Data Science Curriculum

Our Data Science Curriculum is comprehensive in its coverage of the many topics in the field. We offer starting points for all levels – from raw beginner to expert. Our curriculum is customisable for organisations with specific needs.

Courses are offered in online and face-to-face formats.

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

2020-11-02T23:25:54+00:00Categories: Predictive Analytics & AI, Level 1, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Data Engineering Curriculum, Dr Eugene Dubossarsky, Innovation and Technology Curriculum, AI Engineering Curriculum, All Academy Courses|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.

Data-Driven Management

2020-09-17T07:24:02+00:00Categories: AI Engineering Curriculum Electives, Data Engineering Curriculum Electives, Government, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Dr Eugene Dubossarsky, Innovation and Technology Curriculum, All Academy Courses|Tags: , , , |

The Data-Driven Management 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 Visualisation and Communication

2020-09-17T08:23:30+00:00Categories: Executive Curriculum Adv Electives, Data Culture Electives, Data Science Curriculum, Introductory, Data Visualisation, Dr Eugene Dubossarsky, All Academy Courses|Tags: , , , |

This course prepares data analytics professionals to communicate analytics results to business audiences, in a business context while being mindful of the skills, incentives, priorities and psychology of the audience. It also equips analysts [...]

Report Automation – Excel to PowerPoint with R

2020-10-30T03:38:27+00:00Categories: Dr Craig Savage, Data Engineering Curriculum Electives, Data Science Curriculum Electives, R, Data Visualisation, All Academy Courses|Tags: , , , |

Report automation can deliver powerful, time-saving results. This course teaches analytics professionals to automate the creation of PowerPoint packs from input Excel workbooks using R. Time is allotted for students to implement techniques taught so that, by the end of the course, students will have wrangled input data, created plots and tables, defined a PowerPoint template, and built a sample set of slides.

Data Governance I

2020-09-18T02:53:29+00:00Categories: Data Culture Electives, Government, Data Science Curriculum, Data Governance Curriculum, Executive Curriculum, Mark Burnard, Data Engineering Curriculum, Innovation and Technology Curriculum, AI Engineering Curriculum, Financial Risk, All Academy Courses|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.

Your Successful Digital Business Case

2020-09-17T08:27:41+00:00Categories: Data Culture Curriculum, Data Science Curriculum, Executive Curriculum, Thomas Foltyn, 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. It teaches you how to apply the right numbers 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)

2020-10-19T01:35:22+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: , |

This R training 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. 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.

Intro to Python for Data Analysis

2020-11-03T00:09:02+00:00Categories: Level 1, Data Culture Electives, Data Science Curriculum, Python, Data Engineering Curriculum, Dr Eugene Dubossarsky, AI Engineering Curriculum, All Academy Courses|Tags: , |

This course provides a foundation for using Python in exploratory data analysis and visualisation, and as a stepping stone to machine learning. 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.

Data Science and Big Data Analytics: Leveraging Best Practices and Avoiding Pitfalls

2020-10-26T10:07:42+00:00Categories: Data Engineering Curriculum Electives, Data Science Curriculum, Data Governance Curriculum Electives, Stephen Brobst, Executive Curriculum, Data Visualisation, Data Management, Big Data, All Academy Courses|Tags: , , , , , , |

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.

Data Governance II

2020-12-02T02:02:44+00:00Categories: Executive Curriculum Adv Electives, Data Culture Electives, Government, Data Science Curriculum, Data Governance Curriculum, Mark Burnard, Data Engineering Curriculum, Innovation and Technology Curriculum, AI Engineering Curriculum, Financial Risk, All Academy Courses|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 .

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