200 Intelligence courses in London

SQL Queries Course, 1-Day. Basic SQL syntax. This course is good for any database, covering standard SQL. Most attendees are in-work IT Professional. Private individuals are also very welcome.

This course covers the essential Excel data skills. Our course is interactive, instructor-led. This Excel Data course is on offered on intermediate level of Excel and concentrates on the Data Analytical capabilities of Excel. These concepts are daily used by data analysts and is a basic essential skill for data professionals. By the end, you'll be able to use Excel for analytics, data summaries, trends and statistics. You will create Excel data analytical spreadsheets and samples that you can use as examples at work.

The “ISO 42001:2023 Lead Auditor Course” integrates the principles of ISO 42001:2023, the International Standard for Artificial Intelligence Management, with the methodologies outlined in ISO 19011:2018, the Guidelines for Auditing Management Systems. The course equips participants with the skills and knowledge required to lead Artificial Intelligence audits effectively, ensuring compliance with ISO 42001:2023, and applies the principles of ISO 17011:2017 for conformity assessment bodies.

Pivot tables are really very easy to create, but very powerful. By using Excel pivot tables, one can get very interesting and valuable business intelligence from your data in very little time. This short session aims to give you the techniques to use this valuable Excel tool creatively. It is enough time to learn a lot about Excel Pivot Tables, but there is very little time for other questions.

Data Visualization Courses London. In this Power BI Course, you will learn how to translate data trends, summaries, statistics and insights from your data into powerful and inspirational visualizations This course is ideal for managers and data analysts who need to make business decisions based on data.

Business Intelligence Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

An in person London based workshop to help you build Emotional Connection. Our approach is based on helping individuals to rebuild their immense and beautiful capacity for emotional intimacy while also encouraging & fostering personal and psychological safety. We use a set of exercises that are canonical in training actors to deepen emotional connection on stage and screen. You will feel empowered to open up and & become vulnerable with others. The exercises are emotionally ‘light’ and yet powerful. You will not be asked or required to share anything personal. We will work with your imagination, your powers of make believe and ‘creatively play’ in order to show you how you embody changes to help you connect truthfully and genuinely. Overall, the workshop is designed to grow emotional awareness and to provide you with the tools to enable trust, emotional resilience and an expanded capacity for vulnerability which you can use and apply to any relationship whether social, professional or more intimate.

The “ISO 42001:2023 Lead Implementer Course” is designed to provide participants with the knowledge and skills necessary to lead the implementation of an Artificial Intelligence Management System based on ISO 42001:2023. This comprehensive course covers the key principles, requirements, and best practices for establishing and maintaining an effective Artificial Intelligence management system. Participants will learn how to develop, implement, and manage processes that comply with the ISO 42001 standard.

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led