Cleaanvoice 00:01:00 Unit 16: Notion-AI 00:01:00 Unit 17: Pictory 00:01:00 Unit 18: Lex 00:01:00 Unit 19: ChatPDF 00:01:00 Unit 20: Conclusion and the Future of Generatie AI - Searchie 00:01:00