London: workshops​­ Hands on Machine Learning and Big Data

In the big data world, programming is no longer enough!

Whether you are scientist, programmer, entrepreneur or still looking for your unique place in the Tech world, you might be familiar with the terms Machine Learning or Data Science. There is a little bit of confusion between the scientific approach and the exact words’ meaning, but one thing is pretty clear, both in business and science Big Data is the topic.


What is Big Data? According to some definitions, it is when you cannot store and effectively process data on one computer that is big data. The information which we generate and obtain every day is used in Medicine, Computing, Finance, Transportation, Advertising and many other areas of our lives. This is one of the reasons why Big Data is so crucial now. It was always important, but nobody could tackle the problem of really big data that required more computation power than anyone could afford. The cloud has changed it to the point where very powerful hardware became a commodity. The only missing piece was to have software that could handle the amount and distribution of the data. If it could also be able to process streaming data, it’d be even better. ­ Jacek Laskowski, Java Champion & Apache Spark master, Instructor.


There is also another aspect of that tendency. More and more companies want to hire data scientists, while there aren’t enough of us. ­ admitted Piotr Migdał, PhD, Instructor Typical software engineers may be wonderful at programming, but without any grasp of statistical and mathematical techniques to analyze data. Typical scientists may be wonderful at these methods, but not able to ship production­quality code on time. And it takes both to be a data scientist.


One of the technologies which you can use to work with Big Data ­ including analysis and visualisation is Apache Spark. Jacek: With Spark it’s a very straightforward process ­ tons of data in minutes without much computing power in the cloud. Apache Spark comes with the concept of Resilient Distributed Dataset that allows computations to be distributed and fault­tolerant without having a PhD in Computer Science. Spark and Hadoop are open source projects and the available tools shipped with them, make getting insights from your data a breeze.


Big Data is not magic. It is a popular term to describe huge data sets. There are many combinations of technologies and programming tools which help us to effectively use and manipulate huge data sets ­ to which we have wider access to. Even those tools are not going to be efficient if we are not going to learn statistic and data analysis methods. With Machine Learning, you can use your data to make highly accurate predictions. For example, you can build a model to predict if an e­mail is spam, or not. You can try to predict if a book is going to be the winter bestseller, if there will be a traffic Friday afternoon at the 14th Street. Combining programming and Machine Learning can give you all new possibilities. workshops​­ Hands on Machine Learning and Big Data
Nov 26, ­27th and Nov 28­, 29th | London

Just one warning: it will be intense!


Jacek Laskowski and Piotr Migdał are’s instructors for the 2­day intensive workshops using hands­on exercises teaches a wide range of important Machine Learning algorithms and tools that we selected for their value in today’s market. The workshop offers a short yet comprehensive introduction to Machine Learning (Python) and Big Data processing, and then moves to practical exercises with many programming assignments (Spark).


Participants use Python with libraries for data manipulation (Pandas), visualization (Seaborn) and machine learning (scikit­learn). They can also learn IPython Notebook and PySpark from the Apache Spark project. By combining theory with an extensive set of practical exercises led by instructors who are practitioners in the field, each attendee can benefit from a very effective learning experience.
We expect participants to be comfortable with the basics of Python. We assume no prior experience in Machine Learning, Big Data processing or specific Python packages whatsoever. The next training sessions take place on: Nov 26­, 27th and Nov 28­, 29th in London. You can find more information on


See you in London!