DSFM

February 6 – 7, 2020

March 2 – 6, 2020

Why take DSFM?

Data Science is becoming a critical skill for every manager. McKinsey projects that Artificial Intelligence will add $13 trillion to global GDP by 2030, and the most innovative companies are rapidly developing new capabilities in machine learning.

Taught on campus in Lausanne by EPFL Professors in the Formation Continue program, DSFM balances theory and application to quickly cover the most-important concepts and models in data science. You will learn in an interactive environment through a combination of lectures, demonstrations, case studies, visualizations, exercises, and applied projects. And perhaps most importantly, you will learn to separate AI-reality from AI-hype.

Testimonials

DSFM – a fast and comprehensive overview of Data Science

This very intensive course gave me a comprehensive overview of a vast and fast-moving domain. The engaging teaching by Prof. Younge and his team – with lectures and many hands-on exercises – helps you to understand the complicated concepts. Hessel Brouwer, Head of Financial Control – Dätwyler

I highly recommend Data Science for Managers! Prof. Younge gives an extensive overview of the field and the course helped me to improve how I work with our Machine Learning engineers. The highly-interactive nature of the demos and teaching assistants also help one to better understand the strengths and limitations of each algorithm. If you need to come up to speed quickly - so you can collaborate with a data science team or spot new opportunities for your business - this course is for you! Alen Arslanagic, CEO – Visium

Excellent Data Science course. Intensive but you get your money's worth. I'd recommend it to anyone interested in the topic and not afraid to put their hands into the real thing. Erwan Grasland, CFO

The course is like a Neural Network on steroids. Content is deep and wide, but very well explained, and delivered with passion by Ken and the team. Roman Schafer, VP Digital Operations - ABB

In DSFM, you learn deep down what it really takes to implement a Data Science project. For me, it was an eye opener. Now I have a better understanding of what is needed in terms of the people, knowledge, IT infrastructure, commitment, and dedicated budget to be successful. This helps to set expectations at a realistic level and to take more appropriate decisions. I'd recommend this course to anyone who needs to understand what it takes to enter the data science world. You will discover new opportunities and huge potential. Professor Younge and his team are passionate about Data Science and are able to transmit their knowledge and experience in a very effective and fascinating way, with a lot of practical demos and exercises. Federico Bernasconi, Head of Business Management, CEMT - Axpo Solutions

DSFM allowed me to be expand my knowledge on how to apply data science to real world situations. This is instrumental to better support my data science team and enhance our organization performance. Gustavo Fernandez, CEO - Bridge

Invest in your Career

Investing in additional training can be critical for your career.

Although massive amounts of data are now generated in all areas of business – a new computational skillset and mindset are necessary to transform big data into real-world, bottom-line results. That is true across many domains, including finance, manufacturing, logistics, supply-chain, engineering, telecommunications, transportation, healthcare, and many others.

DSFM helps executives, managers, and professionals understand when Machine Learning works, and when it does not. You will learn to spot new opportunities for your company to adopt data-driven prediction models – a promising path for advancing your career.

Course Instructors

Prof. Kenneth Younge

    • Head of the Technology and Innovation Strategy Lab at EPFL.
    • Affiliated Faculty for the CODEX Center for Computational Law at Stanford University

Professor Younge teaches the Master's course on Data Science for Business, the Doctoral course on Computational Methods for Management Research, the Executive Education course for Data Science for Logistics for IML (the International Institute for the Management of Logistics and Supply Chain), and Executive Education on Technology and Innovation Strategy. His Masters students, PhD students, and post-doc researchers collaborate with a wide range of Swiss and US companies.

Prof. Chris Tucci

    • Head of the Corporate Strategy and Innovation Lab at EPFL.
    • Former Dean of the College of Management at EPFL

Professor Tucci teaches and conducts research in the area of technology and innovation management (TIM). He focuses on issues of corporate strategy and innovation -- or how large, multi-business firms manage transitions to new technologies, business models, and organizational forms. He teaches in the executive education program at EPFL and continuing education programs at UNIL-EPFL Formation Continue. He is a leading expert on issues of digital transformation and developing a big data strategy.

Topics Covered

Foundational concepts:

      • Data sampling, measurement, and wrangling
      • Data description, visualization, and graphing
      • Bias, variance, and the bias-variance tradeoff
      • Model validation and model cross-validation
      • Hyperparameter tuning and the leakage of information
      • Model evaluation and comparison
      • Model weighting of costs and benefits
      • Ensemble learning and meta-learning
      • Predictive labeling and data augmentation
      • Data-driven business models
      • Big Data, Map-Reduce, and Spark
      • Virtual Machines and Cloud Computing
      • Strategic Planning for a Digital Transformation
      • The management of talent and strategic Human Capital

We also hold brainstorming sessions over lunch to discuss your own projects. These sessions help you to learn more about the challenges and realities faced by other managers in similar positions.

Methods and models:

      • Exploratory data analysis
      • Normalizing and standardizing data
      • Linear models
      • Log-Linear models
      • Non-parametric models, splines and locally-linear models
      • Nearest neighbor and similarity models
      • Agglomerative clustering and K-means clustering
      • Decision trees, bagging, boosting, and random forests
      • Dimension reduction, PCA, t-SNE, and manifold projections
      • Support Vector Machines
      • Text as Data and Natural Language Processing (NLP)
      • Word Embeddings and Latent Topic Modeling
      • Feed-Forward Neural Networks
      • Convolutional Neural Networks
      • Recurrent Neural Networks, LSTMs, Bi-Lateral LSTMs
      • Generative Adversarial Networks
      • Reinforcement Learning

Outline for the 5-Day Bootcamp

The DSFM bootcamp targets a balance between theory and practice, with visualizations, demonstrations, case studies, exercises, and applied problem solving to show the theory in practice. Most managers have forgotten their advanced mathematics, so we emphasize visualizations of mathematical concepts instead of complicated mathematical proofs. The bootcamp is generally divided into conceptual lectures in the morning, a brainstorming session over lunch, a demonstration after lunch, short exercises in the early afternoon, and a mini-project in the late afternoon. We will take time off for breaks, drinks, snacks, and discussion amongst participants.

Most DSFM participants are not professional programmers. We therefore present basic programming concepts and build up to complete solutions for each problem or topic covered. Novice programmers will learn how to read programming code by "backward engineering" solutions; advanced students will learn to program directly from the scikit-learn APIs and build solutions from the bottom-up. In both cases, however, the primary goal is to give you the skills to read computer programming code at a high level so that you can better understand what is going on,and can communicate with more technical data science professionals.

Teaching assistants are available throughout the day to provide one-on-one assistance with practical problems. You will leave the course being able to build, evaluate, and work with real data, and real data science models!

1. Monday

 8:30 -  9:30    Welcome       Course Introduction
 9:30 - 10:30    Discussion    Student Introduction
10:30 - 11:30    Setup         Jupyter & Python 
11:30 - 13:00    Lunch         Q & A     
13:00 - 15:30    LECTURE 1     Core Concepts
15:30 - 16:00    Break         Q & A
16:00 - 17:30    Demo 1        Data Exploration
17:30 - 18:30    Exercises 1   Data Wrangling
18:30 - 19:00    Project 1     The Birthday Problem

2. Tuesday

 8:30 - 11:30    LECTURE 2     Linear Models
11:30 - 13:00    Lunch         Q & A
13:00 - 14:00    Demo 2        Credit Default
14:00 - 15:30    Exercises 2   Simple prediction    
15:30 - 16:00    Break         Q & A
16:00 - 19:00    Project 2     Credit Default

3. Wednesday

 8:30 - 11:30    LECTURE 3     Similarity & Trees
11:30 - 13:00    Lunch         Q & A
13:00 - 14:00    Demo 3        Clustering
14:00 - 15:30    Exercises 3   Complex predictions
15:30 - 16:00    Break         Q & A
16:00 - 19:00    Project 3     Home Sales

4. Thursday

 8:30 - 11:30    LECTURE 4     SVMs & Text Analysis
11:30 - 13:00    Lunch         Q & A
13:00 - 14:00    Demo 4        Sentiment Analysis
14:00 - 15:30    Exercises 4   Dimension reduction
15:30 - 16:00    Break         Q & A
16:00 - 19:00    Project 4     Pre-screening

5. Friday

 8:30 - 11:30    LECTURE 5     Neural Nets
11:30 - 13:00    Lunch         Q & A
13:00 - 14:15    Demo 5        Image Recognition
14:15 - 14:30    Break         Q & A
14:30 - 16:30    AI Strategy   Business Models
16:30 - 17:00    Apero         Award Certificates

Register Now!

We offer two versions of DSFM. A 2-day Executive Fast Track with lectures, case studies, and demos. You don't need to code, but you will see how code can solve real problems. We also offer a 5-day Manager Bootcamp with the same content as the Fast Track, but also applied examples, practicals, programming coding, and solutions.

DSFM courses fill up quickly, so register today!

Executive Fast Track

2-Day Course:

February 6 - 7, 2020 Register now...

Venue:

10 participants in an executive conference room

The Fast Track is limited to 10 participants to ensure high-quality discussion and information sharing within the group.

Objectives:

      • Learn the foundational concepts and vocabulary
      • Identify business outcomes one can predict with AI
      • Learn how AI is changing business strategy
      • Network with others facing similar problems

Fee:

2'400 CHF per participant

250 CHF early-bird discount before December 15th

250 CHF discount for 2+ participants from same firm

Fee includes all materials, lunches, snacks, and refreshments.

Registration closes January 15th.

Manager Bootcamp

5-Day Course:

March 2 - 6, 2020 Register now...

Venue:

40 participants in the spacious Polydôme

The Bootcamp is limited to 40 participants to ensure every participant has an opportunity to work one-on-one with a TA.

Objectives:

      • Cover the same material as the Fast Track, plus...
      • Learn core methods for evaluating and tuning models
      • Learn how to read and interpret Data Science code
      • See a broad range of real-world models and problems

Fee:

4'200 CHF per participant

250 CHF early-bird discount before December 15th

250 CHF discount for 2+ participants from same firm

Fee includes all materials, lunches, snacks, and refreshments.

Registration closes February 14th.

Preparation

No prior training in Data Science is required before taking DSFM.

For the 2-day Fast Track, we will start from basic concepts - so no preparation is necessary before the course. The Fast Track option is designed for the busy executive who only has time to register and then show up for class!

For the 5-day Bootcamp, coding examples and demonstrations will be given in Python. We therefore strongly recommend that you review the basics of Python. At a minimum, please complete the 7-hour Python tutorial by Kaggle before DSFM. Doing so will help you follow along with the demos, examples, and project solutions covered in class. A little bit of prep will help you get much more out of the Bootcamp.

A well-prepared participant will...

      • be familiar with linear algebra (although we use very little math)
      • be familiar with statistics (although we will review the basics)
      • be conversant in English (the course will be given in English)
      • bring a a laptop (Mac, Windows, Linux, Chromebook are all ok)

Do not fear! We will have several highly-qualified EPFL graduate students on-hand to help you throughout the course. TAs will work with you one-on-one to answer questions about the demos, examples, and programming code.

Contact

Please email us if you have any questions or about registration or logistics:

support@dsfm.ch


Please contact Professor Younge if you have any questions about the course:

https://people.epfl.ch/kenneth.younge


DSFM Alumni Network

Graduates of DSFM are invited to join the DSFM Alumni Network.

We have found that DSFM participants in previous sessions come together as a community and then want to keep in touch. Given the pace of change in machine learning, automation, and digital transformation – the alumni network is a great way to keep in touch with other professionals who are facing the same problems that you are. We therefore organize an annual Lecture and Apéro for the DSFM Alumni Network in the fall and invite graduates to join us at the EPFL College of Management for the event.

Membership in the alumni network is free – and there is no cost for the Apéro. Just graduate from the course, get your certificate, and then come meet other like-minded professionals once a year to stay up on current trends. We look forward to seeing you at the next Apéro!

Please join us for the First Annual DSFM Alumni Apéro

We are planning the event – alumni will hear from us soon.