Testimonials from participants DSF bootcamp 2017, 2018 Testimonials from DSF bootcamp participants 2017, 2018 Leandra Bräuninger “I am personally very interested in technical questions but getting a major in a technical field I would have felt that it lacked the view of the bigger picture. Now studying International Affairs, I appreciate the broad approach it gives me, but I sometimes miss the technical details of the real world. Therefore, the DSF Program is the perfect addition to my studies and with it I can get the best of both worlds and combine them. It gives me the ability to speak both the technical as well as the business (or in my case International Affairs)-oriented language and solve problems from a unique point of view.” Ruben Burdin “Why did I join the DSF programme? As soon as I saw the DSF content presentation on the university's website, I immediately realized that this would be an unequalled opportunity to acquire new skills and to make the difference. Everybody is conscious that the world is changing and that technology and Data Science form nowadays an integral part of the management practice. Leaders qualified in technology are more than ever a scarce resource for companies and integrating the DSF right from the third semester of the bachelor is by far one of the most valuable asset one could achieve at the HSG. The DSF programme is an all-in-one package to learn and understand the basics of Data Science with an eye on the business perspective. Coding, applied mathematics and guest lectures during the workshop will prepare you to make the most of your group project and the following courses that make up the certificate. Last but not least, the DSF is a highly selective programme that gathers the most motivated students of the HSG sharing an interest for Data Science to build new skills and network, this is also what makes this experience exceptional. I am really satisfied with my experience until now, and I can only recommend to apply for this innovative programme.” Andreas Camenisch “The DSF workshop helped me get an overview of the basic ideas and concepts of machine learning and artificial intelligence. Through various guest lectures by practitioners and theorists, we saw the relevance, possibilities and limitations of data science and got a feeling of the big part that it is without a doubt going to play in our future society. I now understand how some important machine learning algorithms work and why a specific algorithm is chosen for a certain task. This is an important quality for members of the business world who want to collaborate with technical specialists from the field of data science.” Julian Leoold The Swiss Data Science Conference 2018 left me with the impression, that there is a real need to bridge the gap between the world of business and data science. Studying at a business school with the DSF certificate to complement, I learn to do exactly this. The certificate program begins with the boot camp. Within two weeks we received a solid data science foundation ranging from basic programming skills over stats and probability to artificial intelligence. More valuable still, the course enabled us to study more advanced concepts and stay in touch with current technological developments by understanding them on an intuitive level. The study of data science as the digital element of the HSGs integrative approach empowered me to recognize unseen opportunities and realize new ideas through the application of data science in a business context. Lukas Neuhauser Fundamentals of Data Science is an exceptional course, not only due to the steep learning curve I experienced but also because I enjoyed challenging myself in a community of like-minded people. In terms of content, the focus on a deep conceptual understanding empowered me to stay involved and pursue the development of expertise in this area. This course clearly demonstrates that the future belongs not only to data scientists; it is also the responsibility of economists and other societal actors to reflect on analytics-based solutions. Jonas Röser “The data science fundamentals programme allowed me to develop a well-founded understanding of the most central machine learning and artificial intelligence concepts. Centred around a two-week bootcamp with subsequent project work, the programme connected me with like-minded students eager to dive deep into mathematics and data handling in the face of machine learning. Especially during the highly intensive project phase I was able to improve my coding skills and replace superficial misconceptions present in the general public with actual knowledge by applying machine learning instead of talking about it. My key take-away from this programme is an intuition that allows me to sense machine learning value in projects and in daily life. Highly engaged and involved, the people in charge really care for a programme that is gaining more and more relevance in an increasingly data-driven world.” Michael Tsesmelis The DSF Bootcamp is the ideal opportunity to kickstart your entry into the world of data. Over a period of two weeks, you are introduced to countless conceptual and technical aspects of Data Science. As it takes place over ten entire days, your mind is allowed a complete dive into the subject, without any distraction. Only this way can you progress in what is arguably the most important discipline of the coming decade. Week 1, taught by Professor Binswanger, introduces you to Programming, Maths in Data Science and Machine Learning. What is particularly underpinned in this first phase is the way machines learn. Gradient Descent is perhaps the most salient tool that is presented. A data scientist’s job is to use the trio of instruments mentioned above to analyse data and produce meaningful results. This is the subject of Week 2, taught by Professor Ortega. Here, intelligent algorithms such as Naïve Bayes Classifiers and Neural Networks help solve more complex problems with real-world applications. Overall, the DSF Bootcamp will help any attentive student make tremendous strides towards understanding what Data Science is and how it is used. The theory, interspersed with interesting exercises, gradually builds up your skillset. This affords you a solid basis for any further step you might take in this discipline. Ira Welz This course is truly amazing. You feel like entering digital Narnia: A whole new world of thinking differently. Structured like a programmer, rational like a statistician and abstract like a mathematician. It is you who is entering the entrepreneurial spirit. You are creating something truly not everyone can do: Your own, first machine learning algorithm. The course is hard and demanding, but definitely worth your time. Gather institutional perspectives for personal growth while obtaining a powerful toolset. What for? To become an ambassador of the upcoming era of data analytics. There’s much to explore no one has done before in this young field, and DSF offers you a treasure here: The entry ticket, or wardrobe door to digital Narnia. Aline Zimmermann When I first heard about the DSF program, I was rather intimidated because I did not have any experience in programming and data handling. But I was aware that the topic would gain importance in the years to come. Therefore, it appeared to me as a “must do”. Moreover, I came to the conclusion, that this program is unique in that it offers skills and techniques which I hardly could acquire anywhere else. I therefore was overly happy that I got accepted. The program turned out to be a massive experience. The two weeks workshop during the break was intense. The first challenge was a day-long assignment where we had to write a code to analyse a set of data. The second challenge was a project following the workshop: Our group decided to code an algorithm which forecasts flight delays. The collaboration and the exchange with the team members of the program was a rewarding experience. The great team spirit and the excellent motivation of the participants were very supportive in tackling the various problems the program offered. Hands-on programming is one pillar of the DSF program, the theoretical foundation on data interpretation is a second pillar. We coded mainly in the programming language R, but we had as well an introduction into the Python programming language as well as into Latex, which is useful to format papers with mathematical syntax. I am happy about this experience, particularly because I learnt elementary techniques regarding the handling of large volumes of data as well as key algorithms of machine learning. I am eager to learn more during the upcoming courses. As a bachelor student in Economics I am using R now frequently mainly for calculations or visualization of data. I strongly encourage you to participate in the DSF program.