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Business analytics, big data and data science

The human side of analytics capability

Predictive analytics, machine learning and data science for big data

Data science, predictive modelling and big data skills are of vital and growing importance in commercial, government, and not-for-profit contexts, particularly for managers and those in risk, customer and IT functions. Learn the fundamentals of predictive modelling, including coverage of generalised linear models, support vector machines, decision trees, tree boosting machines and neural networks. This course also covers a range of other key data mining tools including principal components analysis, cluster analysis, and more.

Introduction to Machine Learning

Data science, predictive modelling and big data skills are of vital and growing importance in commercial, government, and not-for-profit contexts, particularly for managers and those in risk, customer and IT functions. Learn the fundamentals of predictive modelling, including coverage of generalised linear models, support vector machines, decision trees, tree boosting machines and neural networks. This course also covers a range of other key data mining tools including principal components analysis, cluster analysis, and more. Note: This is an alternative title for the course “Predictive Analytics, Machine Learning and Data Science for Big Data”.

Introduction to R and data visualisation

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.

Advanced machine learning masterclass

This course is for experienced machine-learning practitioners who want to take their skills to the next level by using R to hone their abilities as predictive modellers. Trainees will learn essential techniques for real machine-learning model development, helping them to build more accurate models. In the masterclass, participants will work to deploy, test, and improve their models.

Introduction to Data Science

Data science, predictive modelling and big data skills are of vital and growing importance in commercial, government, and not-for-profit contexts, particularly for managers and those in risk, customer and IT functions. Learn the fundamentals of predictive modelling, including coverage of generalised linear models, support vector machines, decision trees, tree boosting machines and neural networks. This course also covers a range of other key data mining tools including principal components analysis, cluster analysis, and more. Note: This is an alternative title for the course “Predictive Analytics, Machine Learning and Data Science for Big Data”.

Training

Presciient regularly runs courses in R and a range of data analytical disciplines in major Australian and Asian cities. Check the links below for a full list of dates and courses currently available in each city, and reserve your place today with our convenient online booking facility.

Courses are conducted by Presciient director Dr Eugene Dubossarsky. Eugene is a director of the University of New South Wales School of Mathematics and Statistics Industry Advisory Board, and a recognised business analytics industry leader. He has 20 years’ experience programming in R and its parent language, S.

Business analytics consulting

Presciient consults on how to make better decisions, recognising that all decision making involves forecasting.

Our process involves using sophisticated techniques to measure, assess, and manage forecasts and the decisions that arise from them. We call this Decision Performance Management.

An integral part of this is Forecasting Performance Management. We advise on better forecasting methods, based on both statistics and human judgement, and on their implications for organisational structure and incentives. We consult on knowledge management as it pertains to forecasting.

Learn how you can build your analytics capability.

Contact us today

About Dr Eugene Dubossarsky

Dr Eugene Dubossarsky is 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 (2,000+ members), the Sydney Users of R Forum (1,500+ 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.

The human side of data

Presciient specialises in the human side of business analytics, data science and big data. We provide services to build effective, valuable and recognised analytics capability within organisations large and small.

We assist our clients by training and mentoring their analytics teams, coaching executives in analytics management and value, and providing strategic advice in establishing and utilising analytics.

We also perform data analysis and implementation project for select clients.

We also conduct regular public training in various aspects of analytics, including predictive modelling, forecasting, forensics, fraud detection and security, visualisation and big data in Australia and Singapore.

Here’s what students are saying about our courses

Eugene’s courses are not your standard technical courses where you learn how to put data into a model and get a result. The real life experiences – warts and all - he brings to the instruction mean that attendees walk away with a better understanding of the real life challenges of analytics as well as the technical know-how. We routinely send our team members on these courses to help them get the capabilities that really help our clients get better insights from their data.

James Beresford

Director, Agile BI

Thank you Eugene for advancing my R skills. I especially appreciate the time spent explaining the fundamentals of data manipulation — i.e. the code one needs to know before running any basic or sophisticated analysis. The pace of the workshop was perfect.

Chelsea Wise

Lecturer, Marketing, UTS Business School

Eugene’s fraud and anomaly detection course is extremely valuable for anyone wishing to learn more about fraud detection using analytical techniques. Eugene’s ability to cater and tailor the course for all levels of experience is fantastic and much appreciated.

Hannah Sakai

Senior analyst, Insurance Australia Group (IAG)

Eugene’s Data Science course really opened my eyes to how accessible the latest machine learning tools are. I won’t need to spend months learning a hard-core new discipline, and I can already think of ways to use this at work.

Alain LeBel

Quantitative analyst and software developer, Cooper Investors

Having studied stats at Uni I was surprised how far the field has progressed in the last few years, particularly in the area of big data. The great thing about Eugene’s course is I left with a sense that I was up to date with the latest big data modelling concepts but more importantly could also deploy them with some confidence using R. Eugene also made it clear he was available to answer questions after the course, so you are not left hanging. I would absolutely recommend this!

Damon Rasheed

CEO, Rate Detective

As a beginner in R, I thought that [the course] might be a bit overwhelming. But I was wrong! Eugene did a fantastic job at explaining the concepts and all practical work was engaging and easy to follow. Entertaining, informative and most importantly relevant – it has already proven valuable in my work.

Sanja Djeckic

Data manager and analyst , South Western Sydney Local Health District

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