315 Conflict courses in Cardiff delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for The introductory-level course is geared for software developers, project managers, and IT professionals seeking to enhance their understanding and practical skills in version control and collaboration using GitLab. It's also well-suited for those transitioning from another version control system to GitLab, or those responsible for software development lifecycle within their organization. Whether you are an individual looking to boost your proficiency or a team leader aiming to drive productivity and collaboration, this course will provide the necessary expertise to make the most of GitLab's capabilities. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Gain a firm understanding of the fundamentals of Git and GitLab, setting a solid foundation for advanced concepts. Learn to effectively manage and track changes in your code, ensuring a clean and reliable codebase. Discover ways to streamline your daily tasks with aliases, stashing, and other GitLab workflow optimization techniques. Develop skills in creating, merging, and synchronizing branches, enabling seamless collaboration and version control. Equip yourself with the knowledge to use Git as a powerful debugging tool, saving time and effort when troubleshooting issues. Understand the basics of continuous integration and continuous deployment (CI/CD) in GitLab, helping you automate the software delivery process. Immerse yourself in the dynamic world of GitLab, a leading web-based platform for version control and collaboration, through our intensive two-day course, GitLab Quick Start. Version control systems, such as GitLab, are the backbone of modern software development, enabling teams to work cohesively and maintain a structured workflow. By mastering GitLab, you can improve efficiency, encourage collaboration, and ensure accuracy and reliability within your projects, adding significant value to your organization. Throughout the course you?ll explore various aspects of GitLab, starting from the fundamental principles of source code management to advanced concepts like rebasing and continuous integration/design. Key topics covered include Git and GitLab basics, reviewing and editing commit history, mastering GitFlow and GitLab Flow, branching and merging strategies, and understanding remote repositories. You'll also learn how to utilize Git as a debugging tool and explore the power of GitLab's built-in CI/CD capabilities. The core value of this course lies in its practical application. You'll learn how to effectively manage changes in code with GitLab, allowing you to maintain audit trails, create reproducible software, and seamlessly move from another version control system. Then you?ll learn how to enhance your workflow efficiency using aliases for common commands, saving changes for later use, and ignoring build artifacts. You?ll also explore GitLab's CI/CD, which will enable you to automate your software delivery process. These hands-on labs will walk you through creating, merging, and synchronizing remote branches, configuring Git, troubleshooting using Git as a debugging tool, and setting up GitLab Runner for CI/CD. Each lab is designed to simulate real-world projects, offering you a first-hand experience in managing and contributing to a version control system like GitLab. Introduction to Source Code Management The Core Principles of Change Management The Power to Undo Changes Audit Trails and Investigations Reproducible Software Changing code-hosting platform Moving from another version control system Git and GitLab Introduction and Basics Introduction to Git GitFlow GitLab Flow Trees and Commits Configuring Git Adding, Renaming, and Removing Files Reviewing and Editing the Commit History Reviewing the Commit History Revision Shortcuts Fixing Mistakes Improving Your Daily Workflow Simplifying Common Commands with Aliases Ignoring Build Artifacts Saving Changes for Later Use (Stashing) Branching Branching Basics Listing Differences Between Branches Visualizing Branches Deleting Branches Tagging Merging Merging Basics Merge Conflicts Merging Remote Branches Remote Repositories Remote Repositories Synchronizing Objects with Remotes Tracking Branches Centralizing and Controlling Access Introduction to GitLab Git Repositories on GitLab Daily Workflow Reviewing Branching and Merging Branch Review Merging Basics Rebasing Rebasing Basics Rebasing with Local Branches Rebasing with Remote Branches Interactive Rebasing Squashing Commits Getting Out of Trouble Git as a Debugging Tool Using the Blame Command to See File History Performing a Binary Search Continuous Integration / Continuous Design (CI/CD) How to install GitLab Runner Adding to our example project Breaking down .gitlab-ci.yml Adding .gitlab-ci.yml to our example project Deconstructing an advanced .gitlab-ci.yml file GitLab CI/CD web UI Optional: Resetting Trees Introduction to Resetting Resetting Branch Pointers Resetting Branches and the Index Resetting the Working Directory Making Good Use of the Reset Command Optional More on Improving Your Daily Workflow Interactively Staging Changes Optional: Including External Repositories Submodules Subtrees Choosing Between Submodules and Subtrees Workflow Management Branch Management

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

Are you tired of “rocky” relationships, bad dates or feeling lonely? Most of us have learned the hard way, the cost of getting a relationship wrong can be enormous. The rewards of getting it right are immeasurable! That is why, as a certified Relationship & Dating Coach, I help clients avoid the pitfalls and find lasting happiness. So, do you really want to do it right this time around? Take charge of your love lfie today and book a free confidential 30-minute introductory session.

Learn how create and structure enterprise projects and programmes. Course overview Duration: 2 days (13 hours) Our P6 Project Planning and Controls Fundamentals course is an intensive two day course aimed at experienced planners and project controllers who need to use Primavera to create and manage detailed plans. It includes creating EPS levels, projects, WBS levels and detailed activity and resource planning. Experience of project planning and scheduling techniques is essential. Objectives  By the end of the course you will be able to: Create a programme structure Create projects and set project properties Create programme milestones Create a Work Breakdown Structure (WBS) Create detailed plans including activities, links and resources Progress the schedule Manage actuals Customise layouts Use the reporting tools in Primavera Content Programme Management Creating EPS elements Defining the programme structure Navigating the EPS structure Finding programmes Project Management and WBS Creating projects Setting project properties Validating projects Assigning project codes Building a work breakdown structure Creating a WBS structure Creating WBS elements Work package management Top Down budgets Allocating top down budgets Budget change Programming milestones and activity planning Creating programme milestones Setting constraints Linking milestones Scheduling Using the schedule function Detailed activity planning Creating activities Relationship types Creating relationships Adding milestones Assigning activity codes Resourcing, workloads and baselining Resource types Creating resources Resource attributes Assigning resources Switching resources Split load resource assignment Reduced hours resource assignment Checking workload Reviewing workload Dealing with resource conflicts Assignments view Baselining Creating baselines Assigning baselines Working with layouts Creating layouts Customising columns Setting filters Sorting and grouping Changing the timescale Customising the Gantt Creating activity code breakdown structures Progressing the schedules Updating task status and remaining duration Setting the data date Monitoring and reporting Exporting and importing information Primavera standard reports Creating custom reports Creating portfolios Printing Printing your schedule Printing to other packages

Are you tired of “rocky” relationships, bad dates or feeling lonely? Most of us have learned the hard way, the cost of getting a relationship wrong can be enormous. The rewards of getting it right are immeasurable! That is why, as a certified Relationship & Dating Coach, I help clients avoid the pitfalls and find lasting happiness. So, do you really want to do it right this time around? Take charge of your love lfie today and book a free confidential 30-minute introductory session.