CS440: Introduction to Artificial Intelligence

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schedule [2016/01/25 16:10]
anderson 		schedule [2017/08/22 13:19]
anderson [Announcements]
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 ====== Schedule ====== ====== Schedule ======
  
-Follow this link to view all [[https://echo.colostate.edu/ess/portal/section/37e115b6-e68b-4318-89ff-d1ecf025c0b9|lecture videos]].+===== Announcements =====
  
-== January == 
  
-|< 100% 20% 20% 20% 30% 10%  >|+Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https://colostate.instructure.com/courses/55296/external_tools/2755|Echo 360]]. 
 + 
 +/* 
 +are available at this [[https://echo.colostate.edu/ess/portal/section/a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]]. 
 +*/ 
 + 
 + 
 +===== August ===== 
 + 
 +|< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 1:\\  Jan 19 - Jan 22    | Overview. Intro to machine learning. Python.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/01 Course Overview.ipynb|01 Course Overview]],\\  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/02 Matrices and Plotting.ipynb|02 Matrices and Plotting]],  | Text: Sections 1.1-1.5. Section 1 of   [[http://www.scipy-lectures.org|Scipy Lecture Notes]]      |  |  +| Week 1:\\  Aug 21 - Aug 25    | What is AI?  Promises and fears.\\ Python review.\\ Problem-Solving Agents.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/01 Introduction to AI.ipynb|01 Introduction to AI]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/02 Introduction to Python.ipynb|02 Introduction to Python]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/03 Problem-Solving Agents.ipynb|03 Problem-Solving Agents]]   | Chapters 1, 2, 3.1.\\ [[http://science.sciencemag.org/content/357/6346/7.full|AI, People, and Society]], by Eric Horvitz.\\ [[https://aeon.co/essays/can-we-design-machines-to-make-ethical-decisions|Automated Ethics]], by Tom Chatfield.\\ [[http://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0|The Great A.I. Awakening]], by Gideon Lewis-Krause, NYT, Dec 14, 2016.\\ [[https://www.commondreams.org/news/2017/07/19/fundamental-existential-threat-lawmakers-warned-risks-killer-robots|"Fundamental Existential Threat": Lawmakers Warned of the Risks of Killer Robots]], by Julia Conley\\ Section 1 of [[http://www.scipy-lectures.org|Scipy Lecture Notes]]   |  |  
-| Week 2:\\ Jan 25 - Jan 29    | Probability distributions and regression.    | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/03 Linear Regression.ipynb|03 Linear Regression]],\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/04 Gaussian Distributions.ipynb|04 Gaussian Distributions]]   | Sections 4.1-4.2, 4.6-4.9, 5.8-5.9     |  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A1 Linear Regression.ipynb|A1 Linear Regression]] due Thursday, January 28th at 10:00 PM. Download and unzip [[http://www.cs.colostate.edu/~anderson/cs480/notebooks/A1 Grader.zip|A1 Grader.zip]]  |  +| Week 2:\\ Aug 28 - Sept 1    |     |     |   |   
  
-== February == 
  
-|< 100% 20% 20% 20% 30% 10%  >|+===== September ===== 
 + 
 +|< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 3:\\ Feb 1 - Feb 5    | Nonlinear regression with neural networks.    | | 11.1-11.5, 11.7.1, 11.7.4, 11.8.1-11.8.2  | +| Week 3:\\ Sept 4 - Sept 8  |  |  |  | 
-| Week 4:\\ Feb 8 - Feb 12    | Recurrent neural networks.     | | 11.9, 11.12, 11.14   | +| Week 4:\\ Sept 11 - Sept 15   |  |  |  | 
-| Week 5:\\ Feb 15 - Feb 19    | Classification, generative models.   | | 4.3-4.5, 5.5-5.7  | +| Week 5:\\ Sept 18 - Sept 22   |  |  |  | 
-| Week 6:\\ Feb 22 - Feb 26    | Classification, discriminant models.  Ranking.  | | 10.1-10.4, 10.5-10.10    |+| Week 6:\\ Sept 25 - Sept 29   |  |  |  |
  
-== March ==+===== October =====
  
-|< 100% 20% 20% 20% 30% 10%  >|+|< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 7:\\ Feb 29 - Mar 5    | Classification with neural networks.     | | 11.7.2     | +| Week 7:\\ Oct 2 - Oct 6  |  |  |  | 
-| Week 8:\\ Mar 7 - Mar 11    | Convolutional, bottleneck, and deep networks.    | | 11.8.3, 11.11, 11.13     | +| Week 8:\\ Oct 9 - Oct 13  |  |  |  | 
-|  Mar 14 - Mar 18    | Spring Break!    |       | +| Week 9:\\ Oct 16 - Oct 20  |  |  |  | 
-| Week 9:\\ Mar 21 - Mar 25    | Nonparametric methods.  | | 8.1-8.10  | +| Week 10:\\ Oct 23 - Oct 27  |  |  |  |
-| Week 10:\\ Mar 28 - Apr 1    | Dimensionality reduction.  | | 6.1-6.8, 6.10-6.13  |+
  
-== April ==+===== November =====
  
-|< 100% 20% 20% 20% 30% 10%  >|+|< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 11:\\ Apr 4 - Apr 8    | Clustering  | | 7.1-7.10  | +| Week 11:\\ Oct 30 - Nov 3  |   |  |  | 
-| Week 12:\\ Apr 11 - Apr 15    | Support vector machines.   | | 13.1-13.12   | +| Week 12:\\ Nov 6 - Nov 10  |  |  |  | 
-| Week 13:\\ Apr 18 - Apr 22    | Reinforcement learning.   | | 18.1-18.9   | +| Week 13:\\ Nov 13 - Nov 17  |  |  |  | 
-| Week 14:\\ Apr 25 - Apr 29    | Multiple models.    | | 17.1-17.12   |+|  Nov 20 - Nov 24  |  Fall Break  | 
 +| Week 14:\\ Nov 27 - Dec 1  |  |  |  |
  
-== May ==+===== December =====
  
-|< 100% 20% 20% 20% 30% 10%  >|+|< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 15:\\ May 2 - May 6    |      |       |+| Week 15:\\ Dec 4 - Dec 8  |  |  |  | 
 +| Finals Week:\\ Dec 11 - Dec 15  |   |  |  | 
 + 
  
schedule.txt · Last modified: 2024/01/08 18:40 (external edit)

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