Core tools for facilitating reproducible data science workflows are version control tools such as Git, virtual environment tools such as Conda, and container technologies such as Docker. KVL has ...

Introduction to Python for Data Science In this module, you will explore the basics of Python. Python is in the 4th most popular programming language used by professional developers (not just Data ...

Introduces students to importing, tidying, exploring, visualizing, summarizing, and modeling data and then communicating the results of these analyses to answer relevant questions and make decisions.

The module will provide an introduction to data science principles and techniques for masters students on psychology and neuroscience programmes. Topics covered will include: 1. The role of code in ...

Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

and Society Introduction to Artificial Intelligence Introduction to Data Analytics Advanced Data Analytics. The final unit, a Data Science mini-project, is a group activity which will be aligned, ...

MLDS-413 teaches data engineering skills that are essential for “data science” practitioners, in particular, how to model, organize, store, and analyze data in modern relational database management ...

For an introduction to data science, we recommend: G Grolemund and Hadley Wickham R for Data Science (O'Reilly Media, 2016) JV. Guttag Introduction to Computation and Programming using Python (Second ...

The goal of this course is to provide future analytics and data science professionals with the practical skills needed to visualize data effectively and tell compelling stories with data. Students ...

Discover how data science can help us solve real-world problems. Gain quantitative skills to prepare you for a range of professional and managerial careers. Our BSc Data Science brings together the ...

The MSc degree in Data Science consists of 120 credits divided into core courses, data science specialisation courses, and other courses, as described below. You can specialise either in the core ...

These courses will build skills necessary for successful completion of the MS in Data Science. Some students will not need to take these foundational courses and will instead use the domain electives ...