Foundation of Big Data Analytics

We Study introductory mathematical and programming tools for big data analytics, in particular focusing on recently successful real-world applications, e.g., web search, spam filtering, crowd-sourcing, visualization, and recommendation system


  • In this course, we discuss such various topics in probability theory and introductory random processes as probability, random variables, expectations, characteristic functions, random vectors, random processes, correlation functions, and power spectrum. From time to time, homework problems will be assigned, usually not for mandatory submission.

  • This course is to provide EE students with understanding and ability for design and implementation of data structure for problems solving in the EE area using computer programming. It deals with information representation using data abstraction, object-oriented programming, Algorithm analysis. Basic data structures to be covered are Array and Linked list, Stack and Queue, Tree, Graph, Sorting, and Hashing. Applications of such basic structures in EE problems using C++ are also covered.

  • Much of the basic discrete mathematical tools useful in electrical and computer engineering will be presented, with applications. Students will learn actively the art of creating real-world proofs in these areas, preparing them for diverse regions of electrical and computer engineering such as communication, architecture, networking, algorithms, cryptography, etc.

Show List