Data Science and Big Data


Units: 12


From empirical, to theoretical, to computational science, we are at the dawn of a new revolution---a fourth paradigm of science driven by data. Like archaeological remnants, data, by its very nature, is a marker of what happened in the past. How can data be used to better understand this past and what is happening in the present? How can data be leveraged to forecast what will happen in the future? Better still, how can data be used to mold what should happen in the future? In this course we will study descriptive, predictive, and prescriptive methods by which data can be used to gain insight and inform actions of people and organizations. The real excitement of data science is in the doing. This is an application oriented course requiring skill in algorithmic problem solving. We will use Python based data science tools. Comfort in the Pythonic way of thinking is required as demonstrated by a graded of C or better in one or more of the following courses: 95-880 Python for Developers 95-888 Data Focused Python 95-828 Machine Learning for Problem Solving 95-865 Unstructured Data Analytics If you've taken 15-688 Practical Data Science, due to the significant overlap in these classes, we will not be able to register you for 95-885.

*95885 can not be taken as grade options of pass/fail or auditing. Course needs to be taken for a letter grade. *

Learning Outcomes

Upon successful completion of this course, students will have achieved the following learning objectives:

  • Appreciate the value of data as a strategic resource for organizations
  • Understand core analytics tasks e.g., exploratory data analysis, classification, prediction, optimization, recommendation etc.
  • Hands on experience with data science tools and real-world case studies
  • Exposure to the nature, potential, and tools for processing Big Data

Prerequisites Description

95888 or 95828 or 95865 or 90819