1604 Basic courses in Manchester delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This lecture and exercise-based course is for individuals who want to understand how to install, configure, and manage an IBM Spectrum Scale storage cluster. Overview After completing this course, you should be able to: Summarize the key features of IBM Spectrum Scale Describe IBM ESS and Spectrum Scale RAID Install IBM Spectrum Scale and configure a cluster Manage a cluster Implement information lifecycle management (ILM) Configure IBM Spectrum Scale high availability features Back up critical cluster data This course is intended for IT professionals tasked with administering an IBM Spectrum Scale storage cluster in environments running Linux and AIX nodes. The course includes information on installing, configuring, and monitoring an IBM Spectrum Scale cluster. Many Spectrum Scale features are described in lecture materials and then implemented in lab exercises. These features include: Storage management, high availability options, cluster management, and information lifecycle management (ILM) tools. Note: Although the lab environment is running the Linux operating system, the differences in Spectrum Scale compared with an AIX environment are minor. Therefore, the skills acquired during the course can be applied in both Linux and AIX environments. Welcome and course overview Unit 1 - IBM Spectrum Scale overview Exercise 1 - Cluster node preparation Unit 2 - Installation and cluster configuration Exercise 2 - Installation and cluster configuration Unit 3 - Cluster management Exercise 3 - Cluster management and configuration Unit 4 - Information Lifecycle Management (ILM) Exercise 4 - Storage pools, filesets, and policies Unit 5 - High availability and cluster data backups Exercise 5 - Replication and snapshots Course wrap-up and evaluation

Scottish Gaelic Beginner Conversation Course for online learners worldwide.

Duration 4 Days 24 CPD hours This course is intended for This intermediate course is designed for technical support personnel who implement, operate, and perform day-to-day administration of IBM MQ V8 on z/OS. Overview Describe message-oriented middleware and the capabilities it must provideIdentify the key components of IBM MQ for z/OSSummarize the responsibilities of the IBM MQ administratorConfigure IBM MQ IBM V8 for z/OSEnable IBM MQ for z/OS eight-byte RBA and buffers above 2 GBDemonstrate how to create and change queues and place and retrieve messages from a queueDefine and demonstrate how to set up and work with distributed queuingDifferentiate between an IBM MQ queue manager and an IBM MQ clientDescribe and demonstrate how to set up an IBM MQ clusterContrast point-to-point and publish/subscribe messaging stylesDescribe shared queues and queue sharing groupsSummarize IBM MQ for z/OS recovery and restart activitiesDemonstrate how to use IBM MQ events for monitoringSummarize performance considerationsDescribe security considerations for IBM MQ for z/OSDescribe and implement connection authentication and channel authorizationIdentify correct problem determination techniques for IBM MQ for z/OSSummarize basic use and configuration of IBM MQ Managed File TransferDescribe IBM MQ support for CICS and IMS interfaces This course provides the skills that are necessary to configure and manage an IBM MQ V8 queue manager on z/OS. Through lectures and hands-on lab exercises, students learn how to install, customize, operate, and administer IBM MQ V8. Course Outline Course introduction IBM MQ review IBM MQ architecture, installation, and configuration Exercise: Configuring an IBM MQ for z/OS queue manager IBM MQ for z/OS administrative interface options Exercise: Working with queues Distributed queuing Exercise: Working with channels IBM MQ clients Exercise: Working with IBM MQ clients IBM MQ cluster basics Exercise: Working with IBM MQ clusters Publish/subscribe basics Exercise: Publish/subscribe basics Queue sharing groups Using IBM MQ events and the dead-letter queue utility Exercise: Working with IBM MQ events Security considerations Exercise: Security Problem determination IBM MQ Managed File Transfer Exercise: IBM MQ Managed File Transfer configuration for z/OS IBM MQ for z/OS backup, recovery, and related file tasks Exercise: Working with file handling utilities Support for CICS, IMS, and HTTP applications Course summary

Duration 4 Days 24 CPD hours This course is intended for Storage and system administrators using HP Data Protector software, System Engineers, Consultants, Project Managers, Professional Services, and Sales. Overview Upon successful completion of this course, you should be able to:Install and distribute HP Data Protector software in your environmentConfigure the HP Data Protector software productConfigure your tape and disk-based backup solutions for use with HP Data Protector softwareUse HP Data Protector software to run backups and restores, and monitor these sessions from both the Data Protector GUI and command lineManage the HP Data Protector software Internal Database (IDB)Create custom reports and notification proceduresSecure your installation by configuring user access and adding security to the Cell Manager and DP client systemsPrepare your client to recover from a disaster situationUnderstand the Data Protector processes and perform basic troubleshooting of your installation The hands-on lab exercises reinforce the theory sessions to ensure a thorough understanding of backup and recovery concepts, the functionality of the software and its application to typical storage implementations. The hands-on lab exercises reinforce the theory sessions to ensure a thorough understanding of backup and recovery concepts, the functionality of the software and its application to typical storage implementations. Additional course details: Nexus Humans DP120 Data Protector 9.x Essentials 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 DP120 Data Protector 9.x Essentials 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 3 Days 18 CPD hours This course is intended for This Yellow Belt training is intended for managers and employees from companies or government institutions who want to get acquainted with Lean Six Sigma or (soon) will have to deal with Lean Six Sigma in their own organization Overview During this training you will become acquainted with the essence of Lean Six Sigma and the importance of improvement management. It discusses how a Lean Six Sigma improvement project is approached, who plays an important role in an improvement project, what it yields as an employee or manager if this methodology is introduced in the organization and what should be taken into account when implementing. Theory and practice go hand in hand. The training encourages you to think about the value for your customer and which methodology best suits your role and your value in a process. This makes Lean and Six Sigma understandable and applicable. We also show what is involved in the introduction of LeanSix Sigma and there are various discussions about the introduction and the 'do's and don'ts of Lean Six Sigma. Course Outline Lean & Six Sigma Overview Basic Statistics Lean Six Sigma: the DMAIC Roadmap Lean Six Sigma: Tools Additional course details: Nexus Humans Lean Six Sigma Yellow Belt 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 Lean Six Sigma Yellow Belt 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 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

Duration 4 Days 24 CPD hours This course is intended for This in an intermediate level Java development course geared for students experienced with Java 8 or later programming essentials who wish to quickly get up and running with advanced Java skills. This course does not cover Java programming fundamentals. Overview Students will leave this course armed with the required skills to improve their Java applications using sound coding techniques and best practices. This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in advanced development skills, coupling the most current, effective techniques with the soundest industry practices. Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Develop modular applications in Java Utilize the tooling that is provided in Java 9 to migrate, monitor and optimize applications Use the new JShell tool to quickly test java constructs Understand how the implementation of the String class has been updated to decrease the memory footprint Use the enhancements made to the Concurrency API, working with Completable Future instance of Thread pools Specific Java 9 features that are covered in the course include: The Java Module System (project Jigsaw) JShell Updated try-with-resources Performance enhancements in Java 9 Multi-Release Jar files This fast-track course is designed for experienced developers who have prior working knowledge of basic Java 8 or Java 9 and want to take advantage of the newest features of Java 9 that can help improve performance and functionality of Java 9 applications. You will gain invaluable insight into how to leverage Modules, scale applications into multi-core environments, improve performance, and become a more effective Java 9 developer. Java 9 Updates Review of What is New in Java 9 Milling Project Coin The Java Module system (Jigsaw) Why JigSaw? Introduction to the Module System The Module Descriptor Working with Modules JShell JShell More Java 9 Other New Java 9 Features Performance Optimizations Memory Management (Optional) Multithreading and Concurrency Multithreading Concurrent Java Java 8 Concurrency Updates Reflection and References Introspection and Reflection Reference Objects Effective Java Objects, Declarations, and Initializations Exceptions Writing High-Performance Applications Profiling and Benchmarking Profiling Tools Code Optimization Techniques Code Optimization Myths Design Optimization Techniques

Duration 3 Days 18 CPD hours This course is intended for In order to be successful in this class, incoming attendees are required to have current, hands-on experience in developing basic web applications, and be versed in HTML5, CSS3 and JavaScript. This is an introductory level Angular development course but an intermediate level web development class, designed for experienced web developers that need to further extend their skills in web development Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to: What Angular is and why should you use it How Angular reduces the amount of code that you must write to add rich functionality to both existing and new web pages What TypeScript is, why it is useful, and how to use it with Angular How to facilitate development and deployment using Angular CLI How to work with the various aspects of the Angular architecture to implement clean, responsive web interfaces How Routers can support navigation within a Single Page Application What the best practices are for using Angular so that it works unobtrusively and performs well How to use Angular with HTTP to support JSON, REST, and other services Best practices for Angular so that it works unobtrusively and performs well Angular is one of the most popular JavaScript frameworks for creating web and native mobile applications. This introductory course thoroughly explores the latest Angular features and advances, demonstrating how to solve the traditional challenges of JavaScript web application development. You will build custom components, using application routes, form validation, and unit-testing and delve into component-driven development with Angular components. Angular Overview Overview of Angular Architecture Getting Started with Angular Getting Started with TypeScript Bootstrapping with Angular CLI Angular Project Structure Unit Testing with Angular Testing and Angular Working with Angular Components and Events Third Party Libraries Dynamic Views Pipes Angular Forms Forms and the Forms API Single Page Applications and Routes Single Page Applications Services and Dependency Injection Modules Using RESTful Services Overview of REST Angular and REST Angular Best Practices Angular Style Guide What is New in Angular 9 Additional Topics (Time Permitting) Lesson: ES6+ Sass and SCSS for Angular and Material

Duration 3 Days 18 CPD hours This course is intended for This introductory-level course is for experienced application developers new to MongoDB. Overview This course is approximately 50% hands-on lab to lecture ratio, combining engaging expert lessons, demos and group discussions with real-world, skills-focused machine-based labs and exercises. Working in a hands-on learning environment, guided by our expert team, you'll explore: Storage Basics MongoDB Document Model MongoDB Setup CRUD: Basics through Advanced Concepts Performance: Basics through Advanced Concepts Aggregation: Basics through Advanced Concepts Replication: Basics through Advanced Concepts Sharding: Basics through Advanced Concepts Schema Design Security Basics, Authentication & Authorization Application Development and Drivers Geared for experienced developers, Introduction to MongoDB for Developers is a comprehensive course that provides you with hands-on experience with the MongoDB query language, aggregation framework, data modeling, indexes, drivers, basic performance tuning, high availability and scaling. Throughout the course, you?ll explore the MongoDB Atlas database environment in detail, gaining job-ready skills you can put right to work after class. Storage Basics What is a Storage Engine? WiredTiger Storage Engine In-Memory Storage Engine Encrypted Storage Engine MongoDB Document Model JSON and BSON MongoDB Data Types MongoDB Setup Atlas Setup / Local MongoDB Setup CRUD Basics Insert Command Find Command Query Operators Remove Command Updating Documents CRUD Advanced Bulk Writes Retryable Writes Find and Modify Transactions Performance Basics Indexes Aggregation Basics Aggregation Pipeline Concepts Aggregation Pipeline Stages Aggregation Pipeline Expressions Aggregation Advanced $lookup stage $graphLookup stage $expr operator Faceted Search Type Conversions Advanced Expression Operators Date Expression Operators Expression Variables Aggregation Pipeline Optimizations Aggregation in a Sharded Cluster Replication Basics MongoDB Replica Sets Replica Set Use Cases Replication Mechanics Replication Advanced Using Write Concern to Tune Durability Semantics Using Read Concern to Tune Read Isolation Using Read Preference Replica Set Tag Sets Sharding Basics Sharding Concepts When to Shard What is a Shard Key? Zoned Sharding / MongoDB Atlas Global Clusters Sharding Advanced Components of a Sharded Cluster Sharding Mechanics Choosing a Good Shard Key Schema Design Schema Design Core Concepts Common Patterns Security Basics Authentication & Authorization Network Encryption Encryption at Rest Auditing

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization. Overview After completing this course delegates will be capable of writing effective R code to manipulate, analyse and visualise data to enable their organisations make better, data-driven decisions. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Course Outline Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R programming language is one of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. The course will explore the following topics through a series of interactive workshop sessions: What is R? Basic R programming conventions Data structures in R Accessing data in R Descriptive statistics in R Statistical analysis in R Data manipulation in R Data visualisation in R Additional course details: Nexus Humans Beginning Data Analytics With R 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 Beginning Data Analytics With R 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.