Data Science

Foundations of Data Science Graduate Certificate 

Purdue’s Foundations of Data Science Graduate Certificate gives students the opportunity to learn in-demand data science skills in less time than a traditional master’s degree – making fast career advancement accessible and affordable. This new 100% online certificate program is designed for current graduate students who want to add data science coursework to their plan of study or professionals who want to learn foundational skills while saving time and money. Take courses in essential data science skills like data mining, data visualization, and data analysis without needing to commit to a full degree program. 

Ready to Dive into the world of Data Science?

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Fast Track Your Way to Becoming a Data Science Expert

  • Build in-demand data science skills in less time and for less money than a traditional graduate degree.
  • Gain expertise in in-demand areas like machine learning, data visualization, data mining, project management and more. 
  • Fast-track your career in data science by earning a credential on an accelerated timeline.
  • Take classes in the areas that interest you and stack skills for career advancement. 

Ready to Dive into the world of Data Science?
9 Total Credit Hours
3 Total Courses
$933.33 Per Credit Hour
9 Total Credit Hours
3 Total Courses
$933.33 Per Credit Hour

Source: LightcastTM (2023). Unique job postings for July 2022-2023. Projected growth for years 2023-2033.

Foundations of Data Science Graduate Certificate

Curriculum Overview

This graduate certificate requires 9 credit hours with 6 required credit hours within the graduate school and 3 credit hours can be taken from technical or professional elective hours below.  

All students are required to take the following 3 credit hour course:  

  • GRAD 50500 – Foundations in Data Science (3 credits) 

Choose one of the following 3 credit hour courses: 

  • GRAD 50600 – Big Data Tools and Technologies (3 credits) 
  • GRAD 50700 – Cross Domain Data Communication and Visualization (3 credits) *
  • GRAD 50800 – Data Analytics (3 credits) 
  • GRAD 50900 – Applied Machine Learning: From Foundations to Latest Advances   (3 credits) 

The following courses are approved substitutes for GRAD 50700:

  • CGT 57500 – Data Visualization (3 credits)
  • SCLA 51000 – Data and AI Storytelling (3 credits)
  • MIS 59300 – Business Data Visualization and Analytics (2 Credit Hours)
  • OBHR 69000 – Business Storytelling in Data (2 Credit Hours)

Students can choose any of the following courses (or any concentration course in the Master of Science in Data Science) to reach the required 9 credits and complete their graduate certificate:

  • CNIT 51000 – Data Literacy (3 credit hours)
  • CNIT 53600 – IT Policy, Law and Ethics (3 credit hours)
  • CNIT 53700 – Professional Research and Communications (1 credit hour)
  • CNIT 58100 – Database Fundamentals (3 credit hours)
  • CNIT 58100 – Enterprise Data Management (3 credit hours)
  • CNIT 58100 – Information Security Governance (3 credit hours)
  • COM 60311 – Seminar in Crisis Communication (3 credit hours)
  • CS 50023 – Data Engineering (1 credit hour)
  • CS 50025 – Foundations of Decision Making (1 credit hours)
  • CS 57700 – Natural Language Processing (3 credit hours)
  • ECE 50874 – Advanced Software Engineering (3 credit hours)
  • ECE 56900 – Introduction to Robotic Systems  (3 credit hours)
  • ECE 59500 – Computer Vision for Embedded Systems (1 credit hour)
  • ECE 60864 – Advanced IoT Design & Applications (3 credit hours)
  • ECE 69500 – AI Foundation Model Basics (1 credit hour)
  • ECE 69500 – Big Data For Reliability and Security (1 credit hour)
  • ECON 57700 – Quantitative Economics and Python (2 credit hours)
  • EDPS 53100 – Introduction to Measurement and Instrument Design (3 credit hours)
  • MA 51100 – Linear Algebra with Applications (3 credit hours)
  • MKTG 52500 – Marketing Analytics (2 credit hours)
  • SCOM 52600 – Project Management (2 credit hours)
  • SCOM 56800 – Supply Chain Analytics (2 credit hours)
  • MIS 57600 –  Database and SQL (2 credit hours)
  • MIS 58600 – Python Programming (2 credit hours)
  • MIS 58700 – Using R for Analytics (2 credit hours)
  • MIS 59900 – AI-Assisted Big Data Analytics in the Cloud (2 credit hours)
  • OBHR 69000 – Business Storytelling in Data (2 credit hours)
  • OLS 58000 – Interpersonal & Group Skills for Leaders (3 credit hours)
  • PHIL 50000 – Advanced Ethics for Technology, Engineering, and Design (3 credit hours)
  • PHIL 50800 – Advanced Ethics in Data Science (3 credit hours)
  • PHRM 50000 – AI and Its Use in Clinical Care (2 credit hours)
  • SCLA 50900 – Strategic Intelligence: Organizations, Technologies, Procedures, Policies (3 credit hours)
  • SCLA 52000 – Social and Digital Media Analytics For Strategic Communication (3 credit hours)
  • SCLA 52100 – Societal Impacts of Artificial Intelligence (3 credit hours)
  • SCLA 52200 – Artificial Intelligence Policy, Governance, and Ethics (3 credit hours)
  • STAT 50600 – Statistical Programming and Data Management  (3 credit hours
  • STAT 51200 – Applied Regression Analysis (3 credit hours)
  • STAT 52700 – Intro to Computing for Statistics (3 credit hours)
  • STAT 58200 – Stat Consulting & Collaboration (3 credit hours)

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