DSFM

Why take DSFM?

Data Science is becoming a critical skill for every company. In the next 10 years, McKinsey projects that over 70% of firms will adopt at least one type of Artificial Intelligence, and AI will add $13 trillion to global GDP. As such, the most innovative companies are rapidly developing new capabilities in machine learning and data science.

Taught in Lausanne, Switzerland by Professors from EPFL, DSFM balances theory and solutions 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.

Perhaps most importantly, you will learn to separate AI-reality from AI-hype.

Testimonials

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. I'd recommend this course to anyone who needs to understand what it takes to enter the data science world. 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

A fast and comprehensive overview of Data Science.

Course Description

We offer two versions of DSFM:


  • 2-Day Executive Fast Track: The Fast Track summarizes the core concepts and methods of Data Science and then explores the strategy of digital transformation through specific examples, case studies, and group discussions.
  • 5-Day Technical Boot Camp: The Boot Camp covers the same material as the Fast Track, but goes into much more depth and detail with respect to the methods, applications, problems, and programming code of building solutions. The Executive Fast Track is also designed to bring foth more discussion from executives about the relative tradeoffs between different options, strategies, and past experience.

2-Day Fast Track

Foundational concepts:

      • Exploratory data analysis, visualization, and graphing
      • Bias, variance, and the bias-variance tradeoff
      • Model evaluation and comparison
      • Core machine learning methods
      • Text analysis and topic modeling
      • Neural Networks & Reinforcement learning

Strategic planning:

      • Data-driven business models
      • Big Data and Cloud Computing
      • Data capture and data augmentation
      • Cost/benefit tradeoffs
      • Digital Transformation of culture and the organization
      • Strategic Human Capital

Day 1: Thursday

  8:30 -  9:00   Welcome Coffee
  9:00 - 10:30   Core Concepts
 10:30 - 12:00   ML Methods & Models 
 12:00 - 13:30   Lunch           
 13:30 - 15:00   Neural Networks
 15:00 - 15:30   Break          
 15:30 - 16:15   Demonstrations
 16:15 - 17:00   Cloud & Data Engineering
 17:00 - 18:00   Break / Hotel
 18:00 - 20:00   Apéro

Day 2: Friday

  8:30 -  9:00   Welcome Coffee
  9:00 - 10:30   AI Applications 
 10:30 - 12:00   AI Strategy 
 12:00 - 13:30   Lunch           
 13:30 - 15:00   Digital Transformation
 15:00 - 15:30   Break          
 15:30 - 17:00   Group Discussion

* The social event at the end of the first day is optional, and some participants may need to return home. We will have a guest speaker join us for the event and/or have other opportunities to network with practitioners from industry.

5-Day Boot Camp

The Technical Boot Camp offers a balance between theory and practice, with visualizations, demonstrations, exercises, case studies and projects.

There are conceptual lectures in the morning, an interactive discussion over lunch, a demonstration after lunch, short exercises in the early afternoon, and a mini-project in the late afternoon.

We also take many breaks to have time for drinks, snacks, and discussion amongst participants.

Foundational concepts:

      • Data sampling, measurement, and wrangling
      • Exploratory data analysis
      • Data description, visualization, and graphing
      • Bias, variance, and the bias-variance tradeoff
      • Model validation and model cross-validation
      • Hyperparameter tuning and information leakage
      • 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

Methods and models:

      • Normalizing and standardizing data
      • Linear and 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

Most managers have forgotten their advanced mathematics, so we emphasize visualizations of mathematical concepts instead of complicated proofs. Moreover, most boot camp participants are not professional programmers. We therefore present basic programming concepts and build up to complete solutions.

Novice programmers will learn how to read programming code provided in solutions; more advanced students will learn to build thsoe solutions from the bottom-up using scikit-learn APIs. Teaching assistants are available throughout the day to provide one-on-one assistance with practical problems. All participants will leave the course being able to build, evaluate, and work with real data and real models!

Day 1: Monday

  8:30 -  9:30   Welcome                            
  9:30 - 10:30   Motivation   Class 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   Exercise 1   Data Wrangling        
 18:30 - 19:00   Project 1    The Birthday Problem  

Day 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   Exercise 2   Simple prediction     
 15:30 - 16:00   Break        Q & A                 
 16:00 - 19:00   Project 2    Credit Default        

Day 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   Exercise 3   Complex predictions   
 15:30 - 16:00   Break        Q & A                 
 16:00 - 19:00   Project 3    Home Sales            

Day 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   Exercise 4   Dimension reduction   
 15:30 - 16:00   Break        Q & A                 
 16:00 - 19:00   Project 4    Pre-screening         

Day 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        Certificates          





Instructors

Prof. Kenneth Younge is an Associate Professor at EPFL, the Chair of the Technology and Innovation Strategy Lab, and Program Director for DSFM. He has started four companies and worked in the roles of Director of Development, Consultant, CTO, and President.

Professor Younge currently teaches the Masters course on Data Science for Business, the Doctoral course on Computational Methods for Management, the IML course on Data Science for Logistics, and an eMBA course on Technology and Innovation Strategy. His research focuses on computational economics and digital transformation. His doctoral students and post-doctoral researchers collaborate with a wide range of Swiss and US companies on ongoing research projects.

We organize interactive lunch sessions during the DSFM Boot Camp. Additional professors and industry experts join the class to meet with small groups of DSFM participants to discuss particular topics of interest. Each discussion leader is an expert in a given area. Examples of discussion leaders include:

Prof. David Atienza is an Associate Professor at EPFL and expert on embedded systems for the Internet of Things (IoT). He leads a discussion on how smart wearables, wireless sensors, edge computing, and embedded machine learning work together to create new business opportunities.

Prof. Chris Tucci is the former Dean of the College of Management at EPFL and an expert on issues of design thinking and digital transformation. He leads a discussion on how firms construct data-driven strategies to transition to new technologies, business models, and organizational forms.

Prof. Dimitrios Kyritsis is an Adjunct Professor at EPFL and Director of the Doctoral Program on Robotics, Control and Intelligent Systems. He is an expert on the management of data and information flows, and D-I-K (Data-Information-Knowledge) transformations all along the lifecycle of products.

Prof. Negar Kiyavash is a Full Professor at EPFL and Chair of Business Analytics in the the College of Management. She is an expert on causal inference from networked big data and teaches on advanced topics in machine learning, artificial intelligence, optimization, and data science.

Prof. Bob West is an Assistant Professor at EPFL and head of the Data Science Lab in the School of Computer and Communication Sciences. His research aims to make sense of Big Data collected from the Web, such as server logs, social media, wikis, online news, online games, etc.

Prof. Jeffrey Kuhn is an Assistant Professor at the University of Carolina and a US patent attorney. He leads a discussion on how AI algorithms and proprietary methods can best be protected as either intellectual property or trade secrets.

Prof. Alex Biedermann is an Associate Professor at the UNIL Ecole des Science Criminelles and an expert on decision-making under uncertainty. He leads a discussion on how computational methods can support a more systematic approach for automating decisions.

Dr. Christopher Bruffaerts is a lecturer at the College of Management at EPFL and instructor for the Masters course on Data Science in Practice. He has worked on customer analytics, fraud detection, and big data technologies at BNP Paribas Fortis, Credit Suisse, and UPC.

Invest in your Career

Continuing education can be critical for your career.

Although massive data is now generated in all areas of business – a new computational skillset and mindset are required to transform that 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, engineers, and other 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 models – a proven path for advancing your career.

Upgrade your skills today and move to the forefront of the Data Science revolution.

Registration

Executive Fast Track

Fast Track - February 6 - 7, 2020 - Full

Fast Track - April 2 - 3, 2020

Fast Track - June 25 - 26, 2020

Fast Track - October 8 - 9, 2020

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:

3'200 CHF per participant

250 CHF early-bird discount before February 15th

250 CHF discount for 2+ participants from same firm

Fee includes all textbooks and all materials.

Fee includes lunches, snacks, and refreshments.

Technical Boot Camp

Boot Camp - March 2 - 6, 2020 - Full

Boot Camp - June 8 - 12, 2020

Boot Camp - September 7 - 11, 2020


Venue:

40 participants in a lecture hall or conference center

The Boot Camp is limited to 40 participants to ensure every participant will have time 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 textbooks and all materials.

Fee includes lunches, snacks, and refreshments.

DSFM courses fill up quickly, so register today!

Preparation for your course

No prior training in Data Science is required to take DSFM.

However, a little bit of preparation will help you to get the most out of the course.

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

For the 5-day Technical Boot Camp, 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.

To get the most out of your course, you 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 be available to work with you one-on-one to answer questions about the programming code.

DSFM Alumni Network

We have found that participants in DSFM often come together as a community during their course and then want to keep in touch. The DSFM alumni network is a great way to network with other professionals facing the same problems that you do. We organize an annual Guest Lecture and Apéro for the DSFM Alumni Network and invite graduates to join us at EPFL for the event.

Membership in the alumni network is free, and there is no cost for the Apéro. Just graduate from a DSFM course, get your certificate, and joins us at an event. We look forward to seeing you at the next Apéro!

DSFM Alumni Apéro

Unfortunately, have had to postpone the alumni event on the evening of February 6th as our speaker will no longer be able to join us. We are hard at work looking for another speaker and a future date, and we will update alumni soon with details via the DSFM Newsletter.

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