Knowledge & Understanding:
1. Demonstrate critical understanding of foundations and principles of data science
2. Demonstrate deep knowledge of fundamental statistical methods, techniques and applications in data science

Intellectual / Professional skills & abilities:
3. Critically assess, select, and apply data collection and cleaning, visualization, statistical inference, predictive modelling, and decision making for statistical analysis in the context of applied data analysis problems
4. Critically evaluate the choice of data science techniques and tools for particular scenarios

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Build a critical awareness of professional, legal, cultural and ethical issues surrounding analysis, exploration, protection and dissemination of data in the context of your role as a data scientist

Knowledge & Understanding:
1. Demonstrate deep knowledge and practical skills for understanding the statistical methods and techniques for data science

2. Critically assess application of adequate techniques for understanding and exploring business data and how it can be exploited for decision making with programming in R

Intellectual / Professional skills & abilities:
3. Appraise and Apply different statistical methods and techniques to real world business environment having to deal with and exploit huge volumes of data using R programming environment

4. Evaluate and reflect on solving real life business problems using suitable statistical techniques

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Build a critical awareness of legal, cultural and ethical issues surrounding analysis, exploration and dissemination of data