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Data Lab

Discovery Is Experimentation

The world is bursting with data, but without analysis, interpretation, and application, the data itself is worthless. Is there value in your data, and how can you find and refine it? In Data Lab, we recognize the value in data and seek ways to build on it. The greatest value seldom comes from a straightforward path; thus we experiment to discover and learn through trial and error.

In Data Lab you will expand your toolkit, learning hands-on from both academic and industry professionals. You will familiarize yourself with methods of analysis and their potential applications and build a mindset for problem solving through curiosity and experimentation. You will learn how to formulate, test, and ask your data the right questions in order to make a difference in your field. 

The Data Lab training has been created for people who have at least basic skills in Python, R, Java, or similar tools. After the program your skills, attitude, and way of thinking will have taken a leap forward towards those of a world class data scientist.

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Concrete methods for real business purposes

Practical project work helps in cracking your business case

Strong foundation for becoming a data scientist professional

Program Benefits

The program provides competencies in how to drive more value from existing data by enhancing data analysis skills, and encourages seeking validation for business problems by testing ideas with data. Up-to-date data analysis skills within an organization open up new business opportunities, while cherishing the mentality of a data scientist contributes towards a culture of experimentation and open-minded venturing into unfamiliar areas. Your business will see tangible benefits from Day 1, through the participants’ work on a project from their own business scenario.

Get acquainted with fundamental data analysis methods and dig deeper into one or more of them
Adopt a problem-solving mindset
Receive guidance on how to tackle your own concrete business case
Learn how data is utilized in fields of business other than your own

For

The program is targeted at professionals who are already dealing with data and wish to upskill or reskill their competencies in the field. Participants should have basic knowledge of at least one tool (e.g. Python, R or Java) in order to gain the greatest benefit from the program. Possible job roles include controller, BI analyst, supply chain specialist, production planner or manager, and marketing analyst or manager. 

The program will help you to keep up-to-date with modern data-analysis methods and know how to combine the correct method with the available data and formulate a problem in a way that returns meaningful results. For managers, the program provides valuable insights for hiring and leading a team of data analysts. 

Contents and Schedule

The program content covers the core concepts of data and the fundamental methods used in data analysis. The methods covered include predictive analytics, dimension reduction and data visualization, clustering, decision trees, time series analysis, and prescriptive analytics.

The program will be delivered in modules of two full-day sessions and four half-day workshops. The emphasis is on learning by doing. Typical days consist of lectures, practical exercises, and debriefing. An individual project is carried out during the program.

Program Structure

Pre-program preparation

Finding and preparing data for project work.

Six modules, opening & closing 6h. Four core models of 4h.

Short lectures followed by exercises and their debriefing.

Project work

You’ll be working on your own organization’s or personal interest fueled project throughout the whole program.

Modules

Instructors

Juuso Liesiö

Juuso Liesiö is Associate Professor of Management Science in the Department of Information and Service Management at Aalto University School of Business.

Professor Liesiö’s research interests lie in decision analysis and prescriptive analytics with a focus on modeling incomplete preference information and uncertainties in decision support. In these areas, he has developed novel theory, methods, algorithms, and computer software. This research has been published in leading journals in the field such as the European Journal of Operational Research, Technological Forecasting & Social Change, and Decision Analysis.

The application areas of Professor Liesiö’s research include, for example, R&D portfolio selection, strategy building, infrastructure asset management, procurement optimization, supply chain planning, and production planning.

Jaakko Hollmén

Jaakko Hollmén is Chief Research Scientist at the School of Science and Technology at Aalto University. Hollmén’s research focuses on machine learning, data mining, and artificial intelligence. He has a special interest in predictive analytics.

Hollmén has more than 20 years experience in data analytics, both in manufacturing industry and university research. He is a founding member of Northlet Ltd., which offers analytics services and consulting for companies aiming to improve their usage of analytical tools. In 2017, Hollmén was a key organizer of ECML-PKDD 2017 – the biggest conference in machine learning and data mining in Europe.

Program Fee and Registration

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