Business analysts and programmers are getting more and more into contact with advanced analytics. Although not the core of their job, it is important that they gain an initial understanding of what it is, and what value it can bring to their organization. Therefore, we have created a 2-day introductory course in Data Science explaining all the important concepts, and the process that leads to a successful project. We end the course with practical examples and applications of machine learning to give food for thought for all participants.
This 2 day training is an excellent opportunity to get up to speed with all the concepts of Data Science, without getting into the nitty-gritty details. After this training, the participants should have enough knowledge to answer the question: “would advanced analytics help to solve this business problem?”.
- Business analysts, Customer Insights analysts, Financial analysts
- Experience with traditional BI tools like Excel and SPSS, no specific progamming knowledge needed
- basic mathematical and statistics knowledge
- Enthusastic and eager to learn about Machine Learning and Data Science
- What’s changing in the world and why are we here today
- Statistics, Machine Learning and Artificial Intelligence: what’s it all about?
- Theoretical overview of statistics
- Machine learning: models and feature importance
- Artificial intelligence
- Data science methodology
- Data Discovery and preparation
- Data Visualization: types of visualization and outcome
- Data preparation process
- What about outliers
- Missing values
- Features and how to define them
- The process of Machine Learning and practical examples
- The machine learning process
- Model performance evaluation
- Embedding Machine learning solutions in your organization and practical examples
- Concrete & practical examples of machine learning