Data Science

DSA ADS Course 2023

This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.

Discuss application of data science for decision making in real world scenarios.

DSA ADS Course - 2023

This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world investing / trading scenarios.

DSA ADS Course 2023

This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.

Discuss building data science teams in real world scenarios.

DSA ADS Course 2023

This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.

Discuss mining of massive datasets in real world scenarios.

DSA ADS Course - 2023

This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world investing / trading scenarios.

Discuss application of probability theory in real world investing / trading scenarios.

DSA ADS Course - 2023

This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.

Discuss enabling marketers to dynamically segment their customer base and to examine methods by which the firm can alter long-term buying behavior.

Discuss dynamics of customer relationships using typical transaction data.

DSA ADS Course - 2023

Avrim Blum, John Hopcroft, Ravindran Kannan  - June, 2016 

Introduction:

Computer science as an academic discipline began in the 1960’s. Emphasis was on programming languages, compilers, operating systems, and the mathematical theory that supported these areas. Courses in theoretical computer science covered finite automata, regular expressions, context free languages, and computability.