Course Plan and Lecture Slides Notes

Course Plan

Introduction (1/22 Slides)
Unix and Python (1/24 Slides) (1/28 Slides)(1/24 Notebook)
Linear Algebra (1/29 Slides)(1/29 Notebook)
Numpy (1/31 Notebook)
Probability Theory (2/7 Notes) (2/12 Notes)(2/14 Notes) (2/7, 2/12, 2/14 Slides)
History of Particles (2/19)
Why HEP? (2/21 Slides) (2/26 Slides)
Feb 28- Particle Interactions. Lab 3 (LArTPC Handscan) Intro. (2/28 Notes, 2/28 Slides)
March 5- Canceled due to power failure.
March 7- Lab Day (focus on Lab 3)
March 19- Particle Detection (Lab 2 Due) (3/19 Notes, 3/19 Slides, 3/19 Slides 2)
March 21- Test Statistics / Performance metrics (3/21 Notes, 3/21 Slides, 3/21 Slides 2)
March 26- HEP Data Analysis / Lab 4 Intro (3/26 Slides) (3/26 Notes) (3/26 Slides 2)
March 28- Machine Learning Techniques (3/28 Notes) (3/28 Slides)
April 2- Deep Learning (4/2 Slides)
April 4 - Deep Learning Tour + Projects (4/3 Slides)
April 9 - Practicing Deep Learning (Keras) (4/9 Slides)
April 11- Recurrent, Generative, and Adversarial NNs. (4/11 Slides)
April 16-
April 18-
April 23- Project I Due
April 25- Exam Due
April 30-
May 2-
May 4- All Labs (Including 5 Due)
May 7- Final: Project II Presentations