1141 Courses delivered Online

Data Entry Administrator Diploma with Transcription and Translation Diploma Welcome to the Data Entry Administrator Diploma with Transcription and Translation. This multifaceted course aims to provide you with comprehensive skills in data entry, alongside a specialised focus on Transcription and Translation. The demand for professionals who can provide accurate and fast transcription and translation services is rapidly growing. This course prepares you to meet that demand head-on. Learning Outcomes: Gain foundational knowledge in Transcription basics. Understand the role of context in Transcription. Attain skills to improve Transcription accuracy. Master the tools used in Transcription and Translation. Acquaint yourself with the translation industry's dynamics. Develop strategies for effective translation. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Key Modules from Data Entry Administrator Diploma with Transcription and Translation Diploma: Basics of Transcription: Begin your journey by understanding the fundamentals of Transcription, the cornerstone for developing specialised skills in the field. Context in Transcription: Here, you'll delve into the nuances of context, learning how it influences the accuracy and effectiveness of Transcription. Transcription Accuracy: Accuracy is paramount in Transcription. This module will equip you with techniques to enhance your Transcription accuracy. Tools in Transcription: This module introduces you to the tools integral to Transcription, from software to hardware, to optimise your workflow. Translation Industry in the Realm of Transcription: An essential overview of the translation industry, explaining how Transcription skills can be effectively utilised within it. Translation Strategies Complementing Transcription: Finalize your training by learning the best strategies for translating content in a manner that complements your Transcription skills.

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.

If data had a fan club, analysts would be the VIP members. This 8-in-1 online bundle offers a structured dive into the data world—from input to insight. With modules in SQL, Python, Microsoft Access, Tableau, Google Analytics, and more, it covers the tools that analysts actually use when trying to make sense of endless spreadsheets. You’ll start with data entry foundations and move through analysis techniques, database management, and visualisation. The goal? To help you read, question, and communicate data without turning it into a maths lesson. Whether you’re new to analytics or brushing up on tools, this bundle is here to turn data into something slightly more interesting than... well, a spreadsheet. 🎯 Learning Outcomes: Understand core data analysis methods across common tools. Learn SQL for querying and managing structured data sets. Apply Python for basic data organisation and automation. Use Tableau and Google tools for visual data presentation. Gain data entry and database management understanding. Analyse online performance through Google Analytics platforms. 👤 Who is this Course For: Aspiring data analysts building core tool knowledge. Marketing professionals interested in online performance stats. Admins needing database and data entry foundations. Junior developers exploring data-related workstreams. Business analysts reviewing structured analysis methods. Freelancers handling data-heavy client tasks. Entrepreneurs reviewing user behaviour via Google tools. Graduates seeking online data training for job roles. 💼 Career Path (UK Average Salaries): Data Analyst – £38,000 per year Business Intelligence Analyst – £42,000 per year Data Entry Administrator – £24,000 per year SQL Analyst – £40,000 per year Marketing Data Analyst – £36,000 per year Analytics Coordinator – £34,000 per year

The Anti Money Laundering (AML): 8 in 1 Premium Courses Bundle helps learners navigate the world of financial transparency, audit trails, and those pesky fraudulent transactions. This content-rich bundle includes AML foundations, employment law, document control, purchase ledger insights, and financial/data analysis to keep your finance knowledge well-polished and compliant. You’ll also cover Excel skills relevant to data handling and the all-important risk mitigation mindset. This isn’t just about ticking legal boxes — it’s about understanding the landscape behind financial red flags. From analysing patterns to securing documents, this is the kind of learning that’s great for careers where trust, accuracy, and the occasional suspicious transaction log all go hand in hand. Learning Outcomes: Understand AML regulations and financial crime prevention strategies Learn how to analyse financial data for suspicious activity detection Explore employment law principles tied to financial conduct Gain insight into document control and risk management processes Study Excel for financial reporting and transaction tracking Learn purchase ledger operations in structured finance departments Who is this Course For: Professionals seeking AML knowledge in finance environments Data analysts interested in financial pattern recognition Office staff working with sensitive financial documentation Accounting learners with interest in legal financial oversight Individuals exploring fraud detection and finance auditing Excel users dealing with large volumes of financial data Bookkeepers and ledgers clerks handling transactional records HR or finance staff needing AML and employment law clarity Career Path (UK Average Salaries): AML Analyst – £35,000/year Financial Crime Assistant – £32,000/year Data Analyst (AML-Focused) – £36,500/year Compliance Support Officer – £33,000/year Purchase Ledger Clerk – £25,500/year Document Control Officer – £27,000/year

Microsoft Excel Complete Course - Beginner Intermediate & Advanced To make learning Microsoft Excel easier for you, we have thoughtfully bundled our three greatest courses: Microsoft Excel Beginners, Intermediate, and Advanced. At this price, you won't find a better deal anywhere else. One of the most popular applications for visualizing and analyzing data that has been created to date is Microsoft Excel. These days, practically every industry and household use this helpful program for personal purposes. Excel is used by business owners for a plethora of tasks, including data analysis, visualizing data, tracking hours worked, money, and statements. This Microsoft Excel Complete Course can be very helpful to you whether you are a newbie, have some training and experience with the program, or haven't used Excel in a long time and need a thorough refresher to develop your skills. After completing this course, you will be a proficient Excel user. In a short period of time, our simple lessons will impart the knowledge in a very easy way. There won't be a rush because you can study whenever you want and at your own speed. After completing the course, your confidence in using Excel will increase. Course Highlights Microsoft Excel Complete Course - Beginner Intermediate & Advanced is an award winning and the best selling course that has been given the CPD Certification & IAO accreditation. It is the most suitable course anyone looking to work in this or relevant sector. It is considered one of the perfect courses in the UK that can help students/learners to get familiar with the topic and gain necessary skills to perform well in this field. We have packed Microsoft Excel Complete Course - Beginner Intermediate & Advanced into 73 modules for teaching you everything you need to become successful in this profession. To provide you ease of access, this course is designed for both part-time and full-time students. You can become accredited in just 11 hours, 6 minutes hours and it is also possible to study at your own pace. We have experienced tutors who will help you throughout the comprehensive syllabus of this course and answer all your queries through email. For further clarification, you will be able to recognize your qualification by checking the validity from our dedicated website. Why You Should Choose Microsoft Excel Complete Course - Beginner Intermediate & Advanced Lifetime access to the course No hidden fees or exam charges CPD Accredited certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential. Who is this Course for? Microsoft Excel Complete Course - Beginner Intermediate & Advanced is CPD certified and IAO accredited. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic backgrounds. Requirements Our Microsoft Excel Complete Course - Beginner Intermediate & Advanced is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path You will be ready to enter the relevant job market after completing this course. You will be able to gain necessary knowledge and skills required to succeed in this sector. All our Diplomas' are CPD and IAO accredited so you will be able to stand out in the crowd by adding our qualifications to your CV and Resume. Microsoft Excel Complete Course - Beginner Intermediate & Advanced Microsoft Excel 2019 New Features Introduction to Microsoft Excel 2019 New Features 00:07:00 CONCAT 00:02:00 IFS 00:01:00 MAXIFS 00:01:00 MINIFS 00:01:00 SWITCH 00:02:00 TEXTJOIN 00:01:00 Map Chart 00:02:00 Funnel Chart 00:01:00 Better Visuals 00:06:00 Pivot Table Enhancements 00:02:00 Power Pivot Updates 00:01:00 Getting Started With Microsoft Office Excel Navigate the Excel User Interface 00:28:00 Use Excel Commands 00:28:00 Create and Save a Basic Workbook 00:19:00 Enter Cell Data 00:12:00 Use Excel Help 00:05:00 Performing Calculations Create Worksheet Formulas 00:15:00 Insert Functions 00:17:00 Reuse Formulas and Functions 00:17:00 Modifying A Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Formatting A Worksheet Apply Text Formats 00:16:00 Apply Number Format 00:08:00 Align Cell Contents 00:09:00 Apply Styles and Themes 00:12:00 Apply Basic Conditional Formatting 00:11:00 Create and Use Templates 00:08:00 Printing Workbooks Preview and Print a Workbook 00:10:00 Set Up the Page Layout 00:09:00 Configure Headers and Footers 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working With Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:24:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working With Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:06:00 Visualizing Data With Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:13:00 Using PivotTables And Pivot Charts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with Pivot Charts 00:08:00 Filter Data by Using Timelines and Slicers 00:11:00 Working With Multiple Worksheets And Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:06:00 Using Lookup Functions And Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:09:00 Sharing And Protecting Workbooks Collaborate on a Workbook 00:20:00 Protect Worksheets and Workbooks 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines And Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:09:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Excel Templates Excel Templates 00:00:00 Resources Microsoft Excel 2019 00:00:00 Assignment Assignment - Microsoft Excel Complete Course - Beginner Intermediate & Advanced 00:00:00

Overview This comprehensive course on Interactive Dashboards with Data Studio will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Interactive Dashboards with Data Studio comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Interactive Dashboards with Data Studio. It is available to all students, of all academic backgrounds. Requirements Our Interactive Dashboards with Data Studio is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 2 sections • 5 lectures • 02:41:00 total length •Module 01: Introduction to GDS: 00:36:00 •Module 02: Data Visualization: 01:29:00 •Module 03: Geo-visualization: 00:16:00 •Module 04: A Socio-Economic Case Study: 00:20:00 •Assignment - Interactive Dashboards with Data Studio: 00:00:00

This course bundle is made up of three separate certification courses: 1. PRINCE2® Foundation; 2. PRINCE2® Practitioner; 3. IASSC Lean Six Sigma Black Belt. The PRINCE2® Foundation And Practitioner course includes the official certification exams. By passing the Foundation and Practitioner exams, you will be an officially certified PRINCE2® Practitioner. The IASSC Lean Six Sigma Black Belt course includes the official IASSC Six Sigma Black Belt exam. By passing this exam, you will be officially certified by the IASSC as a Six Sigma Black Belt. You have 14 months to complete all of the courses in this bundle and take the exams. Read below to find out more about the courses contained within this bundle.

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

Data dashboards provide key information to stakeholders so that they can make informed decisions. While there are plenty of software solutions for building these essential data products, there is much less guidance on how to design dashboards to meet the diverse needs of users.  This course is for anyone who is building or implementing dashboards, and wants to know more about design principles and best practice. You could be using business intelligence software (such as Power BI or Tableau), or implementing bespoke solutions.  The course will give your team the ability to evaluate user needs and levels of understanding, make informed decisions about chart selections, and make effective use of interactivity dynamic data.  We’ll work with you before the course to ensure that we understand your organisation and what you’re hoping to achieve.  Sample learning content  Session 1: Data with a purpose Understanding the different types of dashboard. Information overload and other common dashboard pitfalls. Assessing user needs and levels of data fluency. Session 2: Planning a dashboard Assessing diverse user needs and levels of data fluency. Taking a User Experience (UX) approach to design and navigation. Applying an interative and collaborative approach to onboarding. Session 3: Graphs, charts and dials  Understanding how graphical perception informs chart choices. Making intelligent design choices to help users explore. Design principles for layout and navigation. Session 4: Using interactivity  Making effective use of filters to slice and dice data sets. Using layers of information to enable drilldown data exploration. Complenting dashboards with automated alerts and queries. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets. Testimonial “Alan was great to work with, he took us through the concepts behind data visualisation which means our team is now equipped for the future. He has a wide range of experience across the topic that is delivered in a clear, concise and friendly manner. We look forward to working with Alan again in the future.” John Masterson | Chief Product Officer | ImproveWell

Think libraries are just about stamping books? Think again. This bundle gets under the hood of modern library and information management—where cataloguing meets GDPR, and dusty shelves make way for digital systems. From document control to basic IT and data analysis, this bundle suits anyone working behind the scenes to keep information flowing neatly (and legally). Ideal for those who believe alphabetising can be an art form and spreadsheets deserve proper formatting. 🟪 Learning Outcomes: Manage library records using structured documentation methods. Apply GDPR principles to safeguard personal and public data. Organise and retrieve digital files using basic IT skills. Analyse usage data to support service development decisions. Maintain orderly systems for both physical and digital resources. Understand key tasks in library and information management. 🟪 Who Is This Course For: Library assistants supporting daily resource and data handling. Archive staff maintaining structured and secure records. Admins in educational or public library environments. Data handlers working in knowledge or resource centres. Entry-level staff in information management roles. Professionals dealing with document control and storage. Staff helping with catalogue management and updates. Anyone allergic to messy filing systems and loose ends. 🟪 Career Path (UK Average Salaries): Library Assistant – £22,000/year Document Controller – £27,000/year Information Support Officer – £26,000/year Records Management Assistant – £25,000/year Digital Archive Coordinator – £28,000/year Data Analyst (Library/Info Sector) – £30,000/year