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Intensive 2-day workshop |
20th and 21st of October 2017 |
In the past decade, there has been a fundamental change in the business world: Not only is more and more data gathered by companies, but they are increasingly interested in exploiting this asset to generate business value. Data scientists are tasked with translating between the business world and the data world, turn business questions into machine learning models and extract recommendations for business owners. This workshop introduces the basic techniques used and familiarizes the participants with all they need to know for the start into a successful career.
What you will learn
- Why data science is a main building block of future companies
- The methodological basics of data science
- Data cleaning and preparation
- Machine learning techniques and their diagnostics
After the workshop you will be able to
- Understand the concept behind a data science project
- Prepare data for machine learning
- Develop simple machine learning models
- Industrialize (scale up) these models in a professional environment
What makes it important?
Why is data science named a professional competence?
In the past decade, there has been a fundamental change in the business world: Not only is more and more data gathered by companies, but they are increasingly interested in exploiting this asset to generate business value. However, three challenges initially made the idea of data-driven businesses difficult to reach:
- The data needs to be analysed, which requires mathematical, programming and IT skills
- It needs to be interpreted, which requires knowledge of the business domain
- The results need to be communicated to business leaders / top management, which requires communication and consulting skills.
The role of a data science team in a company is to fill the gap between “classical” IT and business intelligence groups that solely store and report on the data instead of generating novel insights and determining business value. Natural scientists are uniquely suited to work in such a team, since they are able to use their scientific experience to ask key questions and possess the technical and mathematical skills to implement solutions.
These will be major topics during the workshop
- The data science cycle
- Data extraction, transformations, and preparation
- Modelling and machine learning
How you will be working during the workshop - Workshop Framework
Throughout the workshop, input from the trainer will alternate with practical exercises and group discussions of relevant issues. There will be plenty of room for your questions and you will be working on own real data in a professional data science environment, DataIku. Participants will be asked to install DataIku on their laptops before the workshop.
Who should attend - Workshop Participants
This workshop is most useful for students who have some experience in mathematical statistics, even though the basics that are generally known to a natural scientist are sufficient as a first approximation. Knowledge of a high-level programming language or statistics tool is a plus (e.g., Matlab, Python, but also R, Stata or SPSS).
Your trainer – Profile + Experiences
Christoph Euler studied Physics in Heidelberg, Helsinki and Beijing. He received his PhD from the university of Mainz and subsequently worked as a consultant at the Process Analytics Factory. Currently, he is a data scientist at Capgemini Consulting, the strategy consulting brand of the Capgemini group.
As a data scientist, Christoph Euler is working at the interface of corporate strategy, the digital transformation of business models and technical proof-of-concept projects demonstrating the value of data-driven decision making to international enterprises. He is mainly interested in the manufacturing industry where the Internet of Things is beginning to revolutionize the way humans and machines work together in a fully automated factory environment.