Tentative Schedule


Week

Class Topic Due Where
0 0. Computer Career and Data Research & Technologies    
  0.1 A computer career    
  0.2 Data research    
  0.3 Data technologies    
1 01/09
01/11		 1. Introduction to CSCI 515    
  1.1 Course introduction  
  1.2 Data life cycle    
  1.3 Topics covered    
2 01/16
01/18		 2. Programming Exercise I    
  2.1 Specifications    
  2.2 Web page download    
  2.3 Code sample    
01/18  Last day to add a course or drop without record
 Last day to add audit or change to/from audit
 Last day to receive a refund on a dropped class
 Drops after the last day to add will appear on a transcript. 		   
3 01/23
01/25		 3. Essential Technologies for Exercise Construction    
  3.1 Essential software and tools    
  3.2 Using Linux    
  3.3 Writing HTML scripts    
4 01/30
02/01		 4. PHP (HyperText Preprocessor)    
  4.1 LAMP    
  4.2 PHP    
  4.3 MySQL    
5 02/06
02/08		 5. Web Search Services    
  5.1 The World Wide Web    
  5.2 Web page information    
  5.3 Web search methods    
6 02/13
02/15		 6. Information Retrieval (IR)    
  6.1 Various IR methods    
  6.2 Automatic indexing methods    
  6.3 Data classification and clustering EX I  
7 02/22 7. The PageRank Algorithm    
  7.1 Background    
  7.2 The PageRank algorithm    
  7.3 Computing PageRank scores    
02/20
Exam I (for both on-campus and on-line students; 6:30pm – 8:30pm, Tuesday)
   
8 02/27
02/29		 8. Firebase Database    
  8.1 Programming Exercise II    
  8.2 Introduction to Firebase    
  8.3 Using Firebase    
9
03/04
–
03/08
  Spring Break — no classes
   
10 03/12
03/14		 10. TensorFlow    
  10.1 TFJS operations    
  10.2 TFJS models    
  10.3 TFJS visor    
11 03/19
03/21		 11. A TensorFlow.js Example    
  11.1 Example introduction    
  11.2 Example model    
  11.3 Example training    
12 03/26
03/28		 12. JavaScript    
  12.1 JavaScript syntax    
  12.2 JavaScript instructions    
  12.3 JavaScript examples    
13 04/02
04/04		 13. Decision Trees    
  13.1 Background    
  13.2 Measuring impurity    
  13.3 Information gain    
04/05  Last day to change to or from S/U grading
 Last day to change to or from audit grading
 Last day to drop a full-term course or withdraw from school 		   
14 04/11 14. K-Nearest Neighbor (kNN) Algorithm    
  14.1 Background    
  14.2 kNN for prediction and smoothing    
  14.3 Strengths and weaknesses    
04/09
Exam II (for both on-campus and on-line students; 6:30pm – 8:30pm, Tuesday)
   
15 04/16
04/18		 15. Artificial Neural Networks (ANNs)    
  15.1 Artificial intelligence    
  15.2 Backpropagation    
  15.3 Genann: a minimal ANN    
16 04/23
04/25		 16. Data Processing and Management    
  16.1 Data science    
  16.2 Data warehouse    
  16.3 Data fusion    
17 04/30
05/02		 17. Data Mining Concepts    
  17.1 Introduction to data mining    
  17.2 Data mining steps    
  17.3 Data mining techniques    
18 05/07
Final exam (for both on-campus and on-line students; 06:30pm – 08:30pm, Tuesday)
   
19 05/14 Grades posted before noon, Tuesday    





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