ECE 398BD

MAKING SENSE OF BIG DATA

Spring 2014


ECE 398BD is a project based undergraduate course exploring a holistic view towards understanding how this data is collected, represented and stored, retrieved and computed/analyzed upon to finally arrive at appropriate outcomes for the underlying context. The course is based around four stories, drawn from diverse areas of electrical and computer engineering. The course is thus divided into four parts, covering topics from audio/video data, satellite/climate data, genomic data and social networking data. Each part is covered by different sets of instructors, outlined below.

Course Syllabus

Prerequisites: ECE 313 or STAT 400 or STAT 410 or IE 300 or equivalent

Lectures: Mondays and Wednesdays, 9-9:50am, 106B8 Engineering Hall

Labs: Fridays, 9am-noon, 57 Grainger Library

Instructors: Minh N. Do, Wen-Mei Hwu, Farzad Kamalabadi, Jonathan Makela, Olgica Milenkovic, Pierre Moulin, and Pramod Viswanath

Homeworks:

  1. HW 1
  2. HW 1 - solutions
  3. HW 2
  4. HW 2 - solutions
  5. HW 3
  6. HW 3 - solutions
  7. HW 4 (due 9 a.m. Friday, April 25)

Quizzes:

  1. Feb 26 (Machine Learning and Image Analysis)
  2. Mar 12 (Hypothesis Testing)

Lecture notes:

  1. Lecture 1
  2. Lecture 2
  3. Lecture 3
  4. Lecture 4
  1. Acoustic features and speaker recognition
  2. Lecture 5
  3. How does Shazam work?
  4. Lecture 6
  5. Color indexing (local copy)
  6. Lecture 7
  7. SIFT: Distinctive image features from scale-invariant keypoints
  8. Lecture 8
  9. Adaptive background mixture models for real-time tracking
  10. Lecture 9: Video Background Subtraction Demo  
  11. Massive audio and video analytics using deep learning
  1. Lecture 10
  2. Allen and Ziv, Application of real-time GPS to earthquake early warning
  3. Langley, Dilution of Precision
  4. Lecture 11
  5. Lecture 12
  6. Lecture 13
  7. Lectures 14-15
  1. Lecture 16: Introduction to Bioinformatics
  2. Lecture 17: Dynamic Programming Algorithms
  3. Lecture 18A: BLAST (Broad Institute Lecture Notes)
  4. Lecture 18B: RNA Folding (Lecture notes in week 10)
  5. Lecture 19: Burrows-Wheeler Transform
  6. Lecture 20: Suffix Trees
  7. Lecture 21A: Assembly
  8. Lecture 21B: Lander-Waterman Analysis

Lab TA's:

Labs:

  1. Lab 1
  2. Lab 2
  3. Lab 3
  4. Lab 4
  5. Lab 5
  6. Lab 6
  7. Lab 7
  8. Lab 8 (due Sat Mar 22, 11:50 am)
  9. Lab 9 (due Fri, Apr 4, 11:50 am)
  10. Lab 10 (due Fri, April 11, 9:00 am)
  1. Lab 11 (due Sun, April 20, 9:00 am)

Credit: Tech elective with two lecture unit credits and one unit of lab credit

Office hours:

  1. Minji: 2-4 p.m. April 24, 125 CSL