Dr Eugene Dubossarsky

Eugene is Managing Partner of AlphaZetta Academy and a leader in the analytics field in Australia, with 20 years’ commercial data science experience. He is the head of the Sydney Data Science group (3,000+ members), the Sydney Users of R Forum (1,900+ members), and Datapreneurs (400+ members). He is regularly invited to be a conference presenter, consultant and advisor, and appears in print and on television to discuss data science and analytics. Eugene also applies data science in an entrepreneurial setting, to financial trading and online startups, and is the creator of ggraptR, an interactive visualisation package in R.

He is a Director at Presciient, providing analytics capability, development services including team selection, training, and executive coaching for team owners and sponsors. They also provide strategic advisory, communications and specialised advanced data analysis.

Data Literacy for Everyone

2019-11-15T07:02:59+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.

AI and Data Science for Managers and Executives

2019-10-25T02:34:07+00:00Categories: Predictive Analytics & AI, Data Governance Curriculum, Executive Curriculum, Dr Eugene Dubossarsky, Data Governance Level 1, Executive Level 1, All Academy Courses, Innovation & Tech (CTO) Level 1|Tags: , , , |

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.

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

2019-10-25T02:39:22+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.

Intro to R (+ data visualisation)

2019-11-05T23:25:16+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

2019-10-17T00:38:35+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.

Fraud and Anomaly Detection

2019-10-25T02:45:21+00:00Categories: Level 2, Data Science Curriculum Electives, Fraud and Security, R Electives, Dr Eugene Dubossarsky, Financial Risk, All Academy Courses|Tags: , |

This course presents statistical, computational and machine-learning techniques for predictive detection of fraud and security breaches. These methods are shown in the context of use cases for their application, and include the extraction of business rules and a framework for the interoperation of human, rule-based, predictive and outlier-detection methods. Methods presented include predictive tools that do not rely on explicit fraud labels, as well as a range of outlier-detection techniques including unsupervised learning methods, notably the powerful random-forest algorithm, which can be used for all supervised and unsupervised applications, as well as cluster analysis, visualisation and fraud detection based on Benford’s law. The course will also cover the analysis and visualisation of social-network data. A basic knowledge of R and predictive analytics is advantageous.

Data Driven Decision Making for Executives and Managers

2019-10-18T03:28:45+00:00Categories: AI Engineering Curriculum Electives, Data Engineering Curriculum Electives, Government, Data Science Curriculum, Data Governance Curriculum, Data Science Level 1, Executive Curriculum, Data Engineering Level 2, Dr Eugene Dubossarsky, Innovation & Tech (CTO) Curriculum, Data Governance Level 1, AI Engineering Level 2, Executive Level 1, All Academy Courses, Innovation & Tech (CTO) Level 1|Tags: , , , |

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.

Deep Learning and AI

2019-10-17T05:12:36+00:00Categories: Keras, Tensorflow, Level 2, Data Science Curriculum, Python, Data Engineering Curriculum, Dr Eugene Dubossarsky, All Academy Courses|Tags: , |

This course is an introduction to the highly celebrated area of Neural Networks, popularised as “deep learning” and “AI”. The course will cover the key concepts underlying neural network technology, as well as the unique capabilities of a number of advanced deep learning technologies, including Convolutional Neural Nets for image recognition, recurrent neural nets for time series and text modelling, and new Artificial Intelligence techniques including Generative Adversarial Networks and Reinforcement Learning. Practical exercises will present these methods in some of the most popular Deep Learning packages available in Python, including Keras and Tensorflow. Trainees are expected to be familiar with the basics of machine learning from the Fundamentals course, as well as the python language.

Text and Language Analytics

2019-10-18T03:37:35+00:00Categories: AI Engineering Curriculum Electives, Level 2, Data Science Curriculum Electives, R, R Electives, Dr Eugene Dubossarsky, All Academy Courses|Tags: , |

Text analytics is a crucial skill set in nearly all contexts where data science has an impact, whether that be customer analytics, fraud detection, automation or fintech. In this course, you will learn a toolbox of skills and techniques, starting from effective data preparation and stretching right through to advanced modelling with deep-learning and neural-network approaches such as word2vec.

Forecasting and Trend Analysis

2019-10-18T03:03:34+00:00Categories: AI Engineering Curriculum Electives, Data Science Curriculum Electives, R Electives, Dr Eugene Dubossarsky, All Academy Courses|Tags: , |

This course is an intuitive introduction to forecasting and analysis of time-series data. We will review a range of standard forecasting methods, including ARIMA and exponential smoothing, along with standard means of measuring forecast error and benchmarking with naive forecasts, and standard pre-processing/de-trending methods such as differencing and missing value imputation. Other topics will include trend/seasonality/noise decomposition, autocorrelation, visualisation of time series, and forecasting with uncertainty.