D4GC
Workshops

Learn how to crack a case with the guidance of McKinsey consultants. After an introduction to our 7-step problem solving approach, you will get the chance to apply this framework to a real case. This interactive workshop will help you gain better understanding of the type of problems McKinsey consultants solve day by day, as well as hone your problem-solving skills.

This workshop will enable you to re-evaluate your own presentation skills and existing presentation style. It will further provide you with additional skills and techniques to help you prepare and deliver excellent presentations that are engaging and impactful.

Natural language processing has rapidly developed since the advent of transformer networks. In this workshop we go over these recent developments and show how these language models are used in practice.

An interactive explanation on the principles of data visualization followed by a hands-on session where you will visualize a dataset in Google Data Studio.

As the amount of data increases and algorithms become increasingly complex, humans have more trouble understanding their inner workings and explaining their predictions. In the last years, the research community has turned its attention to interpretability and solutions have been rapidly adopted by the industry. This workshop gives a brief introduction to this problem and the methods that have been proposed in the past years. We zoom in on some of the more popular methods and discuss their strengths and weaknesses. After the workshop you should be able to select and apply techniques suitable for your project.

This workshop will give an introduction on how to use Power BI to visualize your data in several steps. Importing your data into Power BI, the importance of data cleaning, creating a data model and building features. Additionally, tips and tricks to create appealing visualizations will also be part of the workshop.

Would you like to learn how to solve a Data Science case? This workshop will include: Data preparation with Pandas, feature engineering, data science methodology, basic modelling and interpreting results using a data case study. Finally a summary of all the important points will presented.

How many visitors can we expect next week, will the water pass the borders the next hour, how busy will it be on the bus tomorrow, … are all Business questions that can be answered with a timeseries analysis. In the first part of this workshop, we will introduce the concept of timeseries. We will give some basic tips and tricks on how to visualize, model and predict them. The second part of the workshop will be hands-on. Inspired by a notebook you will explore the concepts and techniques, the programming language will be Python.

In this workshop, we will walk you through the construction of graphs (nodes and edges), the basic and more advanced algorithms (shortest path, page rank, etc) that can be used. Finally, we will introduce graph neural networks and go through example cases that can be modelled and solved with graphs. In the second part of the workshop, we will demonstrate these concepts with python.

We’ll start the workshop with an overview of AI applications in banking (marketing, risk, insurance, fraud…), and going into some more details on the use case of anti-money laundering: how does machine learning guarantee good screening of transaction behaviour?

Next, we’ll zoom on the life cycle of a machine learning model in a big corporate:

• Model development: feature engineering, target definition & time-line, ML technique, ethical AI (fairness, bias, …)
• MLops: the CI/CD to bring a ML model in a production environment in a corporate
• Model monitoring: different kinds of drift to check if your model is still doing well
• Explainable AI: how to explain the ML scores to end-users

Have you ever wondered what Amazon’s rapid innovation looks like? How do they do it? An exclusive opportunity for you to learn all about what makes Amazon peculiar is presented by its AWS Digital Innovation team through an interactive session that will gives you a sneak peak about how we rapidly innovate new product and service ideas. This interactive session is one where we get hands on to help you define a new product, service, or experience using a customer-centric mechanism for rapid experimentation. This interactive engagement is inspired by the same customer-centric methods used by Amazon to develop breakthrough innovations our customers love, such as Amazon Prime, Amazon Kindle, AWS, Amazon Echo and Alexa. You will learn how to work backwards from a customers’ needs to define a winning solution powered by digital technology.

Sports are data rich, and making sense of that data is the first step in making it an advantage on and off the pitch. Cloud and machine learning technologies are helping sports leagues and teams create memorable fan experiences, transform broadcast products, and invent new ways to improve player health and safety. AWS, Bundesliga’s Official Cloud and Machine Learning Provider, will share stories across a variety of sports and share how machine learning is becoming the most valuable player in sports.

This workshop will focus on learning how to use Python interactively using DataCamp Workspace. Workspace is an online IDE that allows you to write code, analyze data collaboratively and share your data insights. You will learn about Python’s basic data types, functions, methods, and packages, with a focus on solving optimization problems.