Fundamentals of Data Science

The goal of this course is to demystify data science and to familiarize students with key data scientist skills, techniques, and concepts.

Starting with foundational concepts like analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, the course will then move on to compare data science with classical statistical techniques.

An overview of the most common techniques used in data science, including data analysis, statistical modeling, data engineering, relational databases, SQL and NoSQL, manipulation of data at scale (big data), algorithms for data mining, data quality, remediation and consistency operations will be covered.

Required prerequisites: I&C SCI X425.99 Practical Math and Statistics for Data Science and Analytics AND I&C SCI X426.64 Introduction to Python Programming