1912 Object courses in Cardiff delivered Live Online

Aftereffects face to face training customised and bespoke.

Duration 3 Days 18 CPD hours This course is intended for If you have worked in C++ but want to learn how to make the most of this language, especially for large projects, this course is for you. Overview By the end of this course, you'll have developed programming skills that will set you apart from other C++ programmers. After completing this course, you will be able to: Delve into the anatomy and workflow of C++ Study the pros and cons of different approaches to coding in C++ Test, run, and debug your programs Link object files as a dynamic library Use templates, SFINAE, constexpr if expressions and variadic templates Apply best practice to resource management This course begins with advanced C++ concepts by helping you decipher the sophisticated C++ type system and understand how various stages of compilation convert source code to object code. You'll then learn how to recognize the tools that need to be used in order to control the flow of execution, capture data, and pass data around. By creating small models, you'll even discover how to use advanced lambdas and captures and express common API design patterns in C++. As you cover later lessons, you'll explore ways to optimize your code by learning about memory alignment, cache access, and the time a program takes to run. The concluding lesson will help you to maximize performance by understanding modern CPU branch prediction and how to make your code cache-friendly. Anatomy of Portable C++ Software Managing C++ Projects Writing Readable Code No Ducks Allowed ? Types and Deduction C++ Types Creating User Types Structuring our Code No Ducks Allowed ? Templates and Deduction Inheritance, Polymorphism, and Interfaces Templates ? Generic Programming Type Aliases ? typedef and using Class Templates No Leaks Allowed ? Exceptions and Resources Exceptions in C++ RAII and the STL Move Semantics Name Lookup Caveat Emptor Separation of Concerns ? Software Architecture, Functions, and Variadic Templates Function Objects and Lambda Expressions Variadic Templates The Philosophers' Dinner ? Threads and Concurrency Synchronous, Asynchronous, and Threaded Execution Review Synchronization, Data Hazards, and Race Conditions Future, Promises, and Async Streams and I/O File I/O Implementation Classes String I/O Implementation I/O Manipulators Making Additional Streams Using Macros Everybody Falls, It's How You Get Back Up ? Testing and Debugging Assertions Unit Testing and Mock Testing Understanding Exception Handling Breakpoints, Watchpoints, and Data Visualization Need for Speed ? Performance and Optimization Performance Measurement Runtime Profiling Optimization Strategies Cache Friendly Code

Why choose SketchUp Basic to Intermediate Training Course? Click for more info SketchUp offers a user-friendly experience with its intuitive interface, enabling beginners to start smoothly and professionals to work efficiently. The software provides straightforward tools and shortcuts, ensuring precise and speedy creation of 3D models. Duration: 5 hrs Method: 1-on-1, Personalized attention Schedule: Tailor your own schedule by pre-booking a convenient hour of your choice, available from Mon to Sat between 9 am and 7 pm SketchUp is a popular and robust CAD solution designed for engineers, designers, architects, and more. Its powerful suite of tools includes customizable palettes, lighting effects, animations, textures, and access to the Trimble 3D warehouse. SketchUp Basic Training Course. 1 on 1 Training. 5 hours Understanding the Basics of SketchUpIntroduction to SketchUpNavigating the SketchUp EnvironmentExploring Zoom, Pan, and Rotate FunctionsFamiliarizing Yourself with the XYZ Axis Mastering SketchUp ToolsEfficient Toolbar SelectionsUtilizing Templates for ProjectsDrawing with Precision Using the Pencil ToolWorking with Fundamental Geometric ShapesTaking Accurate Measurements Advanced SketchUp TechniquesCreating Circles and ArcsHarnessing Sticky Geometry SolutionsUnveiling the Power of Tags (Formerly Layers)Streamlining Workflow with Keyboard ShortcutsAccurate Object Measurement within SketchUpInformation Management and Database UsageMoving and Copying ObjectsSimple Array TechniquesMastering Rotational ManipulationsEffortless Rotational CopyingFractional and Relative Scaling Component and Group CreationConstructing Components for ReusabilityCreating Efficient GroupsComparing the Advantages of Components and GroupsSaving and Reusing ComponentsImporting Components from Digital Repositories Advanced Modeling and GeometryLeveraging Push-Pull OperationsCreating Complex Shapes with the Follow Me ToolExploring Geometry IntersectionsDuplicating and Offsetting Faces, Edges, and PolygonsIncorporating 2D Polygons into Your DrawingsSkillful Use of the Paint Bucket Tool Materials and TexturesProficiency with the Materials EditorApplying High-Quality TexturesSourcing and Positioning TexturesGraphics and Bitmap ConsiderationsCrafting Scenes and StylesGenerating and Customizing ScenesManaging Scenes and Styles Introduction to Animation and PresentationAnimation ConceptsAdding Dimensions to Your SketchUp ModelsAnnotating Designs for ClarityPreparing Models for PrintingExporting Images and PDFs in 2D Formats

Duration 1.5 Days 9 CPD hours This course is intended for This course is designed for software developers or anyone interested in building Android applications. Overview Install Android Studio. Writing a Java Program. Run a Java Program. Write a Java Comment. Understand Java Variables and Their Data Types. Acquiring Good Knowledge of Java Control Flow Statements. Understanding The Java Methods and Arrays. Understanding the Object-Oriented Programming (OOP) Concepts and Java Class. Developing applications for Android? systems requires basic knowledge of Java programming language. Introductory course that focuses on the fundamentals of Java programming language, its framework, syntax, and paradigm. First Step in Java The History of Java How Java Programs work? Install Java JDK and JRE Why did Google choose Java over other programming languages? Android OS Structure Install Android Studio Create and Run Java Projects Creating an Android Project (Java Project) Using Android Studio Writing a Java Program Java Methods Running a Java Program Write a Comment Java Variables and Their Data Type Control Flow Statements Introduction IF ? Else Statement If?Else and Else?If... Statement If Else and Logical Operators Switch Statement While Loop Do-while Loop For Loop The Break Statement The Continue Statement Methods and Arrays Introduction Method Structure Call Method by Value Call Method by Reference Arrays Enter Data to Java Program Object-Oriented Programming (OOP) Concepts Java Class Additional course details: Nexus Humans Java Fundamentals for Android Development 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 Java Fundamentals for Android Development 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 Experienced VMware vSphere administrators Overview By the end of the course, you should be able to meet the following objectives: Explain the key features and use cases for vSAN Detail the underlying vSAN architecture and components Describe the different vSAN deployment options Detail vSAN cluster requirements and considerations Apply recommended vSAN design considerations and capacity sizing practices Determine and plan for storage consumption by data growth and failure tolerance Design vSAN hosts for operational needs Explain Maintenance Mode use and its impacts on vSAN Apply best practices for vSAN network configurations Manually configure a vSAN cluster using VMware vSphere Client™ Explain and configure vSAN fault domains Understand and apply vSAN storage policies Define encryption in the vSAN cluster Describe the architecture and use cases for stretched clusters Describe the architecture and use cases for two-node clusters Understand the steps involved in creating the vSAN iSCSI target services This two-day, hands-on training course provides you with the knowledge, skills, and tools to plan and deploy a VMware vSAN? cluster. In this course, you are taught the many considerations that the end vSAN configuration has on the initial planning of the vSAN datastore. You also perform a fully manual configuration of a vSAN cluster. Course Introduction Introductions and course logistics Course objectives Introduction to vSAN Describe vSAN architecture Identify vSAN objects and components Describe the advantages of object-based storage Describe the difference between All-Flash and Hybrid vSAN architecture Explain the key features and use cases for vSAN Discuss the vSAN integration and compatibility with other VMware technologies Planning a vSAN Cluster Identify requirements and planning considerations for vSAN clusters Apply vSAN cluster planning and deployment best practices Determine and plan for storage consumption by data growth and failure tolerance Design vSAN hosts for operational needs Identify vSAN networking features and requirements Describe ways of controlling traffic in a vSAN environment Recognize best practices for vSAN network configurations Deploying a vSAN Cluster Deploy and configure a vSAN cluster using the Cluster Quickstart wizard Manually configure a vSAN cluster using vSphere Client Explain and configure vSAN fault domains Using VMware vSphere© High Availability with vSAN Understand vSAN cluster maintenance capabilities Describe the difference between implicit and explicit fault domains Create explicit fault domains vSAN Storage Policies Describe a vSAN object Describe how objects are split into components Explain the purpose of witness components Explain how vSAN stores large objects View object and component placement on the vSAN datastore Explain how storage policies work with vSAN Define and create a virtual machine storage policy Apply and modify virtual machine storage policies Change virtual machine storage policies dynamically Identify virtual machine storage policy compliance status Introduction to Advanced vSAN Configurations Define and configure compression and deduplication in the vSAN cluster Define and configure encryption in the vSAN cluster Understand the remote vSAN datastore topology Identify the operations involved in managing the remote vSAN datastore Understand the steps involved in creating the vSAN iSCSI target service vSAN Stretched and Two-Node Clusters Describe the architecture and use cases for stretched clusters Detail the deployment and replacement of a vSAN witness node Describe the architecture and uses case for two-node clusters Explain the benefits of vSphere HA and vSphere Site Recovery Manager in a vSAN stretched cluster Explain storage policies for vSAN stretched cluster Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware vSAN: Plan and Deploy [v7] 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 vSAN: Plan and Deploy [v7] 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.

Why Choose InDesign Evening Training Course? Course Link. If you aim to enhance your design abilities, acquire proficiency in a new software, or pursue a career in graphic design, an InDesign course is highly beneficial. Tailored for individuals with foundational knowledge of Adobe InDesign, this training is designed to further develop your existing skills. Duration: 10 hrs Method: 1-on-1, Personalized attention Schedule: Tailor your own hours of your choice, available from Mon to Sat between 9 am and 7 pm InDesign Evening Course Outline (10 hours) Introduction Getting Started with Adobe InDesign CC Advanced Course Adjusting Workspace for Maximum Efficiency Customizing Default Font Size for New Documents Utilizing Special Features for Typekit & Open Type Fonts Exploring Sources for Free Fonts in InDesign Mastering Fonts in Adobe InDesign CC Identifying Fonts with Font Guess Selecting Beautiful Font Pairings Incorporating Free Icons from Adobe Market Using the Color Theme Tool Understanding Colour Modes Importing and Setting Default Colors Finding Great Colors with Adobe Color Managing Appearance of Black & Proofing Colors Creating Multiple Shapes with Gridify Live Distribute Drawing Arrows in InDesign CC Designing Complex Flowers in InDesign CC Utilizing Auto Size for Auto-Expanding Text Boxes Exploring Placeholder Text Alternatives Adding Paragraph Borders & Shading Understanding Paragraph vs Single Line Composer Making Paragraphs Span 2 Columns Mastering Justification & Hyphenation Options Aligning Optical Margins Harnessing the Power of Keep Options Working with Advanced Anchored Objects Using Conditional Text Creating Pie Charts & Bar Graphs Pros & Cons of Interactive Types Creating Interactive PDFs Adding Interactive Page Transitions Adding Navigation to Interactive PDFs Understanding Publish Online in InDesign CC Publishing Adobe InDesign Documents Online Adding Video to InDesign Documents Creating Button-Triggered Animations Making Multi-State Objects Incorporating Adobe Animate CC to InDesign Files Adding Maps & Calendars to Interactive Documents Generating QR Codes in InDesign CC Exploring Essential Keyboard Shortcuts Automatically Placing Text on Multiple Pages Creating Cross References & Index Adding Document Name Automatically with Text Variables Utilizing Adobe InDesign CC Book Feature Changing Preferences for Advanced Users Speeding Up Workflow for Advanced Users Using Character Styles Advanced Paragraph Styles Mapping Word Styles with InDesign Styles Creating Nested Styles & Grep Styles Using Next Style Mastering Object Styles Best Practices for Working Across Multiple Documents Utilizing Adobe Stock with InDesign CC Cropping Images Inside Text Making InDesign Layouts with Adobe Comp CC Advanced Use of CC Libraries Integrating Photoshop & Illustrator in InDesign CC Creating PDF Forms in InDesign CC Advanced Use of the Pages Panel Placing InDesign Documents Inside Each Other Installing and Using Scripts in InDesign CC Improving InDesign Performance Advanced Exporting & Printing Tricks Bonus: Software Updates Adobe InDesign https://adobe.com › indesign › get-started Installing for the first time or on a new computer? Click Get InDesign below to begin downloading. Follow the onscreen instructions to sign-in and install.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for technical professionals who require the skills to administer IBM© MQ queue managers on distributed operating systems, in the Cloud, or on the IBM© MQ Appliance. Overview After completing this course, you should be able to:Describe the IBM© MQ deployment optionsPlan for the implementation of IBM© MQ on-premises or in the CloudUse IBM© MQ commands and the IBM© MQ Explorer to create and manage queue managers, queues, and channelsUse the IBM© MQ sample programs and utilities to test the IBM© MQ networkEnable a queue manager to exchange messages with another queue managerConfigure client connections to a queue managerUse a trigger message and a trigger monitor to start an application to process messagesImplement basic queue manager restart and recovery proceduresUse IBM© MQ troubleshooting tools to identify the cause of a problem in the IBM© MQ networkPlan for and implement basic IBM© MQ security featuresUse accounting and statistics messages to monitor the activities of an IBM© MQ systemDefine and administer a simple queue manager cluster This course provides technical professionals with the skills that are needed to administer IBM© MQ queue managers on distributed operating systems and in the Cloud. In addition to the instructor-led lectures, you participate in hands-on lab exercises that are designed to reinforce lecture content. The lab exercises use IBM© MQ V9.0, giving you practical experience with tasks such as handling queue recovery, implementing security, and problem determination. Note: This course does not cover any of the features of MQ for z/OS or MQ for IBM© i. Course introductionIBM© MQ reviewIBM© MQ installation and deployment optionsCreating a queue manager and queuesExercise: Using commands to create a queue manager and queuesIntroduction to IBM© MQ ExplorerExercise: Using IBM© MQ Explorer to create queue managers and queuesTesting the IBM© MQ implementationExercise: Using IBM© MQ sample programs to test the configurationImplementing distributed queuingExercise: Connecting queue managersIBM© MQ clientsExercise: Connecting an IBM© MQ clientImplementing trigger messages and monitorsExercise: Implementing a trigger monitorDiagnosing problemsExercise: Running an IBM© MQ traceImplementing basic security in IBM© MQExercise: Controlling access to IBM© MQBacking up and restoring IBM© MQ messages and object definitionsExercise: Using a media image to restore a queueExercise: Backing up and restoring IBM© MQ object definitionsIntroduction to queue manager clustersExercise: Implementing a basic clusterMonitoring and configuring IBM© MQ for performanceExercise: Monitoring IBM© MQ for performanceCourse summary

InDesign face to face training customised and bespoke.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online. Learn to code a Password Validator in 1 hour.