Soft skills for analytics professionals and data scientists

Soft skills for analytics professionals and data scientists



Date & Time

Tue., 07/05/2019, 9:30 am –

Wed., 08/05/2019, 5:00 pm AEST


Saxons Training Facilities

Level 8

500 Collins Street

Melbourne, Victoria 3000 Australia

CANBERRA: 14-15 April

Date & Time

Tue., 14/05/2019, 9:30 am –

Wed., 15/05/2019, 5:00 pm AEST


Atlas Computer Training

Level 1

33–35 Ainslie Place

Canberra, ACT 2601 Australia

SYDNEY: 9-10 May

Date & Time

Thu., 09/05/2019, 9:30 am –

Fri., 10/05/2019, 5:00 pm AEST



Level 1

65 York Street

Sydney, New South Wales 2000

About the course

This course is for specialists working in the data domain. It teaches some of the vital skills that are not part of the formal training of quantitative professionals, which are essential in the modern workplace and crucial to the success of analytics efforts as well as the careers of analytics professionals.

Issues covered include effective communication, including presentation and communication skills, “storytelling”, and effective listening and elicitation. Technical methods will be presented in the context of their communication value.

The course also shares key insights and “trade secrets” that have served Eugene Dubossarsky well over decades of consulting, enterprise and startup work. These include effective ways to structure teams, projects, and analytics functions and careers, as well as “managing up”, branding and work style.

Course instructor

Courses are taught by Dr Eugene Dubossarsky and his hand-picked team of highly skilled instructors.


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

For someone who does not come from an IT background R is a terrifying program. Before doing the Introduction to R course I had previously done other courses in R but always found myself in over my head because they assumed a high level of program experience (even course that required no prior programming knowledge). This course is not like that at all. It starts at ground zero and teaches you everything you need to know to be able to use R confidently in your everyday workplace. It is a must attend for anyone who wants use R!
—Alix Duncan

Data science can be a challenging topic but Eugene’s “Introduction to Machine Learning” course turns complex statistical models into plain English. The course contents and presentation were accessible and I enjoyed the mixture of hands-on rattle() exercises, the challenge of building multiple models with real life data, and the salient theory whiteboard discussions created many “aha” moments.

It was a great introductory course and it gave me with a better grasp of Machine Learning in general, a great framework for thinking about it and practical hands-on skills that I can put to immediate use. I wish I had done this course sooner.
—Charl Swart, Director of Business Operations, Unisys Credit Services

Questions and further details

Meals and refreshments

Catered morning tea and lunch are provided on both days of the course. Please notify us at least a week ahead if you have any special dietary requirements.


Course material may vary from advertised due to demands and learning pace of attendees. Additional material may be presented, along with or in place of advertised.

Frequently asked question(s) (FAQ(s))

Do I need to bring my own computer?

There’s no need to bring your own laptop or PC. Our courses take place in modern, professional training facilities that have all the computing equipment you’ll need.

You can schedule a call with a Black Cat Data Career Consultant to discuss this course.

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