Azure Machine Learning in Practice: From Fundamentals to Deployment
2020-11-09 09:00 to2020-11-13 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
We will use the brand-new Azure ML Designer UI, and the completely new Azure ML Studio (very diﬀerent from the older ones) to teach all the fundamentals of machine learning. You will understand why and how to use speciﬁc algorithms, notably: classiﬁers such as Boosted Decision Trees, Logistics Regression and Neural Networks, both linear and non-linea regressions, clustering, and recommenders. Though almost all of your work will be done using the graphical UI, you will also see how to code for Azure ML Service in Python and in a little R using the most popular Python libraries, such as scikit-learn. Although deep learning is not a focus for this course, you will also see how easy it can be to use it with Azure ML. If you already have some programming experience: that is great—but it is not necessary, as everything needed to use Azure ML, including every line of code, will be carefully explained during the course. If you are interested in learning R for more advanced ML and data science, please see our other course by Rafal that focuses on R and Microsoft ML and SQL Servers—which we do not cover in this course.
Read more about the course.
Everything necessary to prepare your data, build, evaluate, and, most importantly, validate machine learning models, before deploying them to production, using the newest, 2020 version of Microsoft Azure Machine Learning.
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, BI developers, programmers, power users, predictive modellers, forecasters, consultants, data engineers, anyone interested in using ML for AI, AI engineers.
There are no prerequisites other than general ability to work with data in any form: if you have used a spreadsheet, tables, databases, or you have written a program, no matter how long ago, you will be able to follow the course.
This course will teach you machine learning using Azure ML: you do not need to understand ML or data science 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.