Linda Lankewicz, University of the South. Exchanges Group Presentation Draft. Introduction to Computer Science. Instructional Technology: Digital Literacy and Learning. Business Data Communications and Computer Networks. Computer Networks and Architecture. Pattern Recognition and Machine Learning.
http://lankewicz.sewanee.edu/
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CS Courses | lankewicz.sewanee.edu Reviews
https://lankewicz.sewanee.edu
Linda Lankewicz, University of the South. Exchanges Group Presentation Draft. Introduction to Computer Science. Instructional Technology: Digital Literacy and Learning. Business Data Communications and Computer Networks. Computer Networks and Architecture. Pattern Recognition and Machine Learning.
lankewicz.sewanee.edu
Data Mining
http://lankewicz.sewanee.edu/lankewicz/cs290/syllabus.htm
CS 290 Data Mining. Instructor: Linda Bright Lankewicz. Class Schedule: Monday, Wednesday 2:30-3:45. Final Exam: Wednesday, May 8, 2013 9:00 am. Textbook: Data Mining with R, Luis Torgo. Office Hours: Monday Wednesday Friday 9:00-11:00 am. Objectives of the course:. Understanding of the theory and implementation of data mining approaches such as multiple linear regression, regression decision trees, neural networks, Bayesian classification, clustering, k-nearest neighbor approaches. Grade for the course.
Operating System Topics
http://lankewicz.sewanee.edu/lankewicz/cs428/topics.html
Advent 2000 - CS428 - Operating Systems - Lankewicz. Refers to Practical Linux Programming. Refers to Introduction to Operating Systems. OS 1-2.4.6. Introduction to operating systems. PUP A, OS 18.1-18.3. OS 3; PUP 2.1-2.4. Process states, transitions, context switches. PUP 25-2.6, 2.10; OS 18.4. Process control, Linux forks. OS 1865; PUP 2.7- 2.8, 2.11. Execution of code by spawned processes. Programming with spawned processes. PUP 31-3.3; OS 18.5-18.6. Quiz #1: PUP 1,2. Files and database systems.
CS411 Topics
http://lankewicz.sewanee.edu/lankewicz/cs411/topics.htm
Be prepared to discuss an RFC. Check out online textbook resources. Network delays, bandwidth, protocol layers. The Web and HTTP. Read chapter 2, latency article. Internet email, DNS. Chapter 2 Ethereal labs. Sun's The Java Tutorial. UDP ping client server. UDP (User Datagram Protocol). Chapter 3 Ethereal lab. TCP (Transmission Control Protocol),. Datagram network routers, IP. Routing in the internet. Chapter 4 Ethereal lab. Hubs, bridges, switches. Chapter 5 Ethereal lab. Wireless and mobile networks.
CS320
http://lankewicz.sewanee.edu/lankewicz/cs320/topics.html
CS320 Analysis of Algorithms. LLankewicz, Spring 2001. Analysis of sequential algorithms. Parallel sorting: interconnection networks. Examination 1, chapters 1-6. Graphs: BFS, DFS. Graphs: toplogical sort, shortest path. Greedy methods: knapsack, Huffman codes. Greedy methods: MST, Kruskal, Prim. Divide and conquer: kth smallest. Divide and conquer: matrix multiplication. Examination 2, chapters 8, 12, 13. Dynamic programming: optimal binary search trees. Dynamic programming: all pairs shortest path, tsp.
Machine Learning Topics
http://lankewicz.sewanee.edu/lankewicz/cs430/topics.html
Advent 2007 - CS430 Machine Learning - Lankewicz. Introduction to Machine Learning. Research Methodology: Data Representation, Sampling. Research Methodology: Evaluating Hypotheses. Research Methodology: Comparing Algorithms. Nonparametric Methods: Instance-based Learning. Nonparametric Methods: Instance-based Learning. Overview, Course Evaluation.
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CS Courses
Linda Lankewicz, University of the South. Exchanges Group Presentation Draft. Introduction to Computer Science. Instructional Technology: Digital Literacy and Learning. Business Data Communications and Computer Networks. Computer Networks and Architecture. Pattern Recognition and Machine Learning.
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