MSDS Program Requirements

MSDS Graduation Requirements


SUMMER 1: DATA SCIENCE BOOT CAMP

 

  • Relational Databases (1)

Plus two of the following:

  • Computation for Analytics (1)
  • Review of Linear Algebra (1)
  • Review of Probability and Statistics (1)

FALL MODULE 1

 

  • Linear Regression Analysis (2)
  • EDA and Visualization (1)
  • Communications for Analytics (1)
  • Data Acquisition (2)

Fall MODULE 2

 

  • Introduction to Machine Learning (2)
  • Machine Learning Laboratory (1)
  • Time Series Analysis (2)
  • Practicum I (1)
  • Distributed Computing (1)

INTERSESSION

  • Distributed Data Systems (2)

SPRING MODULE 1

 

  • Case Studies in Data Science (2)
  • Advanced Machine Learning (2)
  • Data Structures and Algorithms (1)
  • Practicum II (2)

Spring MODULE 2

 

  • Ethics in Data Science (1)
  • Experiments in Data Science (2)
  • Product Analytics (2)
  • Practicum III (2)

SUMMER 2

 

  • Special Topics in Analytics (2) *
  • Practicum IV (1)

* Special Topics may include deep learning, reinforcement learning in AI, natural language processing and numerical linear algebra.

In addition to the above, all students complete 10 hours of required interview skills training to be completed outside of class time. Trainings are provided by the Data Science program and may include but are not limited to: workshops, mock interviews, resume editing and guest lecturers.