Machine Learning and Data Science in R on Microsoft ML and SQL Servers
2020-11-16 09:00 to2020-11-20 17:00(Europe/Tallinn)
He has been a popular speaker at major IT conferences since 1998, and he had the honour of sharing keynote platforms with Bill Gates and Neil Armstrong. A natural educator, he explains complex concepts in simple terms in his enjoyably energetic style
Trainer Rafal Lukawiecki
Above all, this course will teach you modern R: currently, the most powerful language explicitly designed for advanced analytics, statistical learning, data science, and cutting-edge general-purpose machine learning. While Python is more popular as a universal programming language, also widely used for image and text analysis using deep learning, R is a clear leader in data science. You will learn how to do machine learning in R especially on classical data sets that you often encounter in business use. Even though such data might come from a data lake, typically you will ﬁnd plenty of it in a data warehouse, a relational databases, or you can acquire it from transactional business application ﬁles, or from devices, such as: healthcare equipment, point-of-sales devices, or manufacturing and transportation machinery. Above all, R is great for exploratory analysis of data and it can help you draw meaningful conclusions from real-world experiments, such as A-B marketing tests or product trials. This course will teach you the foundations of hypothesis testing in order to be able to draw such conclusions with a high dose of conﬁdence.
Read more about the course.
- Building and deploying machine learning models using open source R programming language, including data preparation, visualisation, and stringent model validation.
- High-performance ML using the newest version of Microsoft ML Server and SQL Server 2019 with R and RStudio.
- Deployment to production with nanosecond-scale performance.
- Successful data science project formulation and delivery.
Because of Rafal’s 10+ years of real-world machine learning experience.
You will not only learn all the concepts and tools that you need to know from an experienced teacher who has trained over 900 data scientists world-wide, a highly-respected presenter, capable of holding your attention, but, above all, from a practitioner of machine learning. Rafal Lukawiecki has been delivering ML, data mining, and data science projects for customers in retail, banking, entertainment, healthcare, manufacturing, education, and government sectors for twelve years. Because of that, you will learn:
- everything essential to starting data science, ML, and AI projects,
- all fundamental concepts,
- how to avoid common pitfalls,
- how to work fast yet accurately,
- what is really useful and practical,
- what is more theoretical but still important,
- what hype you should be wary of.
You will be able to ask any questions related to your industry and you will get relevant, pragmatic, no-nonsense answers, helping you get ahead with your own projects.
Learn from Rafal who has done it all, not from those who just teach it—this is why it is Practical Machine Learning.
50% lectures, 25% demos, 25% lab tutorials.
You are encouraged to follow the demos on your machine, and you will be challenged to ﬁnd answers to a few larger problems during the tutorials. We will provide you with all the necessary data sets including structured R Markdown notebooks containing labs. While both the demos and the tutorials are a hands-on part of the course, if you prefer not to practice, you are welcome to use that time for additional Q&A, or to work with your own data. As each training centre is diﬀerent, you will receive an email, two weeks before the course starts, explaining how to prepare your computer for the course, unless the centre is providing one for you. In any case, preparation is easy, because we will use an Azure virtual machine that has been fully preconﬁgured with all the necessary software for the course. If you follow our preparation guide, you can take this VM together with the course data for your own future learning and reference.
Analysts, budding and current data scientists, data engineers, DBAs, BI developers, programmers, power users, predictive modellers, forecasters, consultants, data engineers, anyone interested in using ML for AI, AI engineers.
General ability to work with data in any form: using spreadsheets, tables, or databases. Prior knowledge of any programming language is helpful, however, if you are prepared to work harder by asking Rafal questions and doing a little additional homework during the week you can use this course to learn R as your very ﬁrst programming language.
This course will teach you machine learning and data science using R and Microsoft technologies: you do not need to know that before attending.
The course was an immense learning experience, tapping into the vast knowledge base that is Rafal. His presentation skills and technique made the learning experience very enjoyable. The pace at which he managed to deliver the content was remarkable, even when delayed to answer questions he still managed to run through the enormous subject matter and keep to schedule. All in all it was a very enjoyable learning experience that has fuelled my desire to learn more on the subject.Sean, Globoforce, Ireland
This was a 5 star course. Rafal is a world class teacher who brings the right combination of practical, technical and theoretical experience to the course. I have a Masters in Analytics and have worked on an Analytics Project for 3 years and yet I still learnt so much from this course. Without a doubt the best course I have been on.Brian, Department of Social Aﬀairs, Ireland
I highly recommend this course. Rafal’s knowledge, teaching skills and humour makes complex challenges much easier to grasp and understand.Asbjørn, Genus AS, Norway
I initially stumbled across the Practical Data Science course having seen and been impressed by videos of Rafal speaking at Microsoft Ignite. I appreciated and enjoyed the way he discussed his (extensive) practical experience in the ﬁeld as much as the technology and am pleased to say the course was no diﬀerent. I came into the course from a background of working with database’s, but the world of data science is something I’ve always wanted to get more involved in. This course seemed to be ideally tailored for this.Callum, UK public sector company
I had the pleasure of attending “Practical Data Science” in Copenhagen with Rafal. The course was great, and is just the way it is described—not only was it practical and exciting, but followed by in depth understanding of theory. Rafal is a great instructor, and certainly one of the best experts that I have had the chance to meet. Throughout the whole course I learned a lot and Rafal even took time to debate speciﬁc problems that we were contemplating.Philip, Inspari A/S, Denmark
I can only recommend this course. Rafal is an excellent teacher. He shows real world examples that are directly applicable.Jacquel, Datalytics AG, Switzerland
As Data Scientist at Project Botticelli Ltd, Rafal focuses on making advanced analytics and artiﬁcial intelligence easy and useful for his clients.
He can help you ﬁnd valuable, meaningful patterns and statistically valid correlations using data mining and machine learning in data sets both big and small. Rafal is also known for his work in business intelligence, data protection, enterprise architecture, and solution delivery. While majority of his clients come from consumer and corporate ﬁnance, entertainment, healthcare, IT, retail, and the public sectors, Rafal has worked in almost all industries.
He has been a popular speaker at major IT conferences since 1998, and he had the honour of sharing keynote platforms with Bill Gates and Neil Armstrong. A natural educator, he explains complex concepts in simple terms in his enjoyably energetic style.
Rafal was born in Poland. He left it in 1990 to study computing in United Kingdom, where he earned BEng in Computing Science, followed by MSc in Foundations of Advanced Information Technology, at Imperial College, University of London. His studies were sponsored by Oxford Computer Group Ltd, where he later worked as a developer, trainer, and a consultant. Since 2000 he has worked for Project Botticelli Ltd.
Outside of IT, Rafal spends a quarter of every year ﬁnding abstractions in natural landscapes, expressing them through traditional, black-and-white, large-format ﬁlm photography, making silver-gelatin prints by hand—see rafal.net. You can also follow Rafal on TwitterTwitter,, or connect with him on LinkedIn.