Add learning outcomes and credit info.

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Justin Hsu 2018-08-27 18:53:40 -05:00
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Lectures will be loosely organized around **four modules**: differential
privacy, cryptography, language-based security, and adversarial machine
privacy, applied cryptography, language-based security, and adversarial machine
learning. I will give most of the lectures for the first module (differential
privacy). For the other modules, I will give an introductory lecture surveying
the topic and background material. Then, each student will lead one lecture,
@ -50,6 +50,28 @@ Grades will be assigned as follows:
- **Paper presentation: 25%**
- **Final project: 60%** (First and second milestones, and final writeup)
## Learning Outcomes
By the end of this course, you should be able to...
- Summarize the basic concepts in each of the four course modules: differential
privacy, applied cryptography, language-based security, and adversarial
machine learning.
- Use standard techniques from differential privacy to design privacy-preserving
data analyses.
- Grasp the high-level concepts from research literature on the main course
topics.
- Present and lead a discussion on recent research results.
- Carry out an in-depth exploration of one topic in the form of a self-directed
research project.
## Credit Information
This is a **3-credit** graduate seminar. We will meet for two 75-minute class
periods each week over the fall semester, and you should expect to work on
course learning activities for about 3 hours out of classroom for every class
period.
## Academic Integrity
The final project may be done individually or in groups of two students.