1 Day Workshops

Focus on key topics within Data Science

DSFM offers one-day workshops to focus on a particular topic of interest. Perhaps you've taken the DSFM Boot Camp or Fast Track and you need to explore new models, concepts, or options to address a particular problem; or perhaps you've taken the DSFM Boot Camp or Fast Track and now you wish to return with your Data Science team to work on a particular problem; or perhaps you are new to DSFM and one-day Workshops are a good way to try out and get started in the program.

Each Workshop focuses on just one particular issue so you have time to learn a broader range of tools and concepts to work with in that area - no need to spend time in areas you may not need. Workshops are also easier to fit into a busy work schedule without having to plan for extended time away from the office.

      • Each Workshop runs from 10:00 AM to 3:00 PM.
      • The short-day allows you to commute to Lausanne, and/or stay in touch with colleagues at work.
      • We provide lunch - but it is a working lunch so that we have more time for discussion.
      • Each Workshop is limited to 25 participants to ensure that every participant can raise questions as needed.

The preparation required before each Workshop will depend on the Workshop. We will email you a complete list of suggested steps to prepare for each course as you complete your enrollment.

3 Workshops - and more on the way.

Text As Data

Text is an increasingly important aspect of business decisions and business analytics. Text, however, is often captured in non-structured formats, and analyzing text requires a specialized set of tools and machine learning models.

The Text as Data Workshop covers the entire Text Analysis Pipeline, including: natural language pre-processing, text embedding, topic modeling, sentiment analysis, and outcome prediction. The workshop focuses on methods that work on textual big data, and methods that can run at scale.

The Text as Data Workshop focuses more on programming than other DSFM courses - and is intended for participants who have either already taken a DSFM Boot Camp, or otherwise come into the workshop with background experience in Data Science. We will cover the conceptual materials quickly, and then jump straight into working on practical problems and solutions. You should leave the course able to solve real business problems. More specifically, the course will cover:


      • Text pre-processing, spaCy, TextHero, etc.
      • TF-IDF, Word2Vec, Glove, FastText
      • Attention-based methods for text


      • Latent topic modeling (LDA, etc.)
      • Recurrent Neural Networks (RNN, etc.)
      • Deep bidirectional transformers (BERT, etc.)

Preparation: The Text as Data Workshop is a hands on course in Python. We recommend takings the Python Track at JetBrains Academy before the course. It is a great way to go from absolute beginner to fully prepared, but can take up to 30 hours to do it all in detail. It includes interactive, bite-sized exercises and several tools to track the concepts you have studied. Alternatively, we recommend taking the basic course on Python at Kaggle (requires ~ 7 hours if you are new to Python).

Cloud Computing

Big Data often requires using No-SQL databases, virtual machines, remote access, UNIX commands, Spark clusters, transportable containers, Kubernetes orchestration, and platform-as-a-service (PaaS) solutions running in the cloud. As such, cloud computing is quickly becoming an essential part of the machine learning and data science landscape.

Cloud computing, however, also requires an entirely new set of system administration and user-operator skills, as well as a new conceptual understanding of what-does-what, and how it all fits together. Cloud computing can be fast, powerful, and scalable - but cloud computing can also be bewildering to the newcomer.

The DSFM "Cloud Computing Workshop" focuses on system administration and practical use, with real examples running on Google Compute, Amazon AWS, and Microsoft Azure. Basic knowledge of Python and UNIX commands are helpful, but not essential. Please note that the course focuses on the practical aspects of running individual projects on the cloud - and not enterprises-level aspects of setting up or designing cloud architectures, data lakes, or other large IT system/ERP system integration. This course is for the individual data scientist (and/or their team) - not a broad IT department.

Preparation: The Cloud Computing Workshop is a hands on course with practical examples running as UNIX bash scripts, Python programs, Spark-Python programs, and other system administration tasks. You do not need to have advanced skills in any of these domains, although some familiarity with Python, bash, and SQL will help you get more from the course that you can immediately use. We recommend taking the basic course on Python at Kaggle (requires ~ 7 hours if you are completely new to Python).

Data-Driven Strategy

The Machine Learning Revolution in algorithms, the 4th Industrial Revolution in cyber-physical automation, and the Digital Transformation of many companies, are all changing how strategy impacts the firms. Senior executives now have to plan for, and make decisions about, a broad array of technologies and conditions for which they have little formal training. Nevertheless, strategic decisions today are as important as ever.

The DSFM "Data-Driven Strategy Workshop" focuses on the economic fundamentals of strategy, and how those principles apply to the digital and algorithmic world. The importance of algorithmic prediction vs. managerial judgment has shifted, the role of automation and business robotics are challenging old operations, evidence-based reasoning is challenging the Highest Paid Person's Opinion (HiPPO), and competitors are sprinting forward with completely new business models. Against this background, senior management needs a refresh and update as to what strategy means in the digital age.

Preparation: This course involves zero programming - and so there is not preparation needed. Instead, the course focuses on the conceptual models managers need to orchestrate a competitive advantage using the new technologies of Data Science and advanced business analytics.

Please contact us if you have questions.