Data Culture Curriculum

An effective data analytics strategy in any organisation needs a program to build organisational culture around data; its ethical use, understanding, acceptance and its place in the daily conversation of what matters at all levels. Literacy around data, its purpose and management drives the development of that culture.

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

2020-02-14T02:04:02+00:00Categories: Predictive Analytics & AI, Level 1, Data Culture Electives, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Data Engineering Curriculum, Dr Eugene Dubossarsky, Innovation & Tech (CTO) Curriculum, AI Engineering Curriculum, All Academy Courses|Tags: , , , , |

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.

Data Literacy for Everyone

2020-04-02T01:15:40+00:00Categories: Data Culture Curriculum, Data Governance Curriculum, Introductory, Executive Curriculum, Dr Eugene Dubossarsky, Innovation & Tech (CTO) Curriculum, All Academy Courses|Tags: |

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.

Critical Thinking for Data Analytics

2020-04-07T06:31:42+00:00Categories: Data Culture Curriculum, Introductory, Executive Curriculum, Dr Eugene Dubossarsky, All Academy Courses|Tags: |

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.

Your Successful Digital Business Case

2020-03-04T03:45:28+00:00Categories: Thomas Foltyn, Data Culture Curriculum, Data Science Curriculum, Executive Curriculum, All Academy Courses|Tags: |

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.

Intro to R (+ data visualisation)

2020-03-16T00:47:45+00:00Categories: Level 1, Data Culture Electives, Impact, Data Science Curriculum, R, Data Visualisation, Data Engineering Curriculum, Dr Eugene Dubossarsky, AI Engineering Curriculum, All Academy Courses|Tags: , |

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.

Intro to Python for Data Analysis

2020-02-14T02:07:57+00:00Categories: Level 1, Data Culture Electives, Data Science Curriculum, Python, Data Engineering Curriculum, Dr Eugene Dubossarsky, AI Engineering Curriculum, All Academy Courses|Tags: , |

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 Governance 1

2020-04-08T06:24:28+00:00Categories: Data Culture Level 1, Data Culture Electives, Government, Data Science Curriculum, Data Governance Curriculum, Data Science Level 1, Executive Curriculum, Mark Burnard, Data Engineering Curriculum, Innovation & Tech (CTO) Curriculum, Data Governance Level 1, AI Engineering Curriculum, Financial Risk, Data Engineering Level 1, AI Engineering Level 1, Executive Level 1, All Academy Courses, Innovation & Tech (CTO) Level 1|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.

Best Practices in Enterprise Information Management

2019-10-24T04:45:22+00:00Categories: Data Culture Level 1, Data Culture Curriculum, Innovation & Tech (CTO) Curriculum Electives, Data Governance Curriculum, Stephen Brobst, Fraud and Security, Executive Curriculum, Data Engineering Curriculum, Data Governance Level 1, Data Management, Executive Level 2, Big Data, Data Engineering Level 1, All Academy Courses, Innovation & Tech (CTO) Level 3|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

2019-10-25T10:26:46+00:00Categories: AI Engineering Curriculum Electives, Data Culture Electives, Data Governance Curriculum, Introductory, Executive Curriculum, Innovation & Tech (CTO) Curriculum, Alexander Heidl, All Academy Courses|Tags: , , , , |

This course presents a process and methods for an agile analytics delivery. Agile Insights reflects the capabilities required by any organization to develop insights from data and validating potential business value.Content presented describes the process, how it is executed and how it can be deployed as a standard process inside an organization. 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

2019-10-24T04:46:56+00:00Categories: Data Culture Electives, Innovation & Tech (CTO) Curriculum Electives, Data Science Curriculum, Data Science Level 1, Data Culture Level 2, Innovation & Tech (CTO) Level 2, Stephen Brobst, Executive Curriculum, Data Visualisation, Data Management, AI Engineering Curriculum, Executive Level 2, Big Data, AI Engineering Level 1, All Academy Courses|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.