3046 Software Development courses

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

In a world of big data, statistical analysis is no longer a luxury, it's a necessity. Whether you're a seasoned professional or just starting out, our "Measuring Central Tendency and Dispersion" course is a must-have tool in your analytical arsenal. With comprehensive modules covering everything from introduction to statistics to common statistical mistakes, you'll gain a deep understanding of how to measure and interpret data, making you a valuable asset to any organisation. Enrol now and take your analytical skills to the next level! Learning Outcomes: After completing the course, you can expect to: Understand statistical analysis and its importance in decision-making. Learn how to measure central tendency and dispersion accurately. Gain knowledge about correlation and regression analysis, probability, and hypothesis testing. Acquire skills in creating charts and graphs for data visualisation. Identify and avoid common statistical mistakes. Develop a strong foundation in statistical analysis to apply in future studies and career. In today's data-driven world, a strong understanding of statistics is crucial for professionals across industries. Our comprehensive Statistics course is designed to equip learners with the foundational knowledge and skills necessary for effective statistical analysis. With modules covering a range of statistical concepts, including measuring central tendency and dispersion, probability, hypothesis testing, and more, this course provides an in-depth exploration of the principles that underpin statistical analysis. Whether you're a business professional looking to make data-driven decisions or a student preparing for further study in statistics, this course offers a comprehensive overview of statistical analysis. Our course materials provide a theoretical foundation that can be applied to a range of real-world situations, helping learners to develop a strong understanding of the concepts that underpin statistical analysis. Certification Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is ideal for the following: Business professionals looking to improve their data analysis skills. Students preparing for further study in statistics or related fields. Anyone with an interest in statistical analysis. Career path This course will be helpful for anyone looking to pursue a career as: Statistical Analyst: £23,000-£40,000 per year. Data Analyst: £24,000-£45,000 per year. Business Analyst: £25,000-£50,000 per year. Market Research Analyst: £24,000-£40,000 per year. Financial Analyst: £26,000-£55,000 per year. Actuary: £30,000-£70,000 per year.

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.