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

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

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.

Feedback

Use enquiries@presciient.com to email us any questions about the course, including requests for more detail, or for specific content you would like to see covered, or queries regarding prerequisites and suitability.

If you would like to attend but for any reason cannot, please also let us know.

Variation

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.

Cancellations and refunds

You can get a full refund if you cancel 2 weeks or more before the course starts. No refunds will be issued for cancellations made less than 2 weeks before the course starts.

Frequently asked questions (FAQ)

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.

I’m lost! How do I find the venue?

Please call 0800-424282 (toll-free) or email training@presciient.com if you can’t find the venue.

Presciient training, coaching, mentoring and capability development for analytics

Please ask about tailored, in-house training courses, coaching analytics teams, executive mentoring and strategic advice and other services to build your organisation’s strategic and operational analytics capability.

Our courses include:

• Predictive Analytics, Machine Learning, Data Science and AI
• Data Literacy for Everyone
• Introduction to R and Data Visualisation
• Introduction to Python for Data Analysis
• Forecasting and Trend Analytics
• Advanced Machine Learning Masterclass
• Advanced Masterclass 2: Random Forests
• Advanced R
• Quantum Computing
• Text and Language Analytics
• Fraud and Anomaly Detection
• Introduction to Machine Learning
• Introduction to Data Science
• Kaggle Boot Camp