Introduction to Data Science
Dive into the world of data-driven decision-making with our comprehensive Data Science course. Designed for professionals from diverse backgrounds this course equips you with essential skills to harness the power of data for insightful analysis and predictive modeling.
Practical information:
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- Price: SMEs and midcap: Free ; Large companies and participants without a company: € 6746
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In the first part of the course, we will provide solid theoretical bases, introducing core concepts in data science such as data types, data formats, data quality issues and predictive modeling. In order to facilitate application in practical settings, these concepts will be directly related to existing use cases under the supervision of the course lecturers. For the second part of the course, we will employ industry standard Python packages (e.g. pandas, numpy, scikit-learn), to develop a prototype of a data analysis pipeline. Participants are assumed to already have a working knowledge of programming (ideally Python), but additional self-learning resources will be provided if needed.
Course Content
- Introduction to Data Science and Data Analytics
- The four flavors of Data Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
- Implementing a data analysis pipeline with Python
- Data Science in Practice: Do’s, Dont’s and Ethical considerations
Learning Outcomes
By the end of this course you should be able to:
- Explain the core concepts involved in a Data Science project (i.e data types, data storage, data analysis, predictive modeling);
- Examine an existing situation to identify what suitable Data Science methodologies and analysis are applicable
- Develop a prototype of a data analysis pipeline using Python and its data science toolkit (pandas, seaborn, sci-kit learn, …)