297 History courses in Reading delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level course, designed for anyone wanting to learn Linux. Attendees should be comfortable working with computers and the command line, but no other specific skills are required to attend. Overview This skills-focused course is about 50% lab to lecture ratio, combining expert instructor-led discussions with practical hands-on labs that emphasize current techniques, best practices and standards. Working in a hands-on lab environment, guided by our expert practitioner, attendees will explore The Design of Linux Basic Operations File System Basics Wildcards File and Directory Permissions Working with files Executing Programs Using find Filters and other useful commands The vi editor Customizing the user environment Networking/Communications Backups and archiving This hands-on course provides you with an essentials-level foundation in core skills for using any version of Linux. This course focuses on essential skills that ordinary users might use daily when working with Linux. The Design of Linux A brief history of Linux The Linux design philosophy Linux architecture Basic Operations Logging in and out The general form of a Linux command Common commands Using man pages Essential commands File System Basics The Linux directory structure Standard directories Relative and absolute pathnames Legal file names Navigating the filesystem Wildcards Matching one character Matching many characters Shortcuts Wildcard gotchas Wildcards and ls File and Directory Permissions Viewing permissions File permissions Directory permissions Setting defaults Changing permissions Keeping data secure Working with files Viewing contents Identifying file contents Copying and moving Deleting Using symbolic links Executing Programs Redirecting STDOUT Redirecting STDERR Redirecting STDIN Creating pipelines Processes attributes Listing processes Killing processes Foreground & background processes Using find Syntax Finding by name, type, or size Combining tests Finding by size, owner, or timestamps Using xargs with find Other find options Filters and other useful commands What is a filter? cat: a generic filter head and tail grep sort wc other interesting filters The vi editor Why vi? Basic vi operations: navigating, adding, deleting Advanced operations: buffer management, search and replace, configuration options Customizing the user environment About shells Shell startup files Shell variables Search path Aliases Simple shell scripts Networking/Communications Reading and sending mail Remote login Remote file transfer Other network utilities (ping, finger, etc) Backups and archiving Checking space used or available Creating tar archives Viewing and extracting files from archives Compression utilities Working with windows

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Sage 50 Computerised Accounting / Bookkeeping Training - Fast Track Overview: If you're looking to gain competency in the world's most popular bookkeeping software, the Sage 50 Computerised Accounting course will teach everything you need to know, while helping you gain a recognised qualification. This course is designed to provide individuals from beginner to advanced knowledge of bookkeeping and Sage 50 accounts. It is intended for individuals who aim to improve career prospects and to be able to better financial management and control of the business. This course covers Level 1-3 of Sage 50 Bookkeeping/Accounting Training. Every business, no matter how large or small, is required by law to 'keep books'. Therefore, Bookkeepers play a vital role within organisations; ensuring records of individual financial transactions are accurate, orderly, up to date and comprehensive. If you are organised and methodical, like working through documents and enjoy seeing a set of figures add up properly, then bookkeeping is the career for you. You will receive a CPD Completion certificate from Osborne Training once you finish the course. Then, you have an option to attain a Certificate from SAGE(UK) subject to passing the exams. Level 1 Working with Sage 50 Accounts Program Basics. Creating Account names, Numbers & Bank Payments Financials Bank Reconciliations Generating Customers Invoices Monitoring Customer Activity Generating Product Invoices & Credit Notes Compiling & Sending Customer Statements Creating Customer Receipts & Purchase Invoices Supplier Payments Managing Recurring Entries Generating Reports & Information The Active Set-Up Wizard VAT Changes. Level 2 An overview of the Sage program Entering opening balances, preparing and printing a trial balance Creating customer records Creating supplier records Setting up opening assets, liabilities and capital balances, Producing routine reports Checking data, Entering supplier invoices Posting error corrections, amending records Invoicing, generating customer letters, entering new products, checking communication history Banking and payments, producing statements, petty cash Audit trails, correcting basic entry errors, reconciling debtors and creditors Creating sales credit notes, Processing purchase credit notes Preparing journals Verifying Audit Trail Purchase orders, processing sales orders Processing Trial Balance Creating Backups Restoring data Writing-off bad debts Level 3 Creating a Chart of Accounts to Suit Company Requirements Sole Trader Accounts preparation The Trial Balance preparation Errors in the Trial Balance Disputed Items Use of the Journal Prepare and Process Month End Routine Contra Entries The Government Gateway and VAT Returns Bad Debts and Provision for Doubtful Debts Prepare and Produce Final Accounts Management Information Reports Making Decisions with Reports Using Sage The Fixed Asset Register and Depreciation Accruals and Prepayments Cash Flow and Forecast Reports Advanced Credit Control

Duration 5 Days 30 CPD hours This course is intended for This course is intended for students who want to gain knowledge of basic networking components, TCP/IP, and related services Overview Upon successful completion of this course, students will be able to identify different types of networks, understand TCP/IP protocols, subnetting, name resolution, and configuring various related services This course will introduce students to different types of network environments, understand the processes involved with TCP/IP-based networking, and installing and configuring related services such as DHCP, DNS, Active Directory, and VPNs Basic Network Infrastructure Network Architecture Standards Local Area Networking Wide Area Networking Wireless Networking Connecting Network Devices OSI Model Networking Hardware Introduction to TCP/IP History of TCP/IP TCP/IP Terminology TCP/IP Components in Windows Architectural Overview of TCP/IP TCP/IP Protocol Suite Internet Layer Protocols Transport Layer Protocols IP Addressing IPv4 Addressing IPv6 Addressing Subnetting Subnetting for IPv4 Subnetting for IPv6 IP Routing IP Routing Overview IPv4 Routing Dynamic Host Configuration Protocol DHCP Overview How DHCP Works Windows-based DHCP DHCP Relay Agent Host Name Resolution TCP/IP Naming Schemes Name Resolution Process Domain Name System Overview The Domain Name System Name Resolution Name Server Roles Resource Records Zone Transfers Windows Support for DNS Active Directory Fundamentals DNS Server in Windows Active Directory Integration Windows Internet Name Service Introduction to WINS How WINS Works WINS Client and Server Configuration Virtual Private Networking Virtual Private Networking Overview VPN Protocols VPN Server Installation Troubleshooting TCP/IP Basic Steps Windows Troubleshooting Tools Troubleshooting IPv4 Additional course details: Nexus Humans Network Fundamentals and Implementing TCP/IP 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 Network Fundamentals and Implementing TCP/IP 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.

Read and discuss these two gripping stories of race, identity and sexuality Highlights Join this book club and gain extra motivation to read in English 7 hours of live classes to help you develop fluent speaking in English Read and discuss these important novels about race, identity and sexuality Be corrected by an expert English teacher to remove errors and mistakes Practise and develop your English online in this advanced course featuring Passing (1928) and Giovanni's Room (1956). Each week you read some chapters, discuss them in class and improve specific areas of vocabulary or grammar while also examining literary aspects of the novel. Personalised feedback improves your grammar, vocabulary and pronunciation. The Book Club books Passing by Nella Larsen: Clare Kendry "passes" as a white woman. She is married to a white man who is unaware of her African-American heritage. On meeting her childhood friend Irene, both women examine and reassess their marriages, confronting their past lies & fears for the future. Nella Larsen's intense, gripping story & insight into identity established her as a key author of America's Harlem Renaissance. Giovanni's Room by James Baldwin: David, a young American in 1950s Paris, plans to get married. However, while waiting for his fiancée to return from holiday, he meets Giovanni, a handsome Italian barman, starting a passionate affair. Tortured by his sexual identity, he has to decide who he is and who to spend his life with. 'Audacious... remarkable... elegant and courageous' Caryl Phillips 'Gorgeous, fearless, tempered by dark knowledge and pain ... the greatest American prose stylist of his generation' Colm Tóibín Geoff says: "These two short novels are both important contributions to literature by black writers. Passing (1929) established Nella Larson as one of the most important black female novelists in American history. Recently made into a Netflix film, Passing is the second and last of Larson's novels, and considered a classic work. She was a pioneer in writing about sexuality, race and the secret suffering of women. James Baldwin's powerful and controversial second novel is his most sustained treatment of sexuality, and a classic of gay literature."

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Developers responsible for developing Deep Learning applications Developers who want to understand concepts behind Deep Learning and how to implement a Deep Learning solution on AWS Overview This course is designed to teach you how to: Define machine learning (ML) and deep learning Identify the concepts in a deep learning ecosystem Use Amazon SageMaker and the MXNet programming framework for deep learning workloads Fit AWS solutions for deep learning deployments In this course, you?ll learn about AWS?s deep learning solutions, including scenarios where deep learning makes sense and how deep learning works. You?ll learn how to run deep learning models on the cloud using Amazon SageMaker and the MXNet framework. You?ll also learn to deploy your deep learning models using services like AWS Lambda while designing intelligent systems on AWS. Module 1: Machine learning overview A brief history of AI, ML, and DL The business importance of ML Common challenges in ML Different types of ML problems and tasks AI on AWS Module 2: Introduction to deep learning Introduction to DL The DL concepts A summary of how to train DL models on AWS Introduction to Amazon SageMaker Hands-on lab: Spinning up an Amazon SageMaker notebook instance and running a multi-layer perceptron neural network model Module 3: Introduction to Apache MXNet The motivation for and benefits of using MXNet and Gluon Important terms and APIs used in MXNet Convolutional neural networks (CNN) architecture Hands-on lab: Training a CNN on a CIFAR-10 dataset Module 4: ML and DL architectures on AWS AWS services for deploying DL models (AWS Lambda, AWS IoT Greengrass, Amazon ECS, AWS Elastic Beanstalk) Introduction to AWS AI services that are based on DL (Amazon Polly, Amazon Lex, Amazon Rekognition) Hands-on lab: Deploying a trained model for prediction on AWS Lambda Additional course details: Nexus Humans Deep Learning on AWS 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 Deep Learning on AWS 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 This certification is appropriate for anyone who is interested in working as a Scrum Master or for someone who is already a Scrum master in his organization. Scrum Master is an important role in any Scrum team and need not be a technology expert to be effective. Moreover, although Scrum is popular in the IT industry, it can be used effectively across different industries. The SBOK Guide, on which the SMC course is based on, can be used as an effective guide for implementation. Overview The participants will be prepared to take SMC™ certification exam and pass. Also they will be able to apply the concepts in their day to day job. This course guides & teaches Scrum practices to everyone involved in the project; clears impediments for the team; and, ensures that Scrum processes are being followed. Successful candidates will be awarded the Scrum Master Certified (SMC?) certification by SCRUMstudy after passing the included certification exam. The certification exam voucher is included in this course so you can take the exam at your convenience. Introduction Course Objectives Course Methodology Certification Schema Exam Format Overview of Agile Agile Manifesto Agile Principles What has Changed Agile Methods Overview of Scrum Definition and brief history of Scrum Why Scrum Scrum vs. Traditional Project Management Benefits of Scrum Overview of A Guide to the Scrum Body of Knowledge (SBOK? Guide) Framework of the SBOK? Guide Who uses the SBOK? Guide How to use the SBOK? Guide Scrum Flow Principles Empirical Process Control Self-organization Collaboration Value-based Prioritization Time-boxing Iterative Development Scrum Aspects Organization Business Justification Quality Change Risk Scrum Phases and Processes Initiate Plan and Estimate Implement Review and Retrospect Release Scaling Scrum Scaling Scrum for Large Projects Scaling Scrum for the Enterprise Transition to Scrum Mapping Traditional Roles To Scrum Maintaining Stakeholder Involvement Importance Of Executive Support Additional course details: Nexus Humans Scrum Master Certified (SMC) 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 Scrum Master Certified (SMC) 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 This course is designed for developers who want to learn about Git and GitHub. Overview Upon completion of this course, participants will be able to: ? Install and run Git ? Describe basic concepts of Git version control ? Work on multiple branches ? Optimize merging and fixing merge conflicts ? Create and manage GitHub repositories ? Collaborate using GitHub This hands-on course teaches participants how to integrate Git and GitHub into their daily command-line workflow. Git operations, customizations of Git functionality, and how to connect to Git via Eclipse are covered as well. Introduction Introduction to Version Control Systems The Birth of Git and Why Git? What is GitHub? GitHub Repository Concepts Getting Started With Git Installing and Running Git The Git command Line Configuration Files Creating your First Git Repository Staging Area Git Commit Viewing History Creating Aliases and Shortcuts Hands-on Lab Session Getting Started with GitHub Creating and Configuring a Repository in GitHub Uploading your Repository to GitHub Understand Repository?s Main Page Using the README Hands-on Lab Session File Management in Git Locally The Index File Classifications in Git Rename a File Delete a File Ignore Files using .gitignore File Hands-on Lab Session Collaboration on Pull Requests Cloning and Forking Repositories Creating a Pull Request Collaborating a Pull Request Merging on a Pull Request Working with Branches Hands-on Lab Session Integrating GitHub with Eclipse Introducing EGit Plugin Configuring GitHub in Eclipse Working with Eclipse Hands-on Lab Session Reviewing and Configuring a Project on GitHub Configuring a Repository Adding Collaborators Creating Organizations Managing Teams Introducing Issues Merging, Rebasing and Resolving Conflicts Merging Branches Git diff and Commit Ranges Working with Merge Conflicts Merge Strategies Introduction to Rebasing Rebasing Branches Reverting and Fixing Bad Commits Hands-on Lab Session Additional course details: Nexus Humans Learning Git and GitHub 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 Learning Git and GitHub 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.

When managers have too many decisions to make, it can have a serious impact on the speed and efficiency of the organisation. When those decisions are commercial ones, the results can wreak havoc with the bottom line. Often the problem arises when those below them or in operational areas of the organisation aren't equipped or allowed to make a decision for themselves. Issues get passed back up and that wastes time. This programme provides a solution, giving your entire team the skills to: And most importantly, they'll be able to do this in line with the broader aims and commercial objectives of the business. By the end of the programme participants will be able to: Fully appreciate the importance of effective decision-making in business Use the five-step 'Stop, Think, Act!' decision-making process Stop leaping to conclusions Really understand the situations and decisions they are dealing with Identify good options Evaluate those options Make decisions and then put them into action Apply these tools and techniques to all their decisions in future 1 Understanding the business we work in What are the critical factors in our business? What is the SWOT analysis for our business? 2 Understanding what decision-making is 3 Background Culture of 'having to be doing' To change things we have to think about it! We are paid to make decisions! 4 Recognise the opportunity to make a decision 5 The 'Stop, Think, Act!' technique 6 STOP! Recognise the opportunity to make a decision Don't leap to conclusions Get ready to think Initial questions:Is this my decision? (Do I have the authority?)Who is this going to affect? (Do they need to be included?)When do I need to make the decision? (What's the timeline?) 7 THINK! The 3 Cs - making sure we understand the decisions we have to make What is the context of this decision?What is the overall situation?Why is this decision important?What do we need to achieve?What will success look like? Do I have clarity about the decision I need to make?Can I write it down?Can I express it clearly in two sentences? What are the criteria?What are the critical commercial factors that we will use to select our options?What will we use to measure the business success? 8 ACT! Identifying options What data do I need to collect?Issues with today's overloadIdentifying what will help you Select optionsHow many options?Must match your criteriaMust achieve success'Decision compass' exercise Analyse optionsTabular methodRisk analysis (likelihood v effect)Head, heart and gut (is there any organisational history/bias that we are up against?) Making your decision Taking it to actionFirst actionsPlanning how to make it happen

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a batch data analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures