Data science is a discipline that uses scientific methods, processes and algorithms to extract meaningful information, knowledge and insights from structured and unstructured data.
The aim of this course is to provide insights on intermediate and advanced data science topics, using the Python programming language. The course will explore concepts such as machine learning, deep learning and natural language processing from a practical hands-down point of view. The focus will be on tools and methods rather than diving into the theoretical basis, in order to be appreciated by an audience with a minimal mathematical background.
Experience in using a programming or scripting language is a must. The student should master all the concepts explored in the course "Python Programming for Data Science - Part 1".
In order to complete the assignment (and in order to get the full benefit from the course) students will need access to a computer capable of running the open-source software used in the course and access to the Internet. A limited amount of class time will be allocated to working on the class assignment, so students should ensure that they have access to a computer outside of class.
The course will rely on Jupyter Notebooks for interactive Python programming as they are widely used in Data Science.