Data Science Concentration-Carnegie Mellon University Africa - Carnegie Mellon University

Data Science Concentration

This track covers the concepts, methodology and techniques needed throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and providing actionable insights via a dashboard.

The Data Science concentration is designed to train students to become tomorrow's leaders in this rapidly growing area. Through a unique combination of interdisciplinary coursework and cutting-edge research, the programs will enable them to apply techniques and tools of data science to applications drawing on appropriate and relevant concepts and models from the engineering, computing, natural and social sciences.

What skills will the student accquire?

The objective of this concentration is to give students an overview of the potential of data science in research, business and the public sector. Participants will learn how to plan, design and implement an empirical research project using statistical and computational techniques. This will cover the entire data science process from raw data to insights via a dashboard. They will learn how to test for statistically significant relationships and to build decision support tools and offer solutions for business intelligence. Practical skills will be strengthened by discussing project design, data collection, data exploration, data visualization and the advantages and disadvantages of the quantitative models available for different tasks such as forecasting, classification, risk management and decision-making. The course will combine theoretical aspects of data science with visual examples and demonstrations of how to construct and utilize quantitative models in practice. 

What kind of jobs can students expect after graduation?

This concentration can lead students to the following careers in the IT industry:

  • Business analyst
  • Data analyst
  • Data scientist
  • Analytics expert
  • Search engine engineer
  • Business intelligence expert
  • Risk manager

Recommended Courses

Code

Dept

Description

Units

18-899/R1 

ICT/Rwanda

Data and Inference 

6

18-899/R2 

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Applied Machine Learning

6

18-899/R3

ICT/Rwanda

Data Analytics

6

18-899/R4

ICT/Rwanda

Big Data Science

6

04-611 

ICT/Rwanda

Strategic Use of Digital Information in Enterprises

12

91-801 

Heinz/Pgh

Data Analysis for Managers

12

94-842/A4 

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Programming R for Analytics

6

95-797 

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Data Warehousing

6

95-865/A4 

Heinz/Pgh

Text Analytics

6

95-872/A3 

Heinz/Pgh

The Art & Science of Business Analytics

6

95-703

Heinz/Pgh

Database Management

12

95-796

Heinz/Pgh

Statistics for IT Managers

6

95-791

Heinz/Pgh

Data Mining I

6

95-852

Heinz/Pgh

Applied Data Science

6

95-760

Heinz/Pgh

Decision Making Under Uncertainty

6

05-839 

CS/Pgh

The Information Pipeline: Collecting & Computing with Data for Interactive Systems    

12

90-866

CS/Pgh

Large Scale Data Analysis for Policy

6

10-605

CS/Pgh

Machine Learning with Large Datasets

12