Big Data: Data Science and Business Analytics
Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with Católica Lisbon School of Business & Economics.Full disclaimer.
The amount of data available reached incalculable dimensions with the advancement of the information systems, so it is vital their treatment and analysis to support companies strategic decisions.
This program aims to provide analytics professionals a deeper view and understanding of the concepts and methodologies used in scientific research over large datasets that can be applied and implemented in industry contexts, with direct impact on firms’ performance.
The Business Analytics: Data Science and Big Data program combines theoretical lectures with hands-on sessions. The program is designed to walk participants along the typical phases of a data analytics project, starting with business understanding, followed by data collection and interpreting descriptive statistics, then moving into simple and advanced predictive modeling, to conclude with the design of randomized experiments to try to establish causal effects.
- Understand how to use Big Data Processing Systems (Hadoop, Hive, Spark);
- Understand how to use cloud computing infrastructures, replicable in any business context;
- Implement the latest theories on data analysis, including the predictive and causal deduction methods;
- Use some statistical programming language that allows the company to put into practice the new methods of machine learning and causal modeling (R language);
- Understand how to assess companies data assets value and how to measure the effect of every change.
Who should attend
The ideal students for this program are individuals who have a strong interest in data analysis for business decision making. Requires a background in intro level statistics; basic programming skills (in any programming language) and the understanding of programming concepts such as variables, functions and loops.