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Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

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Expand your communication skills with our British Sign Language Level 2 course. Dive deeper into BSL with advanced fingerspelling, personal information exchange, and specialized topics like family, weather, and transport. Embrace inclusivity and enhance your linguistic abilities now.

Duration 3 Days 18 CPD hours This course is intended for This introduction to Spring development course requires that incoming students possess solid Java programming skills and practical hands-on Java experience. This class is geared for experienced Java developers who are new to Spring, who wish to understand how and when to use Spring in Java and JEE applications. Overview Working in a hands-on learning environment, students will review configuration basics of the Spring framework. The course then moves into Spring Boot, providing in-depth content and experience working with Spring Boot to accomplish a variety of tasks. In addition to working through the Spring Actuator, students work extensively at testing and debugging Spring Boot applications. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' application development and Spring experience into every classroom. Working in a hands-on learning environment, led by our expert practitioner, students will: Review the concept of Java-based configuration Become familiar with the conditionally loading bean definitions and Application Contexts Understand how to leverage the power of Spring Boot Use Spring Boot to create and work with JPA repositories Use Spring Boot to work in conjunction with Spring Cloud Understand the Spring Cloud project and how it relates to general Cloud concepts and practices Work with Spring Cloud configuration and the Config Client The Spring framework is an application framework that provides a lightweight container that supports the creation of simple-to-complex components in a non-invasive fashion. Spring's flexibility and transparency is congruent and supportive of incremental development and testing. The framework's structure supports the layering of functionality such as persistence, transactions, view-oriented frameworks, and enterprise systems and capabilities. Introduction to Spring Boot and Spring Cloud is a hands-on Spring training course geared for experienced Java developers who need to understand what the Spring Boot is in terms of today's systems and architectures, and how to use Spring in conjunction with other technologies and frameworks. This course targets Spring Boot 2, which includes full support for Java 8 and JEE 7 (earlier versions of Java and JEE continue to be supported). Spring supports the use of lambda expressions and method references in many of its APIs. Spring makes enterprise development easier. Spring simplifies common tasks and encourages good design based on programming to interfaces. Spring makes your application easier to configure and reduces the need for many JEE design patterns. Spring puts the OO design back into your enterprise application, and it integrates nicely with many view technologies and the new features of HTML5. Introduction to Spring The Spring Framework Configuring Spring Managed Beans Defining Bean dependencies Spring Cloud Spring Boot Additional Configuration Spring Cloud Project Introduction to Spring Boot Working with Spring Boot Spring AOP Introduction to Aspect Oriented Programming Spring Cloud Config Spring Cloud Registry and Discovery Spring AOP Spring Boot 2 Spring Boot Actuator Developing in Spring Boot Thymeleaf Spring Cloud GateWay Additional course details: Nexus Humans Introduction to Spring Boot and Spring Cloud (TT3324) 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 Introduction to Spring Boot and Spring Cloud (TT3324) 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 Motivations: Quickly learn the foundations of containerization and orchestration with Docker Swarm, and become familiar with all the features of Docker Enterprise. Roles: System Operators & Administrators Overview This course combines all topics of CN100 , CN110 , CN210 In this intense cloud native bootcamp, you?ll encounter containers for the first time, learn to orchestrate them into scalable, highly available applications orchestrated by Docker Swarm, and finally discover how to enhance the security of your entire software supply chain and production environments using Docker Enterprise. This bundle is ideal for students who are just starting out with containerization and want to leverage the full power of the Docker Enterprise platform as soon as possible. In this intense cloud native bootcamp, you'll encounter containers for the first time, learn to orchestrate them into scalable, highly available applications orchestrated by Docker Swarm, and finally discover how to enhance the security of your entire software supply chain and production environments using Docker Enterprise. This bundle is ideal for students who are just starting out with containerization and want to leverage the full power of the Docker Enterprise platform as soon as possible.

Duration 5 Days 30 CPD hours This course is intended for Software Engineers and DevOps professionals working in an Enterprise developing mission critical line of business applications. Overview By the end of this course, students will be able to: Assess the advantages of a containerized software development & deployment Use Docker engine features necessary for running containerized applications Utilize Swarm and Kubernetes orchestrators to deploy, maintain, and scale a distributed application Describe the essential patterns used in a highly distributed EE application Understand how to configure EE applications for different environments without code changes Produce and containerize scalable, accessible, and fault-tolerant EE applications Apply different debugging and testing techniques to containerized EE applications The Docker Fundamentals + Enterprise Operations Bundle includes the full Docker for Enterprise Operations course as well as the prerequisite Docker Fundamentals course run back to back in a single intensive training experience. The Docker Fundamentals training course features the foundational concepts and practices of containerization on a single Docker node. The course offers learners the opportunity to assimilate basic container orchestration and how to scale Docker across multiple nodes in a simple swarm cluster. This course provides essential foundational knowledge for subsequent Docker courses. As the follow-on to the Docker Fundamentals course, Docker for Enterprise Operations is a role-based course is designed for Docker Operations teams to accelerate their Docker journey in the enterprise. The course covers in-depth core advanced features of Docker EE and best practices to apply these features at scale with enterprise workloads. Platform Availability: Linux, Windows (Fundamentals Only). Introducing Docker Containerization Fundamentals Creating Images Docker Volumes Docker Networking Basics Introduction to Docker Compose Introduction to Swarm Mode Introduction to Kubernetes Secrets Fundamentals Signature Assignment Distributed Application Architecture Sample Application Edit and Continue Debugging Docker Compose Testing Service Discovery Defensive Programming Logging and Error Handling Health Checks Secrets Configuration Management Development Pipeline Overview Universal Control Plane Docker Trusted Registry Repository Automation Build Server

Duration 4 Days 24 CPD hours This course is intended for Application developers who want to increase their understanding of Spring and Spring Boot with hands-on experience and a focus on fundamentals Overview By the end of the course, you should be able to meet the following objectives: Spring configuration using Java Configuration and Annotations Aspect oriented programming with Spring Testing Spring applications using JUnit 5 Spring Data Access - JDBC, JPA and Spring Data Spring Transaction Management Simplifying application development with Spring Boot Spring Boot auto-configuration, starters and properties Build a simple REST application using Spring Boot, embedded Web Server and fat JARs or classic WARs Implementing REST client applications using RestTemplate and WebClient Spring Security Enable and extend metrics and monitoring capabilities using Spring Boot actuator Utilize Spring Boot enhancements to testing This course offers hands-on experience with the major features of Spring and Spring Boot, which includes configuration, data access, REST, AOP, auto-configuration, actuator, security, and Spring testing framework to build enterprise and microservices applications. On completion, participants will have a foundation for creating enterprise and cloud-ready applications. Introduction to Spring Java configuration and the Spring application context @Configuration and @Bean annotations @Import: working with multiple configuration files Defining bean scopes Launching a Spring Application and obtaining Beans Spring JAVA Configuration: A Deeper Look External properties & Property sources Environment abstraction Using bean profiles Spring Expression Language (SpEL) Annotation-based Dependency Injection Component scanning Autowiring using @Autowired Java configuration versus annotations, mixing. Lifecycle annotations: @PostConstruct and @PreDestroy Stereotypes and meta-annotations Factory Pattern in Spring Using Spring FactoryBeans Advanced Spring: How Does Spring Work Internally? The Spring Bean Lifecycle The BeanFactoryPostProcessor interception point The BeanPostProcessor interception point Spring Bean Proxies @Bean method return types Aspect-oriented programming What problems does AOP solve? Defining pointcut expressions Implementing various types of advice Testing a Spring-based Application Spring and Test-Driven Development Spring 5 integration testing with JUnit 5 Application context caching and the @Dirties Context annotation Profile selection with @Active Profiles Easy test data setup with @Sql Data Accss and JDBC with Spring How Spring integrates with existing data access technologies Data Access Exception hierarchy Spring?s Jdbc Template Database Transactions with Spring Transactions overview Transaction management with Spring Transaction propagation and rollback rules Transactions and integration testing Spring Boot Introduction Introduction to Spring Boot Features Value Proposition of Spring Boot Creating a simple Boot application using Spring Initializer website Spring Boot Dependencies, Auto-configuration, and Runtime Dependency management using Spring Boot starters How auto-configuration works Configuration properties Overriding auto-configuration Using Command Line Runner JPA with Spring and Spring Data Quick introduction to ORM with JPA Benefits of using Spring with JPA JPA configuration in Spring Configuring Spring JPA using Spring Boot Spring Data JPA dynamic repositories Spring MVC Architecture and Overview Introduction to Spring MVC and request processing Controller method signatures Using @Controller, @RestController and @GetMapping annotations Configuring Spring MVC with Spring Boot Spring Boot packaging options, JAR or WAR Rest with Spring MVC An introduction to the REST architectural style Controlling HTTP response codes with @ResponseStatus Implementing REST with Spring MVC, @RequestMapping, @RequestBody and @ResponseBody Spring MVC?s HttpMessageConverters and automatic content negotiation Spring Security What problems does Spring Security solve? Configuring authentication Implementing authorization by intercepting URLs Authorization at the Java method level Understanding the Spring Security filter chain Spring security testing Actuators, Metrics and Health Indicators Exposing Spring Boot Actuator endpoints Custom Metrics Health Indicators Creating custom Health Indicators External monitoring systems Spring Boot Testing Enhancements Spring Boot testing overview Integration testing using @SpringBootTest Web slice testing with MockMvc framework Slices to test different layers of the application Spring Security Oauth (Optional Topic) OAuth 2 Overview Implementing OAuth 2 using Spring Security OAuth Reactive Applications with Spring (Optional Topic) Overview of Reactive Programming concepts Reactive Programming support in Spring Using Spring?s reactive WebClient Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Spring: Core Training 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 VMware Spring: Core Training 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 This course is for support staff for AIX on POWER systems Overview After completing this course, you should be able to: - Distinguish Korn and bash shell specific features - Use utilities such as sed and awk to manipulate data - Understand system shell scripts such as /etc/shutdown - Write useful shell scripts to aid system administration This course will teach you how to use shell scripts and utilities for practical system administration of AIX (or other UNIX) operating systems. Basic shell conceptsFlow control in a shell ScriptFunctions and typesetShell features such as arithmetic and string handlingUsing regular expressionsUsing sed, awk and other AIX utilities

Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

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