Advanced Programming

GENERAL DESCRIPTION OF THE COURSE

In this course three advanced topics are taught in order to complement the knowlege acquired in the master, so that data science and data analysis skills of students are improved: combining C++ and R in order to improve R efficiency; basic knowledge about Python and its data, machine learning, and visualization libraries; and basic knowledge about the statistical Stan language.

OBJECTIVES: KNOWLEDGE AND SKILLS

Knowledge:

• Concepts about C++ necessary for integrating this language with R.
• Basic concepts of base (core) Python.
• Main concepts about machine learning stages and its use with R.
• Basic concepts about data visualization.
• Basic concepts about probabilistic programming.

Skills:

• Use of RCpp for integrating C++ and R.
• Advanced use of Python, its main data libraries (numpy and pandas), its main machine learning library (scikit-learn), and its main visualization libraries (matplotlib and seaborn).
• Basic use of RStan.

TEACHING MATERIAL

Slides for the lectures, that include some tutorials and exercises.

 PRACTICAL ASSIGMENTS AND ASSESSMENT ACTIVITIES

Lab materials for practicing R and C++ integration, Python, Machine Learning, and data visualization.

Exams (with answers) for self-evaluation.