278 Modeling courses in Glasgow delivered Live Online

Duration 2 Days 12 CPD hours This course is intended for This training is ideally suited for data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities. It will also benefit system administrators and data engineers who wish to harness Elastic Stack's functionalities for efficient system logging, monitoring, and robust data visualization. With a focus on practical application, this course is perfect for those aspiring to solve complex data challenges in real-time environments across diverse industry verticals. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll explore: New features and updates introduced in Elastic Stack 7.0 Fundamentals of Elastic Stack including Elasticsearch, Logstash, and Kibana Useful tips for using Elastic Cloud and deploying Elastic Stack in production environments How to install and configure an Elasticsearch architecture How to solve the full-text search problem with Elasticsearch Powerful analytics capabilities through aggregations using Elasticsearch How to build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis How to create interactive dashboards for effective storytelling with your data using Kibana How to secure, monitor and use Elastic Stack's alerting and reporting capabilities The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. Geared for experienced data analysts, IT professionals, and software developers who seek to augment their data processing and analytics capabilities, Working with Elasticsearch will explore how to use Elastic Stack and Elasticsearch efficiently to build powerful real-time data processing applications. Throughout the two-day hands-on course, you?ll explore the power of this robust toolset that enables advanced distributed search, analytics, logging, and visualization of data, enabled by new features in Elastic Stack 7.0. You?ll delve into the core functionalities of Elastic Stack, understanding the role of each component in constructing potent real-time data processing applications. You?ll gain proficiency in Elasticsearch for distributed searching and analytics, Logstash for logging, and Kibana for compelling data visualization. You?ll also explore the art of crafting custom plugins using Kibana and Beats, and familiarize yourself with Elastic X-Pack, a vital extension for effective security and monitoring. The course also covers essentials like Elasticsearch architecture, solving full-text search problems, data pipeline building, and creating interactive Kibana dashboards. Learn how to deploy Elastic Stack in production environments and explore the powerful analytics capabilities offered through Elasticsearch aggregations. The course will also touch upon securing, monitoring, and utilizing Elastic Stack's alerting and reporting capabilities. Hands-on labs, captivating demonstrations, and interactive group activities enrich your learning journey throughout the course. Introducing Elastic Stack What is Elasticsearch, and why use it? Exploring the components of the Elastic Stack Use cases of Elastic Stack Downloading and installing Getting Started with Elasticsearch Using the Kibana Console UI Core concepts of Elasticsearch CRUD operations Creating indexes and taking control of mapping REST API overview Searching - What is Relevant The basics of text analysis Searching from structured data Searching from the full text Writing compound queries Modeling relationships Analytics with Elasticsearch The basics of aggregations Preparing data for analysis Metric aggregations Bucket aggregations Pipeline aggregations Substantial Lab and Case Study Analyzing Log Data Log analysis challenges Using Logstash The Logstash architecture Overview of Logstash plugins Ingest node Visualizing Data with Kibana Downloading and installing Kibana Preparing data Kibana UI Timelion Using plugins

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course is as follows: Cloud administrators Cloud solution architects Customer sales engineers DevOps engineers Sales engineers Systems engineers Technical solutions architects Overview After you complete this course the learner will be able to meet these overall objectives: Explain business and technical challenges of going to the cloud Understand benefits of an application-centric hybrid cloud multicloud management platform Navigate Cisco CloudCenter Suite architecture Understand Cisco CloudCenter Suite administrative capabilities including cloud management, multi-tenancy, governance, and policy enforcement Describe application lifecycle management and provisioning in cloud Describe how to use Cisco CloudCenter Suite to manage the workloads in multicloud CLDCCS, Mulitcloud Management with Cisco© CloudCenter Suite is a 3-day intensive training course that teaches you to securely design, automate, and deploy applications across multiple clouds while optimizing cost and compliance with comprehensive reporting, visibility, and policy-enforcement. Through a combination of lessons with hands-on lab exercises, you will learn to simplify the lifecycle management of multicloud applications, workflows, and their infrastructure. This course will help you: Acquire the advanced skills and techniques for API calls, that can deploy and manage workloads in multiple environments without having deep cloud expertise Learn provisioning and orchestration, cost management, and workload optimization by leveraging cloud management Understanding Cloud Transitions Overview of Traditional IT Introducing Cisco CloudCenter Suite Cisco CloudCenter Suite Definition Setting Up Cisco CloudCenter Workload Manager Artifact Repository Overview and Configuration Understanding User Administration and Multitenancy in Cisco CloudCenter Suite Cisco CloudCenter Suite User Roles Grasping Application Modeling in Cisco CloudCenter Workload Manager Model an Application Identifying Resource Placement Callouts and Lifecycle Actions in Cisco CloudCenter Workload Manager Resource Placement and Validation Callout Understanding Application Deployment Framework in Cisco CloudCenter Workload Manager Workload Manager Application Parameters Exploring Application Services in Cisco CloudCenter Workload Manager Application Services Framework Integrating Cisco CloudCenter Workload Manager with Cisco Application-Centric Infrastructure Configure CloudCenter Workload Manager for Cisco ACI Introducing Application Management in Cisco CloudCenter Workload Manager Cisco CloudCenter Workload Manager Actions Library Exploring Advanced Features in CloudCenter Workload Manager Scheduling an Application in Cisco CloudCenter Workload Manager Comprehending Policies and Tagless Governance in CloudCenter Workload Manager Cisco CloudCenter Workload Manager Policies Introducing Action Orchestrator and Cost Optimizer in Cisco CloudCenter Suite Action Orchestrator in Cisco CloudCenter Suite Additional course details: Nexus Humans Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) 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 Cisco Multicloud Management with Cisco CloudCenter Suite (CLDCCS) 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 This intermediate course is designed for integration specialists and senior-level developers with experience in IBM Integration Bus application development. Overview After completing this course, you should be able to:Use event driven message processing to control the flow of messages by using message aggregation, message collections, message sequences, and time-sensitive nodesTransform data by using Microsoft .NET and XML stylesheetsAnalyze and filter information in complex XML documentsExtend DFDL message modelsUse message sets and the Message Repository Manager (MRM) parserProvide a message flow application as a web serviceRequest a web service from within a message flowDescribe how to implement WS-Addressing and WS-Security standards in IBM Integration BusCreate an integration serviceCreate and implement an IBM MQ request and response service definitionCreate and implement a database service definitionConfigure security-enabled message processing nodesCreate a decision service that implements business rules to provide routing, validation, and transformationExpose a set of integrations as a RESTful web serviceUse a global cache to store static dataRecord and replay data that a message flow application processesImplement publish and subscribe with IBM Integration BusDescribe the workload management options for adjusting the message processing speed, and controlling the actions that are taken on unresponsive flows and threadsConstruct user-defined patternsDescribe how IBM Integration Bus integrates with other IBM products such as IBM WebSphere Enterprise Service Bus and IBM DataPower Appliances This course focuses on using IBM Integration Bus to develop, deploy, and support platform-independent message flow applications and integration services. Course Outline Course introduction Using event driven processing nodes Exercise: Implementing message aggregation Transforming data with Microsoft .NET Transforming data with XSL stylesheets Analyzing XML documents Modeling complex data with DFDL Exercise: Extending a DFDL model Working with message sets and the MRM domain Supporting web services Exercise: Implementing web services Developing integration solutions by using integration services Exercise: Creating an integration service Connecting a database by using a discovered service Connecting IBM MQ by using a discovered service Exercise: Creating IBM MQ and database services Creating a decision service Exercise: Creating a decision service Developing integration solutions by using a REST API Using the global cache Implementing message flow security Exercise: Implementing IBM Integration Bus runtime security Implementing publish/subscribe Monitoring message flow events Exercise: Recording and replaying message flow data Managing the workload Creating patterns for reusability Extending IBM Integration Bus Course summary Additional course details: Nexus Humans WM676 IBM Integration Bus V10 Application Development II 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 WM676 IBM Integration Bus V10 Application Development II 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.

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OVERVIEW DIAD is a one-day, hands-on workshop for business analysts, covering the breadth of Power BI capabilities. The course focuses on five practical Labs and at the end of the day, attendees will better understand how to: Connect and transform data from a variety of data sources. Define business rules and KPIs. Explore data with powerful interactive visuals. Build stunning reports. Share their dashboards with their team business partners and publish them to the web. The course content is managed by the Power BI engineering team at Microsoft. There is no exam associated with the course. COURSE BENEFITS: Learn how to clean, transform, and load data from various sources Create and manage a data model in Power BI consisting of multiple tables connected with relationships Build Measures and other calculations in the DAX language to plot in reports Manage and share report assets to the Power BI Service WHO IS THE COURSE FOR? Data Analysts and Management Consultants with little or no experience of Power BI who wish to upgrade their knowledge to include Business Intelligence Analysts looking for a quick introduction to Power BI who don’t have the time for the full three day PL-300 course Marketers in data-intensive organisations who need new tools to build visually appealing, dynamic charts for their stakeholders to use LAB OUTLINE Lab 1 Accessing & Preparing The Data Load data from Excel and CSV sources Manipulate the data to prepare it for reporting Prepare tables in Power Query and load them into the data model Lab 2 Data Modelling And Exploration Create a range of different charts Highlight and cross-filter Create new groups and hierarchies Add new measures to the model Lab 3 Data Visualization Add conditional formatting to a report Add logos to a filter Import a custom visual Apply a custom theme Add bookmarks to the report to tell a story Lab 4 Publishing A Report And Creating A Dashboard Create a Workspace in the Power BI Service Publish a report to the Service Create a Dashboard and pin visuals to it Generate and view insights Lab 5 Collaboration Share a Dashboard Access a Dashboard on a Mobile Device

OVERVIEW Prerequisites—DIAD training or equivalent working experience This one-day course will cover using Power BI Desktop to import and shape data from a variety of sources. It will also walk through Power BI capabilities you can use to enhance the data model for your business users. The course covers key aspects of how to create a great data model to meet your business needs, various features in Power BI used to enhance data models so you can build great reports, and an introduction to DAX to create calculations. After completing this training, the attendees should be able to import data from a variety of data sources into Power BI, shape the data, create the data model, and write DAX functions to the Power BI model. COURSE BENEFITS: Understand the Power BI Desktop data model, its components and most effective schemas Describe concepts of calculated columns and measures Create queries using M Create calculations with DAX Understand the use of functions Create and optimize a data model Understand the consequences of data model design decisions WHO IS THE COURSE FOR? Power BI report developers who wish to improve the structure of their data models Power BI report developers who wish to use advanced features like parameters and M coding in Power Query Power BI practitioners who wish to optimise their models more effectively Attendees wishing to prepare thoroughly for the DAX In A Day course COURSE OUTLINE Module 1 Getting And Shaping The Data Understand what is meant by data model in the context of Power BI Understand the consequences of data model design decisions Understand consequences of Power BI’s data type handling Understand data connection options Module 2 Basic Data Modelling Understand basic data modelling Understand basic data model types Explore dimension tables and fact tables Explore data connections Module 3 Getting Started With M (Power Query Language) Get introduced to M Understand key components and syntax Module 4 Understanding Logic Operators Understand Transformations Understand Join operation Module 5 Introduction To DAX Get introduced to DAX and how can it be used Understand working with parameters and DAX (lab combining the previous module) Module 6 Working With Functions - DAX CALCULATE And More Understand working with functions Understand the basics of the CALCULATE formula Module 7 Modelling With Power BI & DAX Best Practice Gain familiarity with basic data modelling for business scenarios Learn some best practices for working with Power BI

he role of a CFO extends beyond day-to-day financial management and plays a pivotal role in preparing a business for an exit. The role of a CFO extends beyond day-to-day financial management and plays a pivotal role in preparing a business for an exit, whether it be through a merger, acquisition, or other strategic transaction. Here are some key points to consider: Financial Due Diligence: CFOs play a crucial role in conducting financial due diligence to assess the company’s financial health and identify any potential risks or issues. This involves reviewing financial statements, accounting practices, contracts, and other financial data to ensure accuracy and transparency. Valuation and Financial Modeling: CFOs work closely with the executive team, external advisors, and investment bankers to determine the company’s valuation. They develop financial models, assess growth projections, and analyze market comparables to arrive at a fair and realistic valuation range. Financial Documentation and Reporting: CFOs ensure that financial documentation and reporting are in order, accurate, and compliant with regulatory requirements. This includes preparing financial statements, management reports, and other financial disclosures necessary for the exit process. Negotiation and Deal Structuring: CFOs collaborate with legal and executive teams to negotiate the terms of the exit transaction. They provide financial insights and expertise to structure the deal in a way that maximizes value for the company and its stakeholders. Tax Planning and Optimisation: CFOs work closely with tax advisors to develop tax-efficient strategies for the exit transaction. They assess potential tax implications, explore tax-saving opportunities, and ensure compliance with applicable tax laws and regulations. Financial Communication and Investor Relations: CFOs play a critical role in communicating the financial aspects of the exit to internal and external stakeholders. They work with investor relations teams to ensure that key messages are effectively conveyed, providing transparency and clarity throughout the exit process. https://www.fdcapital.co.uk/podcast/the-vital-role-of-cfos-in-business-exit-preparation/ Tags Online Events Things To Do Online Online Seminars Online Business Seminars #business #cfo #preparation #exit #vital

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2 Days 12 CPD hours This course is intended for Sales engineers Account managers Networking engineers Technical and non-technical audiences Overview After taking this course, you should be able to: Understand the role that programmable infrastructure is having on the transition to the digital enterprise Describe Cisco DNA, its components and benefits, and explain a few use cases Describe the different technologies and solutions within the Cisco programmable infrastructure portfolio Describe Cisco DNA Center REST APIs Understand the functionality provided by Cisco WebEx Teams Describe Cisco CMX, services, and related APIs Describe the importance of DevOps culture within network operations in the shift to becoming a digital enterprise The Programming Use Cases for Cisco Digital Network Architecture (DNAPUC) v1.0 course highlights the shift toward the digital enterprise and examines the components, benefits, and use cases of Cisco Digital Network Architecture (Cisco DNA?) in an enterprise environment. You will learning about key platforms including Cisco© DNA Center, Cisco WebEx Teams?, Cisco Connected Mobile Experiences (CMX), and their related APIs. This course also covers open standards, tools, and network APIs that you can use to complement the Cisco DNA software portfolio, including Python, JavaScript Object Notation (JSON), Network Configuration Protocol (NETCONF), Representational State Transfer Configuration Protocol (RESTCONF), and Yet Another Next Generation (YANG). Understanding Programmable Infrastructure Digital Enterprise Four Pillars of Digitization Network Programmability and Automation What Should Be Automated? Quantifying Programmability and Automation for the Business Network Programmability and Automation Use Cases Introducing Cisco DNA Cisco DNA Overview Cisco DNA Components Benefits of Cisco DNA Cisco DNA Use Cases Describing Programmable Infrastructure Cisco Programmability Options Data Center Infrastructure Enterprise Network Programmability Streaming Telemetry Collaboration Management, Monitoring, and Analytics Describing Network APIs How APIs Enable Business Automation API Overview Data Encoding with JSON and XML RESTful APIs RESTCONF and NETCONF Overview Data Modeling with YANG Describing Cisco DNA Center APIs Cisco DNA Center Overview Cisco DNA Center Automation Enterprise Benefits Cisco DNA Center Applications and Use Cases Cisco DNA Center REST API Overview Case Study: Network Automation at Symantec Describing Cisco Collaboration APIs Cisco Webex Teams Overview Cisco Webex Teams Business Benefits Cisco Webex Teams API Overview Describing Cisco Mobility APIs Cisco CMX Overview Cisco CMX Programmability Business Benefits Cisco CMX Mobility Services API Overview Case Study: Victoria University and Cisco CMX Implementing DevOps Culture Within Network Operations Transition to DevOps CALMS Model (Culture, Automation, Lean, Measurement, Sharing) Role of Cisco Technology in the Transition to DevOps Additional course details: Nexus Humans Cisco Programming Use Cases for Cisco Digital Network Architecture v1.0 (DNAPUC) 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 Cisco Programming Use Cases for Cisco Digital Network Architecture v1.0 (DNAPUC) 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 Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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.