Please provide feedback on the class!

• TN Voice

Class Apr 22:

• The class will be online https://tennessee.zoom.us/j/2766448345
• Chad will unveal mysteries of hidden Markov Model
• Alex will explain GPUs

Class Apr 15:

• No presentations

Class Apr 8:

• The class will be online https://tennessee.zoom.us/j/2766448345
• Anna will present process mining slides
• Shan will present docker tutorial
• Recording

Class Apr 1:

• The class will be online https://tennessee.zoom.us/j/2766448345
• Dave will talk about memory safety

Class Mar 25:

• The class will be online https://tennessee.zoom.us/j/2766448345
• Nick will give an introduction to the neuromorphic computing, a discussion of the techniques (STDP, Genetic Algorithms, Particle Swarm Optimization, and Temporal Filtering), and finally how he plans on using them towards solving the problems in his research.

Class 6: Feb 26 (no class Feb 19)

• Christoph and Allan will present
• I will bring bagels+coffe

Class 5: Wed Feb 12 (no class Feb 5)

• Rebecca will give a talk
• Anna will bring snacks
• Discussed WoC: sign up at

Class 4: Wed Jan 29

• Presentation by Nick Skuda on Reinforcement Learning basics, recent advances, and lessons learned.

Class 3: Wed Jan 22

• Discuss workplans

Class 2: Wed Jan 15

• Pecording https://drive.google.com/drive/folders/1RJObnYwcpMAjZ5_46LJgBXscg9nxyuJx?usp=sharing
• Please add an .md file to https://github.com/AdvSwEng/workplan descrbing your interests

Class 1: Monday Jan 13

• Please create github ID and and send it to me so that I can add you to the class
• Please let me know which days would work best for you: I hope to have class only once a week, for example on Wed if you can stay for two hours on that day

No class on Jan and 10!

Syllabus and News for CS594/690: Advanced Software Engineering

• Course: [COSCS-594/690]
• ** MK623 W 10:10AM-12:05PM (Min Kao 623) **
• Instructor: Audris Mockus, [email protected] office hours MK613 - on request

The primary purpose of the course is to learn-by-doing advanced operational data techniques including:

1. Text analysis, e.g., Word2Vec, GloVe, NMF, LDA, LSTM
2. Image analysis, e.g., RCNN, Mask-RCNN, CAM, ...
3. Network analysis, network databases (neo4j),
4. Advanced data analysis, Graphical models

Each of the techniques will be learned through work on a real project.

Draft Syllabus