Comprehensive course analysis
Who should attend
This program is designed for business and IT professionals involved in business and IT strategy development and value creation out of IT enabled investments.
Potential participants are holding following positions: C-level executives, IT Director/Manager, Program & Portfolio Manager, Chief Data/Analytics Officer, (chief) Information security Officer (CISO), Data Protection Officer (DPO), Security Manager, Governance, Risk and Compliance (GRC) Officer, Program/Project Manager, Business Analyst, etc.
Participants are active in various types of organizations such as consulting and auditing firms, IT service providers, manufacturing, healthcare, governmental organizations, media, energy & transport, etc.
About the course
Digital transformation has caused changes in all aspects of human life. Nearly a third of European industrial output is attributed to the uptake of digital technologies (COM, 2016). An example to show the massive impact: from 2008 to 2016, the top five e-commerce retailers grew an average of 32% per year, while the entire EU retail sector grew only an average of 1% per year (EC, 2017).
Businesses nowadays not only have access to the sociodemographic data of their customers such as age and gender, but also every contact with the customer, every payment made or product bought is being stored. In these large volumes of data very valuable knowledge is hidden which can be used to improve profitability or increase revenues.
Data science is all about extracting this valuable knowledge from the data.
After attending this program:
- You are able to develop a data science strategy in alignment with your business strategy;
- You understand the performance impact of data science-enabled initiatives;
- You can identify and communicate the company’s data science related business value opportunities and risks;
- You have gained a comprehensive overview and understanding of data science concepts, techniques and applications in a variety of business domains;
- You can identify potential ethical concerns when applying data science in business.
The program consists of 4 chapters, all addressing specific topics. In each chapter, models and concepts are explained and illustrated through cases and exercises. All in-class sessions will be highly interactive, with a lot of focus on sharing experiences and challenging ideas.
Part 1: Data Science Applications in Business
- Introduction to data science and Artificial Intelligence
- Applications in marketing, HR, finance, risk and marketing
- The concepts of overfitting and learning
Part 2: Data Science technologies
- Building predictive models from data using decision trees
- How to evaluate a data science model: from accuracy to profit curves
- Recommender systems
Part 3: Hands-on session using data
- Building models using open source tools (Weka, Python)
- Visualizing data and evaluating models
Part 4: Recent trends
- The importance of ethical data science for business: concepts and cautionary tales
- Deep learning as a game changer in image and speech recognition
- Potential pitfalls in data science projects
- The future of data science in business
Prof. dr. David Martens Professor at University of Antwerp Prof. dr. David Martens is the head of the Applied Data Mining research group at the University of Antwerp. His research focuses on the development and use of predictive data mining techniques for a better decision making process. We sp...
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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.