2981 Software Development courses in Stowmarket delivered Online

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Apple is one of the leading mobile programs, so developing applications for Apple users can be an immense advantage for a business owner. Apple is appreciated for its high-quality apps and its strict requirements for iOS app developers. Not only is it critical to follow standard practices for acceptance into the App Store, but it's also important for user friendliness and usability. To be able to appreciate these well-developed apps and features, you need to learn about the basic iPhone tricks and updated applications. Through this course, you will learn all about iPhone app development and how you can be part of the organisation which helps in developing iPhone's applications, features, and functions. Course Highlights iPhone Tricks and App Development Skills Training is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed iPhone Tricks and App Development Skills Training into 35 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 20 hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose iPhone Tricks and App Development Skills Training Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? iPhone Tricks and App Development Skills Training is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our iPhone Tricks and App Development Skills Training is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Module 1: Iphone Tricks and Apps The Most Popular Productivity Applications For the Multi-Tasker 01:00:00 Augmented Reality on the iPhone 00:30:00 Funny iPhone tricks 00:30:00 Get Beer and Popcorn on your iPhone 00:15:00 Great iPhone tips 01:00:00 Handy iPhone Tricks and Applications to Have 01:00:00 How to Find Your Way Using iPhone GPS 01:00:00 How to Use TweetDeck on Your iPhone and Stay Connected 00:15:00 Impress your friends with these iPhone usage tips and applications 00:15:00 Interesting iPhone Applications for People to Try 01:00:00 Managing Your To Do List with an iPhone Application 00:30:00 Most Wanted Applications For The iPhone 00:15:00 Popular Tricks for Your IPhone 00:15:00 Teaching Your Kids with an iPhone Application 00:15:00 Using Your iPhone as a Flash Drive 00:30:00 Top 3 Games for iPhone Addicts 00:30:00 Top 3 Must Have Tricks For iPhone Survival 00:15:00 Top 3 Social Networking Applications for the Multi-tasker 01:00:00 Top 3 Tricks to Get The Most out Of Your iPhone 00:15:00 Truly Productive Real Estate Management with an iPhone Application 01:00:00 Using an iPhone Application to Remember Key Dates 00:15:00 Using an iPhone Application to Translate Your Way to Success 00:15:00 Using an iPhone Application to Make Your Run Work for You 01:00:00 Using the Weather Channel iPhone Application to Plan Your Day 00:30:00 Module 2: App Development and Marketing Introduction 00:15:00 Potential Opportunities for Earning 00:30:00 Brainstorming your App Ideas 01:00:00 Developing your App 01:00:00 Marketing your App 01:00:00 Leveraging the App Market 01:00:00 Other Ways to Generate Income with Apps 01:00:00 Conclusion 00:15:00 Resources 00:30:00 Additional Supporting Materials iOS Development 00:00:00 iOS 10 App Essentials 00:00:00 Mock Exam Final Exam

Register on the Machine Learning in Flutter today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The Machine Learning in Flutter course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Machine Learning in Flutter Course Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Machine Learning in Flutter course, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Unit 01: Introduction Module 01: Course Curriculum 00:02:00 Unit 02: Image Picker and Camera Libraries Module 01: Image Picker Library for Flutter App Development 00:13:00 Module 02: Flutter Image Picker Application Testing 00:01:00 Module 03: Camera Package Setup for Flutter 00:04:00 Module 04: Flutter Camera Package Code 00:08:00 Unit 03: Firebase ML Kit Module 01: Firebase ML kit section Introduction 00:01:00 Module 02: Firebase ML Kit introduction 00:02:00 Unit 04: Image Labeling using ML Kit Module 01: Flutter Image Labeling Section Introduction 00:02:00 Module 02: Importing Starter code for image labeling 00:03:00 Module 03: Image labeling starter code explanation 00:06:00 Module 04: Creating firebase project for image labeling 00:06:00 Module 05: Adding Firebase ML Vision library in Flutter Application 00:10:00 Module 06: Testing Firebase Image labeling application 00:01:00 Module 07: Importing Image Labeling live feed application starter code 00:03:00 Module 08: Flutter Camera Package Code 00:06:00 Module 09: Flutter Image Labeling live feed application code 00:08:00 Module 10: Flutter Image labeling live feed application testing 00:01:00 Unit 05: Section Barcode Scanning Module 01: Flutter Barcode Scanning Section Introduction 00:02:00 Module 02: Importing Starter code for Flutter Barcode Scanning 00:03:00 Module 03: Flutter Barcode Scanning code 00:11:00 Module 04: Flutter Barcode Scanning Application Testing 00:01:00 Module 05: Flutter Barcode Scanning Live Feed Application code 00:08:00 Module 06: Flutter Barcode Scanning Live feed Application Testing 00:01:00 Unit 06: Section Text Recognition Module 01: Flutter Text Recognition Section Introduction 00:01:00 Module 02: Importing Starter code for Flutter Text Recognition 00:03:00 Module 03: Writing Flutter Text Recognition Code 00:09:00 Module 04: Testing Flutter Text Recognition Application 00:01:00 Unit 07: Section Face Detection Module 01: Flutter Face Detection Section Introduction 00:02:00 Module 02: Flutter Face Detection Application Flow 00:01:00 Module 03: Flutter Face Detection code 00:06:00 Module 04: Flutter drawing rectangles around detected faces 00:05:00 Unit 08: Pretrained Tensorflow lite models Module 01: Pretrained Tensorflow lite models Section Introduction 00:02:00 Unit 09: Section Image Classification Module 01: Flutter Image classification Section introduction 00:02:00 Module 02: Importing Starter code for Flutter Image classification application 00:03:00 Module 03: Starter code explanation for Flutter Image classification 00:06:00 Module 04: Writing flutter image classification code 00:13:00 Module 05: Testing flutter image classification application 00:02:00 Module 06: Importing Flutter live feed Image classification application starter code 00:03:00 Module 07: Starter code explanation of Flutter Live feed Image classification application 00:05:00 Module 08: Writing Flutter Image classification code 00:11:00 Module 09: Testing live feed image classification flutter application 00:01:00 Unit 10: Section object detection Module 01: Flutter Object detection section introduction 00:02:00 Module 02: Importing Application code object detection flutter 00:05:00 Module 03: Flutter Object detection code 00:13:00 Module 04: Flutter Drawing Rectangles around detected objects 00:04:00 Module 05: Importing the code for live feed object detection flutter application 00:02:00 Module 06: Testing object detection live feed flutter application 00:01:00 Module 07: Flutter Live feed object detection application code 00:10:00 Unit 11: Section human pose estimation Module 01: Flutter Pose estimation section introduction 00:02:00 Module 02: Importing Flutter Pose estimation Application code 00:04:00 Module 03: Flutter Pose estimation code 00:10:00 Module 04: Importing pose estimation live feed flutter application code 00:02:00 Module 05: Flutter Live feed pose estimation application demo 00:09:00 Module 06: Using PoseNet model for Flutter Live feed pose estimation application 00:08:00 Unit 12: Image segmentation section Module 01: Flutter Image Segmentation Section Introduction 00:02:00 Module 02: Importing Flutter Image Segmentation Application code 00:03:00 Module 03: Flutter using DeepLab model for image segmentation 00:09:00 Unit 13: Section Training Image Classification Models Module 01: Section Introduction 00:02:00 Module 02: Machine Learning and Image classification 00:02:00 Unit 14: Dog Breed Classification Module 01: Flutter getting the dataset for model training 00:05:00 Module 02: Flutter Training the model 00:06:00 Module 03: Flutter Dog Breed Classification Application 00:18:00 Module 04: Flutter Live feed dog breed classification application 00:03:00 Module 05: Testing live feed dog breed classification application 00:01:00 Unit 15: Fruits Recognition using Transfer Learning Module 01: Transfer learning introduction 00:02:00 Module 02: Flutter getting the dataset for model training 00:05:00 Module 03: Flutter Training fruit recognition model 00:09:00 Module 04: Flutter Testing Live feed fruits recognition application 00:01:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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 2 Days 12 CPD hours This course is intended for This basic course is for everyone needing to write, support, or understand SQL queries. This includes but is not limited to end-users, programmers, application designers, database administrators, and system administrators who do not yet have knowledge of Overview Code SQL statements to retrieve data from a DB2 or Informix table, including the SELECT, FROM, WHERE, GROUP BY, HAVING and ORDER BY clauses Code inner joins and non-correlated subqueries Use SQL arithmetic operations Use scalar and column functions Use UNION and UNION ALL INSERT, UPDATE and DELETE rows Code simple CREATE TABLE and CREATE VIEW statements This course is appropriate for customers working in all DB2 environments, that is, z/OS, VM/VSE, iSeries, Linux, UNIX, and Windows. It is also appropriate for customers working in an Informix environment. Outline Introduction Simple SQL Queries Retrieving Data from Multiple Tables Scalar Functions and Arithmetic Column Functions and Grouping UNION and UNION ALL Using Subqueries Maintaining data

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 1 Days 6 CPD hours This course is intended for Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

Duration 5 Days 30 CPD hours This course is intended for Motivations: Use and manage containers from first principles & architect basic applications for Kubernetes Roles: general technical audiences & IT professionals CN251 is an intensive cloud native training bootcamp for IT professionals looking to develop skills in deploying and administering containerized applications in Kubernetes. Over the course of five days, students will start with learning about first principles for application containerization followed by learning how to stand up a containerized application in Kubernetes, and, finally, ramping up the skills for day-1 operating tasks for managing a Kubernetes production environment. CN251 is an ideal course for those who need to accelerate the development of their IT skills for a rapidly-changing technology landscape. Additional course details: Nexus Humans Cloud Native Operations Bootcamp 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 Cloud Native Operations Bootcamp 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 5 Days 30 CPD hours This course is intended for Professionals who need to maintain or set up a Kubernetes cluster Container Orchestration Engineers DevOps Professionals Overview Cluster architecture, installation, and configuration Rolling out and rolling back applications in production Scaling clusters and applications to best use How to create robust, self-healing deployments Networking configuration on cluster nodes, services, and CoreDNS Persistent and intelligent storage for applications Troubleshooting cluster, application, and user errors Vendor-agnostic cloud provider-based Kubernetes 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, vendor agnostic training you will go back to work with the knowledge, skills, and abilities to design, implement, and maintain a production-grade Kubernetes cluster. We prioritize covering all objectives and concepts necessary for passing the Certified Kubernetes Administrator (CKA) exam. You will be provided the components necessary to assemble your own high availability Kubernetes environment and configure, expand, and control it to meet the demands made of cluster administrators. Your week of intensive, hands-on training will conclude with a mock CKA exam that simulates the real exam. Cluster Architecture, Installation & Configuration Each student will be given an environment that allows them to build a Kubernetes cluster from scratch. After a detailed discussion on key architectural components and primitives, students will install and compare two production grade Kubernetes clusters. Review: Kubernetes Fundamentals After successfully instantiating their own Kubernetes Cluster, students will be guided through foundational concepts of deploying and managing applications in a production environment. Workloads & Scheduling After establishing a solid Kubernetes command line foundation, students will be led through discussion and hands-on labs which focus on effectively creating applications that are easy to configure, simple to manage, quick to scale, and able to heal themselves. Services & Networking Thoroughly understanding the underlying physical and network infrastructure of a Kubernetes cluster is an essential skill for a Certified Kubernetes Administrator. After an in-depth discussion of the Kubernetes Networking Model, students explore the networking of their cluster?s Control Plane, Workers, Pods, and Services. Storage Certified Kubernetes Administrators are often in charge of designing and implementing the storage architecture for their clusters. After discussing many common cluster storage solutions and how to best use each, students practice incorporating stateful storage into their applications. Troubleshooting A Certified Kubernetes Administrator is expected to be an effective troubleshooter for their cluster. The lecture covers a variety of ways to evaluate and optimize available log information for efficient troubleshooting, and the labs have students practice diagnosing and resolving several typical issues within their Kubernetes Cluster. Certified Kubernetes Administrator Practice Exam Just like the Cloud Native Computing Foundation CKA Exam, the students will be given two hours to complete hands-on tasks in their own Kubernetes environment. Unlike the certification exam, students taking the Alta3 CKA Practice Exam will have scoring and documented answers available immediately after the exam is complete, and will have built-in class time to re-examine topics that they wish to discuss in greater depth.