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Payroll courses in London | Online Courses | Distance Learning Course Overview: Broken down into practical modules this course is a very popular and well-received introduction to moving from manual payroll to computerised payroll, and it incorporates all the new government requirements for RTI reporting Payroll is a vital role within any organisation. A career in payroll means specialising in a niche field with excellent progression opportunities. What support is available? Free high-quality course materials Tutorial support Highly equipped IT lab Student Discount with NUS card Exam fees and exam booking service Personalised individual study plan Specialist Career Management service State of the Art Virtual Learning Campus Free Sage Payroll Software Duration 6 Weeks Study Options Classroom Based - Osborne Training offers Daytime and Weekend sessions for Payroll Training Course from London campus. Online Live - Osborne Training offers Live Online sessions for Sage Payroll Training Classes through the Virtual Learning Campus. Distance Learning - Self Study with Study Material and access to Online study Material through Virtual Learning Campus. Benefits for Trainees Sage Payroll Qualifications open new doors to exciting careers, as well as extending payroll skills if you are currently employed. State of the Art Virtual Learning Campus Start your own payroll bureau Work in small businesses A payroll career can lead to great things Update your knowledge of Sage payroll Improve your employability prospects A career path into payroll Ideal Continuing Professional Development course Gain a qualification to boost your CV Option to gain IAB accredited qualification Start your training immediately without having to wait for the new term to begin Certification You will receive a certificate from Osborne Training once you finish the course. You have an option to get an IAB Certificate subject to passing the IAB exam or Sage certified exam. Syllabus Advanced processing of the payroll for employees Preparation and use of period end HMRC forms and returns preparation of internal reports Maintaining accuracy, security and data integrity in performing payroll tasks. Deductions - Pension schemes and pension contributions Processing the payroll -complex income tax issues Processing Payroll Giving Scheme Processing Statutory Adoption Pay (SAP) Advanced Income tax implications for company pension schemes Student Loan repayments Processing Holiday Payments Processing Car Benefit on to the Payroll System Attachment of Earnings Orders & Deductions from Earnings Orders Leavers with complex issues Advanced processing of statutory additions and deductions Recovery of statutory additions payments - from HMRC Completing the processing of the payroll Complex Reports and payments due to HMRC Introduction to Auto-enrolment Cost Centre Analysis Advanced, routine and complex payroll tasks Calculation of complex gross pay

Duration 3 Days 18 CPD hours This course is intended for Before taking this course delegates should already be familiar with basic analytics techniques, comfortable with basic data manipulation tools such as spreadsheets and databases and already familiar with at least one programming language Overview This course teaches delegates who are already familiar with analytics techniques and at least one programming language how to effectively use the programming language for three tasks: data manipulation and preparation, statistical analysis and advanced analytics (including predictive modelling and segmentation). Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. Outcomes: After completing the course, delegates will be capable of writing production-ready R code to perform advanced analytics tasks enabling their organisations make better, data-driven decisions. Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. Topic 1 Intro to our chosen language Topic 2 Basic programming conventions Topic 3 Data structures Topic 4 Accessing data Topic 5 Descriptive statistics Topic 6 Data visualisation Topic 7 Statistical analysis Topic 8 Advanced data manipulation Topic 9 Advanced analytics ? predictive modelling Topic 10 Advanced analytics ? segmentation

Duration 5 Days 30 CPD hours This course is intended for Project Team Members IT Support Team Members Advanced Business Analysts System Administrators Application Consultants Business Process Owners / Team Leads / Power Users Program / Project Managers Trainers Overview Learn how to design, configure, consolidate, and report with BPC Standard In this course, students learn all of the key steps to set up Consolidation based on the SAP Business Planning and Consolidation, version for SAP NetWeaver. SAP Business Planning and Consolidation Overview Describing SAP Business Planning and Consolidation Running Consolidation Tasks Implementing BPC Standard Consolidation Modeling Consolidation Structures and Reporting Configuring Environments and Dimensions Creating Models for Consolidation Creating Reports and Formats in the EPM Add-In Report on BPC Standard Data in Analysis for Office Data Collection and Preparation Collecting Transforming Data for Consolidation Scenarios Creating Consolidation Logic Configuring Reclassifications Configuring Balance Carryforward Managing Journals Consolidations and Eliminations Translating Local Currency Configuring Intercompany Matching and Booking Using the Ownership Manager Configuring Integration Rules Eliminating Intercompany Transactions Configuring Intercompany US Elimination Designing Management, Matrix, and Multiple Accounting Standard Solutions Describing Consolidation and Elimination Principles Consolidating Investments Describing Stage Consolidation Configuring Scope Variation Configuring Equity Pickup Consolidation Process Monitoring Configuring Work Status Using the Controls Monitor to Validate Data Configuring Consolidation Business Process Flows

Duration 3 Days 18 CPD hours This course is intended for This course is designed for anyone currently working on Agile-based projects or having experience with other forms of project management experience and want to add Agile PM skills and knowledge to their portfolio. Anyone with any experience in project-based work, either from the customer or supplier side can benefit from this course, including but not limited to: project manager, team leaders and managers or project employees. Overview AgilePM ™ certification is the result of collaboration between APMG-International and the DSDM Consortium. DSDM (Dynamic Systems Development Method) is the longest existing Agile method and the only Agile method aimed at managing Agile projects. It Has evolved over the years into a Project Framework, and AgilePM is a subset tailored to the Agile project manager. Students will be explained how the model is set up, how the different project activities and project roles are connected and how AgilePM handles project management. This course provides preparation for the Foundation exam of APMG. Training Day 1 - AgilePM Foundation Topics What is Agile? Choosing an appropriate Agile approach philosophy, principles and project variables preparing for success The DSDM Process Training Day 2 - AgilePM Foundation Topics The People ? DSDM Roles and Responsibilities The DSDM Products Key practices ? prioritization and timeboxes Training Day 3 - AgilePM Foundation Topics Planning and control throughout the lifecycle Other practices: facilitated workshops, modeling and iterative development

MojiTax is hosting an invaluable event for ADIT students aimed at unlocking the secrets to exam success. This engaging session is designed to provide insights into MojiTax's effective learning methodologies that have contributed to its impressive success rates. Attendees will benefit from expert discussions on Knowledge-Based Learning, and Exam Writing Techniques. Additionally, we will share motivational ADIT journies, highlighting the impactful benefits of MojiTax. This event represents a unique opportunity for ADIT candidates to enhance their exam preparation strategies, connect with a supportive community, and learn from those who have excelled. Video time: X hours Exams: X Author: MojiTax Level: Not Applicable Study time: 1 hour 01 Live session Open Event Link (2pm - 3pm London Time)

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced attendees who wish to learn and use basic machine learning algorithms and concepts. Students should have skills at least equivalent to the Python for Data Science courses we offer. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to Understand the main concepts and principles of predictive analytics Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms w with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This course provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. Hands-on Predictive Analytics with Python is a three-day, hands-on course that guides students through a step-by-step approach to defining problems and identifying relevant data. Students will learn how to perform data preparation, explore and visualize relationships, as well as build models, tune, evaluate, and deploy models. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seabor, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. The Predictive Analytics Process Technical requirements What is predictive analytics? Reviewing important concepts of predictive analytics The predictive analytics process A quick tour of Python's data science stack Problem Understanding and Data Preparation Technical requirements Understanding the business problem and proposing a solution Practical project ? diamond prices Practical project ? credit card default Dataset Understanding ? Exploratory Data Analysis Technical requirements What is EDA? Univariate EDA Bivariate EDA Introduction to graphical multivariate EDA Predicting Numerical Values with Machine Learning Technical requirements Introduction to ML Practical considerations before modeling MLR Lasso regression KNN Training versus testing error Predicting Categories with Machine Learning Technical requirements Classification tasks Credit card default dataset Logistic regression Classification trees Random forests Training versus testing error Multiclass classification Naive Bayes classifiers Introducing Neural Nets for Predictive Analytics Technical requirements Introducing neural network models Introducing TensorFlow and Keras Regressing with neural networks Classification with neural networks The dark art of training neural networks Model Evaluation Technical requirements Evaluation of regression models Evaluation for classification models The k-fold cross-validation Model Tuning and Improving Performance Technical requirements Hyperparameter tuning Improving performance Implementing a Model with Dash Technical requirements Model communication and/or deployment phase Introducing Dash Implementing a predictive model as a web application Additional course details: Nexus Humans Hands-on Predicitive Analytics with Python (TTPS4879) 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 Hands-on Predicitive Analytics with Python (TTPS4879) 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 4 Days 24 CPD hours This course is intended for IS Security Officers IS Managers Risk Managers Auditors Information Systems Owners IS Control Assessors System Managers Government Employees Overview Upon completion, Certified Information Systems Risk Manager students will be prepared to pass the CISRM exam.  Certified Information Systems Risk Manager, CISRM, course is made for IT and IS professionals who are involved with all aspects of risk management. Requests for this particular area of certification is growing fast in the employment sector. Recent high-profile breaches in both the public and private sectors have increased awareness for the need for Risk Management professionals. Mile2?s CISRM certification exam will test your knowledge in all areas of risk management. If you would like some training and test preparation before taking the Certified Information System Risk Manager Exam we offer the CISRM course as both a live class and a self-study combo. First, you will learn to assess a system, then implement risk controls. Finally, you will be able to monitor and maintain risk procedures. With this training, you will be able to identify risks associated with specific industries. After course completion, you will be able to design, implement, monitor and maintain risk-based, efficient and effective IS controls. Knowledge of all of these areas will be required to pass the CISRM exam. Course Outline The Big Picture Domain 1 ? Risk Identification Assessment and Evaluation Domain 2 ? Risk Response Domain 3 ? Risk Monitoring Domain 4 ? IS Control Design and Implementation

AAT Bookkeeping Course Online Overview If you want to become a certified bookkeeper with AATQB (AAT Qualified Bookkeeper) status, then you must complete the AAT bookkeeping course successfully. This bookkeeping course is broken down into two levels, Foundation Certificate in Bookkeeping Advanced Certificate in Bookkeeping Once you pass all 5 exams successfully, you can gain AATQB status giving you a leading edge to build a successful career in bookkeeping. Next steps after qualifying You will be awarded Foundation Certificate in Bookkeeping and Advanced Certificate in Bookkeeping from the Association of Accounting Technicians (AAT) once you have passed all the exams. Therefore, you will be eligible for Certified Bookkeeper Status. It gives you greater recognition and professional approval. What you will gain? Firstly, this course will help you develop your skills in double-entry bookkeeping and give you an understanding of management and administrative processes. You'll learn how to use manual bookkeepin systems and to work with the purchase ledger, sales ledger and general ledger. You would also get better understanding about VAT system and how to do VAT Return. You will be awarded with Foundation Certificate in Bookkeeping and Advanced Certificate in Bookkeeping from Association of Accounting Technicians (AAT) once you have passed all the exams. Therefore, you will be eligible for Certified Bookkeeper Status. It gives you greater recognition and professional approval. The AAT bookkeeping course covers the following areas: Bookkeeping transactions Bookkeeping Controls Advanced Bookkeeping Final Accounts Preparation Indirect Tax

AAT Bookkeeping Course Online Overview If you want to become a certified bookkeeper with AATQB (AAT Qualified Bookkeeper) status, then you must complete the AAT bookkeeping course successfully. This bookkeeping course is broken down into two levels, Foundation Certificate in Bookkeeping Advanced Certificate in Bookkeeping Once you pass all 5 exams successfully, you can gain AATQB status giving you a leading edge to build a successful career in bookkeeping. Next steps after qualifying You will be awarded with Foundation Certificate in Bookkeeping and Advanced Certificate in Bookkeeping from Association of Accounting Technicians (AAT) once you have passed all the exams. Therefore, you will be eligible for Certified Bookkeeper Status. It gives you greater recognition and professional approval. What you will gain? Firstly, this course will help you develop your skills in double entry bookkeeping and give you an understanding of management and administrative processes. You'll learn how to use manual bookkeepin systems and to work with the purchase ledger, sales ledger and general ledger. You would also get better understanding about VAT system and how to do VAT Return. You will be awarded with Foundation Certificate in Bookkeeping and Advanced Certificate in Bookkeeping from Association of Accounting Technicians (AAT) once you have passed all the exams. Therefore, you will be eligible for Certified Bookkeeper Status. It gives you greater recognition and professional approval. The AAT bookkeeping course covers the following areas: Bookkeeping transactions Bookkeeping Controls Advanced Bookkeeping Final Accounts Preparation Indirect Tax

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.