Our leading course has transformed the artificial intelligence (AI), machine learning (ML) and data science practice of the many managers, sponsors, key stakeholders, entrepreneurs and beginning data analytics and data science practitioners who have attended it. This course is an intuitive, hands-on introduction to ai, data science and machine learning, it's your artificial intelligence 101. The training focuses on central concepts and key skills, leaving you with a deep understanding of the foundations of ai and data science and even some of the more advanced tools used in the field. The course does not involve coding, or require any coding knowledge or experience.
This one-day workshop is aimed at current or aspiring leaders and managers of AI / machine learning teams and functions. The focus of the course is on the key concepts that are required to avoid the most common and far too frequent failures in AI projects and initiatives.
With the advent of automation, humans’ role has become to do what computers cannot. Many more white-collar workers—perhaps all of them—will end up “working with data” to some extent. This course for managers and workers without a strong quantitative background introduces a range of skills and applications related to critical thinking in such areas as forecasting, population measurement, set theory and logic, causal impact and attribution, scientific reasoning and the danger of cognitive biases. There are no prerequisites beyond high-school mathematics; this course has been designed to be approachable for everyone.
This course is for executives and managers who want to leverage analytics to support their most vital decisions and enable better decision-making at the highest levels. It empowers senior executives with skills to make more effective use of data analytics. It covers contexts including strategic decision-making and shows attendees ways to use data to make better decisions. Attendees will learn how to receive, understand and make decisions from a range of analytics methods, including visualisation and dashboards. They will also be taught to work with analysts as effective customers.
This course is a vital first step in the data literacy journey, and the one that introduces the most vital and basic skills of the effective 21st century professional or leader. Working with data is not just about manipulating software tools : it is first and foremost about effective reasoning, using all available information. As such, this course loads the key “software” into the most vital hardware of the business - the human professional, enabling them to reason effectively with data, and thus realise the value that data analytics promises, deriving more reliable and correct insights and making better decisions.
All participants in digital transformation will need to be digital business case literate in an automated, decision-focused future. This course is designed to increase non-expert level ability to competently turn data into concise data storytelling, and then teach them how to apply the right numbers afterwards to transform the story into a business benefit calculation, so that both parts are well understood by technical and business decision makers within a company. This course covers a broad range of business skills, including telling a concise story based on data (business storytelling), techniques to simplify and abstract complex situations and sharpening data stories to apply financial figures to the resulting business case.
R is the world’s most popular data mining and statistics package. It’s also free, and easy to use, with a range of intuitive graphical interfaces. This two-day course will introduce you to the R programming language, teaching you to create functions and customise code so you can manipulate data and begin to use R self-sufficiently in your work.
Python is a high-level, general-purpose language used by a thriving community of millions. Data-science teams often use it in their production environments and analysis pipelines, and it’s the tool of choice for elite data-mining competition winners and deep-learning innovations. This course provides a foundation for using Python in exploratory data analysis and visualisation, and as a stepping stone to machine learning.
Data science is the key to business success in the information economy. This workshop will teach you about best practices in deploying a data science capability for your organisation. Technology is the easy part; the hard part is creating the right organisational and delivery framework in which data science can be successful in your organisation. We will discuss the necessary skill sets for a successful data scientist and the environment that will allow them to thrive. We will draw a strong distinction between “Data R&D” and “Data Product” capabilities within an enterprise and speak to the different skill sets, governance, and technologies needed across these areas. We will also explore the use of open data sets and open source software tools to enable best results from data science in large organisations. Advanced data visualisation will be described as a critical component of a big data analytics deployment strategy. We will also talk about the many pitfalls and how to avoid them.