144 Courses in Cardiff delivered Live Online

Learn how to work with data using Python (the coding language) as a tool. Learn how data is structured and how to manipulate it into a usable, clean form ready for analysis. Work on a small real-life project from conception to solution, in a team or on your own.

Are you looking to enter the dynamic world of real estate? Our course is designed to equip you with the knowledge and tools you need to communicate effectively with real estate professionals and develop key skills in real estate investment strategy and analytics. At the end of the course, you'll be able to read and interpret real estate market reports, and have a firm grasp of how iconic buildings, cities, and companies fit into the overall picture of the real estate sector. On this course, you will… Become familiar with the players, structure, general terminology and overall needs of Real Estate. Learn what is Real Estate and why it is different from other asset classes Get to grips with the overall size and structure of the UK Real Estate Market Learn and analyse the links between the different parts of the property market Understand who works in the Real Estate Market, their qualifications and their job descriptions Recognise how and when to use basic real estate concepts: Rent, Value, Yield, Risk and Return, etc… Learn how to read a real estate market report Understand how current affairs, politics and economics affects Real Estate Investment Use household names and iconic companies, cities and buildings to help consolidate your appreciation of this exciting sector Who will benefit from this course: Graduates or undergraduates studying economics, finance. Professionals working in Marketing or Accounting teams within Real Estate firms. APC students. Anyone interested in Real Estate. School leavers/A-Level Students looking to gain an understanding of Real Estate. Non cognate students who wish to transfer into Real Estate/Finance careers. Course Outline Module 1: What is and why buy Real Estate? The property Market The Size and Structure of the UK property market The impact of Real Estate in the Economy Module 2: The Real Estate Market System The Space Market The Asset Market The Development Market Module 3: How to value Real Estate An Introduction to Financial Mathematics The difference between Price, Value and Worth Property Yield Conventional Valuation Methods Module 4: How to read a Real Estate Market Report Property Market Indicators: Stock Indicators Property Market Indicators: Investment Indicators Module 5: Who works in Real Estate? The build Environment by Cobalt Recruitment Rea; Estate Agents Examples of Real Estate Market Agents CVs Real Estate Network

This course is designed for those already using Power BI Desktop and are ready to work with more comprehensive elements of analysing and reporting in Power BI. The course maintains a balanced look at data analysis including the Power Query Editor, with a deep dive into writing DAX formulas, and enhanced dashboard visualisations. The aim of this course is to provide a more complete understanding of the whole Power BI analytics process, by working with business examples that will equip you with the necessary skills to output comprehensive reports and explore Power BI's analytical capabilities in more depth. 1 The Query Editor Grouping rows in a table Split row by delimiter Add days to determine deadlines The query editor 2 Fuzzy Matching Joins Matching inconsistencies by percentage Matching with transformation table 3 The Query Editor M Functions Adding custom columns Creating an IF function Nested AND logics in an IF function 4 DAX New Columns Functions Including TRUE with SWITCH Using multiple conditions The FIND DAX function The IF DAX function Logical functions IF, AND, OR 5 Editing DAX Measures Making DAX easier to read Add comments to a measure Using quick measures 6 The Anatomy of CALCULATE Understanding CALCULATE filters Add context to CALCULATE with FILTER Using CALCULATE with a threshold 7 The ALL Measure Anatomy of ALL Create an ALL measure Using ALL as a filter Use ALL for percentages 8 DAX Iterators Anatomy of iterators A closer look at SUMX Using RELATED with SUMX Create a RANKX RANKX with ALL 9 Date and Time Functions Overview of functions Create a DATEDIFF function 10 Time Intelligent Measures Compare historical monthly data Create a DATEADD measure Creating cumulative totals Creating cumulative measures Visualising cumulative totals 11 Visualisations In-Depth Utilising report themes Applying static filters Group data using lists Group numbers using bins Creating heatmaps Comparing proportions View trends with sparklines 12 Comparing Variables Visualising trendlines as KPI Forecasting with trendlines Creating a scatter plot Creating dynamic labels Customised visualisation tooltips Export reports to SharePoint

SQL for Data Science, Data Analytics and Data Visualization Course Overview: This course offers a comprehensive introduction to SQL, designed for those looking to enhance their skills in data science, data analytics, and data visualisation. Learners will develop the ability to work with SQL databases, efficiently query and manage data, and apply these techniques for data analysis in both SQL Server and Azure Data Studio. By mastering SQL statements, aggregation, filtering, and advanced commands, learners will be equipped with the technical skills required to manage large datasets and extract meaningful insights. The course provides a solid foundation in data structures, user management, and working with multiple tables, culminating in the ability to perform complex data analysis and visualisation tasks. Course Description: This course covers a broad range of topics essential for anyone working with data in a professional capacity. From setting up SQL servers to mastering database management tools like SQL Server Management Studio (SSMS) and SQL Azure Data Studio, the course provides a thorough grounding in SQL. Learners will gain expertise in data structure statements, filtering data, and applying aggregate functions, as well as building complex SQL queries for data analysis. The course also includes instruction on SQL user management, group by statements, and JOINs for multi-table analysis. Key topics such as SQL constraints, views, stored procedures, and database backup and restore are also explored. The course incorporates SQL visualisation tools in Azure Data Studio, empowering learners to visualise data effectively. By the end of the course, learners will be proficient in SQL queries, data manipulation, and using Azure for data analysis. SQL for Data Science, Data Analytics and Data Visualization Curriculum: Module 01: Getting Started Module 02: SQL Server Setting Up Module 03: SQL Azure Data Studio Module 04: SQL Database Basic SSMS Module 05: SQL Statements for DATA Module 06: SQL Data Structure Statements Module 07: SQL User Management Module 08: SQL Statement Basic Module 09: Filtering Data Rows Module 10: Aggregate Functions Module 11: SQL Query Statements Module 12: SQL Group By Statement Module 13: JOINS for Multiple Table Data Analysis Module 14: SQL Constraints Module 15: Views Module 16: Advanced SQL Commands Module 17: SQL Stored Procedures Module 18: Azure Data Studio Visualisation Module 19: Azure Studio SQL for Data Analysis Module 20: Import & Export Data Module 21: Backup and Restore Database (See full curriculum) Who is this course for? Individuals seeking to enhance their data management and analysis skills. Professionals aiming to progress in data science, data analytics, or database administration. Beginners with an interest in data analysis and SQL databases. Anyone looking to gain expertise in SQL for Azure and SQL Server environments. Career Path: Data Analyst Data Scientist Database Administrator SQL Developer Business Intelligence Analyst Data Visualisation Specialist

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is people who are moving into a database role, or whose role has expanded to include database technologies. Developers that deliver content from SQL Server databases will also benefit from this material. Overview Describe key database concepts in the context of SQL Server Describe database languages used in SQL Server Describe data modeling techniques Describe normalization and denormalization techniques Describe relationship types and effects in database design Describe the effects of database design on performance Describe commonly used database objects This three-day instructor-led course is aimed at people looking to move into a database professional role or whose job role is expanding to encompass database elements. The course describes fundamental database concepts including database types, database languages, and database designs. This course updates and replaces course 10985C previously published under the same title. 1 - Introduction to databases Introduction to Relational Databases Other Databases and Storage Data Analysis SQL Server Database Languages 2 - Data Modeling Data Modelling Designing a Database Relationship Modeling 3 - Normalization Fundamentals of Normalization Normal Form Denormalization 4 - Relationships Introduction to Relationships Planning Referential Integrity 5 - Performance Indexing Query Performance Concurrency 6 - Database Objects Tables Views Stored Procedures, Triggers and Functions Additional course details: Nexus Humans 55313 Administering Configuration Manager, Part 1: Fundamentals and Asset Management 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 55313 Administering Configuration Manager, Part 1: Fundamentals and Asset Management 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 Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context. Overview By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. In this course you will start with the absolute basics of Python, focusing mainly on data structures. Then you will delve into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python.This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets. Introduction to Data Structure using Python Python for Data Wrangling Lists, Sets, Strings, Tuples, and Dictionaries Advanced Operations on Built-In Data Structure Advanced Data Structures Basic File Operations in Python Introduction to NumPy, Pandas, and Matplotlib NumPy Arrays Pandas DataFrames Statistics and Visualization with NumPy and Pandas Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame Deep Dive into Data Wrangling with Python Subsetting, Filtering, and Grouping Detecting Outliers and Handling Missing Values Concatenating, Merging, and Joining Useful Methods of Pandas Get Comfortable with a Different Kind of Data Sources Reading Data from Different Text-Based (and Non-Text-Based) Sources Introduction to BeautifulSoup4 and Web Page Parsing Learning the Hidden Secrets of Data Wrangling Advanced List Comprehension and the zip Function Data Formatting Advanced Web Scraping and Data Gathering Basics of Web Scraping and BeautifulSoup libraries Reading Data from XML RDBMS and SQL Refresher of RDBMS and SQL Using an RDBMS (MySQL/PostgreSQL/SQLite) Application in real life and Conclusion of course Applying Your Knowledge to a Real-life Data Wrangling Task An Extension to Data Wrangling

Duration 4 Days 24 CPD hours This course is intended for A Dynamics 365 Customer Engagement Functional Consultant is responsible for performing discovery, capturing requirements, engaging subject matter experts and stakeholders, translating requirements, and configuring the solution and applications. The Functional Consultant implements a solution using out-of-the-box capabilities, codeless extensibility, application, and service integrations. Overview Install and configure the customer service app Identify common customer service scenarios Complete a case resolution process Analyze customer service data Automate case management record processing Create and use knowledge articles Create and use entitlements and service level agreements Microsoft Dynamics 365 for Customer Service offers any organization an opportunity for customer success. Using tools such as automatic case creation and queue management frees up time to dedicate where a greater impact can be made, directly with customers. Our team of globally recognized experts take students step by step, from creating cases, to interacting with customers, to resolving those cases. Once those cases are resolved, students will learn from data analysis the key details to help resolve similar cases faster or avoid new issues altogether. Customer Service Overview Lesson 1: Create case records Lesson 2: Related service apps Lesson 3: Analytics for service Lesson 4: AI for service Lesson 5: Configuring customer service Lesson 6: Module summary Case Management Lesson 1: Case management overview Lesson 2: Creating case records Lesson 3: Queue management Lesson 4: Case routing Lesson 5: Resolving cases Lesson 6: Module summary Service Level Agreements and Entitlements Lesson 1: SLA and entitlement overview Lesson 2: Create and manage entitlements Lesson 3: Create and manage S Knowledge Management Lesson 1: Knowledge management overview Lesson 2: Authoring and organizing Lesson 3: Use knowledge content Lesson 4: Manage knowledge content Lesson 5: Module summary Additional course details: Nexus Humans MB-230T01 Dynamics 365 for Customer Engagement for Customer Service 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 MB-230T01 Dynamics 365 for Customer Engagement for Customer Service 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.

Course Overview The "Microsoft Excel Complete Course" is designed to equip learners with the essential skills to master Microsoft Excel, one of the most widely used tools in data analysis and business operations. This course covers a comprehensive range of topics, including Excel's new features, formula creation, data visualisation, and workbook management. It offers practical knowledge that will help learners work more efficiently, whether they are managing large datasets, analysing trends, or presenting information. By the end of this course, learners will be confident in using Excel for various business tasks, gaining a strong foundation for further professional development. Course Description This course covers all key aspects of Microsoft Excel, from the basics to advanced techniques. Learners will explore Excel’s new features in the 2019 version, as well as how to perform calculations, modify worksheets, and apply formatting. The course delves into functions, lists, and data analysis tools, including PivotTables and charts. Learners will also learn how to work with multiple worksheets and workbooks, use lookup functions, and automate workbook functionality. With a focus on essential Excel tools and techniques, learners will gain the ability to efficiently manage and analyse data for business or personal use. Course Modules Module 01: Microsoft Excel 2019 New Features Module 02: Getting Started with Microsoft Office Excel Module 03: Performing Calculations Module 04: Modifying a Worksheet Module 05: Formatting a Worksheet Module 06: Printing Workbooks Module 07: Managing Workbooks Module 08: Working with Functions Module 09: Working with Lists Module 10: Analyzing Data Module 11: Visualizing Data with Charts Module 12: Using PivotTables and PivotCharts Module 13: Working with Multiple Worksheets and Workbooks Module 14: Using Lookup Functions and Formula Auditing Module 15: Sharing and Protecting Workbooks Module 16: Automating Workbook Functionality Module 17: Creating Sparklines and Mapping Data Module 18: Forecasting Data (See full curriculum) Who is this course for? Individuals seeking to improve their data management and analysis skills. Professionals aiming to enhance their productivity in Excel for business applications. Beginners with an interest in data analysis or office administration. Anyone looking to build a strong foundation in Excel for career advancement. Career Path Data Analyst Financial Analyst Office Administrator Project Manager Business Analyst Operations Manager Administrative Assistant HR Specialist

Course Overview This comprehensive Data Analytics course provides an in-depth exploration of data analysis, covering the essential principles and techniques used to extract valuable insights from data. Learners will engage with core concepts, such as data mining, statistical analysis, and visualisation, enabling them to make informed decisions and drive business outcomes. By the end of the course, participants will have the skills to analyse and interpret data, apply analytical tools effectively, and present their findings clearly. This course equips learners with the necessary tools to understand and leverage data in various professional settings, adding significant value to their career prospects. Course Description The Data Analytics course covers a wide range of topics, including the fundamentals of data analysis, statistical methods, and various data visualisation techniques. Learners will explore essential tools such as Excel and specialised software, while gaining a deep understanding of how to collect, store, and process data effectively. Emphasis is placed on developing the analytical mindset required to interpret data accurately and draw actionable insights. This course is designed to ensure learners can confidently navigate the world of data analytics and apply their knowledge in diverse industries, enhancing their problem-solving and decision-making abilities. Course Modules Module 01: Introduction to the World of Data Module 02: Basics of Data Analytics Module 03: Statistics for Data Analytics Module 04: Actions Taken in the Data Analysis Process Module 05: Gathering the Right Information Module 06: Storing Data Module 07: Data Mining Module 08: Excel for Data Analytics Module 09: Tools for Data Analytics Module 10: Data-Analytic Thinking Module 11: Data Visualisation That Clearly Describes Insights Module 12: Data Visualisation Tools (See full curriculum) Who is this course for? Individuals seeking to enhance their analytical skills for data-driven decision-making. Professionals aiming to transition into data analytics or enhance their data-related roles. Beginners with an interest in understanding data and its applications across industries. Business professionals seeking to leverage data for strategic growth. Career Path Data Analyst Business Intelligence Analyst Data Scientist Market Research Analyst Operations Analyst Financial Analyst Business Analyst Data Visualisation Specialist

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