Innovation & Tech (CTO) Curriculum

Training Courses, Workshops and Seminars

Our CTO curriculum is aimed at innovation managers, research and development managers and others looking to educate themselves about the latest trends in technology across a broad range of fields.

Fundamentals of AI, Machine Learning, Data Science and Predictive Analytics

2021-09-28T06:17:23+00:00November 30th, 2018|Tags: , , , , |

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 fundamentals and key skills, leaving you with a deep understanding of the core concepts 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. As our leading course, it 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.

AI and Data Science for Managers and Executives

2022-02-14T06:00:47+00:00July 20th, 2019|Tags: , , , |

Improve your project’s chance of success by avoiding common failures in AI and data science projects. 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.

Data Literacy for Everyone

2021-09-08T03:50:08+00:00January 22nd, 2019|Tags: , , |

This course is for workers and managers without a strong quantitative background. It introduces a range of skills and applications related to data literacy for digital transformations and 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.

Data-Driven Decision-Making

2021-09-08T06:35:02+00:00December 1st, 2019|Tags: , , , |

The Data-Driven Decision-Making 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.

Data Governance I

2021-09-08T01:48:49+00:00May 8th, 2019|Tags: , , , |

This two day course provides an informed, realistic and comprehensive foundation for establishing best practice data governance in your organisation. Suitable for every level from CDO to executive to data steward, this highly practical course will equip you with the tools and strategies needed to successfully create and implement a data governance strategy and roadmap.

Data Governance II

2021-04-15T02:25:28+00:00December 2nd, 2020|Tags: , , , |

This one day course builds on the foundation of Data Governance I, and dives deeper into selected areas that are designed to provide the most practical and real-world applications of data governance. It includes the change management journey to the “data-driven” organisation, and implications of the necessity of model governance in the context of data science, AI/ML initiatives and RPA/IPA .

Stars, Flakes, Vaults and the Sins of Denormalisation

2021-07-23T01:03:47+00:00May 13th, 2019|Tags: , , , |

Providing both performance and flexibility are often seen as contradictory goals in designing large scale data implementations. In this talk we will discuss techniques for denormalisation and provide a framework for understanding the performance and flexibility implications of various design options. We will examine a variety of logical and physical design approaches and evaluate the trade offs between them. Specific recommendations are made for guiding the translation from a normalised logical data model to an engineered-for-performance physical data model. The role of dimensional modeling and various physical design approaches are discussed in detail. Best practices in the use of surrogate keys is also discussed. The focus is on understanding the benefit (or not) of various denormalisation approaches commonly taken in analytic database designs.

Best Practices in Enterprise Information Management

2021-07-23T00:58:54+00:00May 17th, 2019|Tags: , , , , , |

The effective management of enterprise information for analytics deployment requires best practices in the areas of people, processes, and technology. In this talk we will share both successful and unsuccessful practices in these areas. The scope of this workshop will involve five key areas of enterprise information management: (1) metadata management, (2) data quality management, (3) data security and privacy, (4) master data management, and (5) data integration.

Agile Insights

2021-04-13T04:26:47+00:00February 11th, 2019|Tags: , , , , |

This course presents a process and methods for an agile analytics delivery. Agile Insights reflects the capabilities required by any organisation to develop insights from data and validate potential business value. Content presented describes the process, how it is executed and how it can be deployed as a standard process inside an organisation. The course will also share best practices, highlight potential tripwires to watch out for, as well as roles and resources required.

Overcoming Information Overload with Advanced Practices in Data Visualisation

2021-07-23T01:02:29+00:00May 14th, 2019|Tags: , , , , , , , |

In this workshop, we explore best practices in deriving insight from vast amounts of data using visualisation techniques. Examples from traditional data as well as an in-depth look at the underlying technologies for visualisation in support of geospatial analytics will be undertaken. We will examine visualisation for both strategic and operational BI.

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