Course title: 
<br>   Python programming implementation for important algorithms
<br>   (or, Programming Top Ten Important Algorithms in Python)
<br>
<br>Intended Students: 
<br>   CS students in their 2nd, 3rd, or 4th year
<br>
<br>Objectives: 
<br>   To teach students theory, algorithms, programming, and applications
<br>   of Top ten important algorithms by in-class hands-on programming in PYTHON.
<br>
<br>Prerequisite: 
<br>   Introduction to programming; 
<br>   Bringing own NB to class
<br>
<br>Reference: 
<br>   Selected papers; Python Docs
<br>
<br>Grading: 
<br>   Student report after each topic's hands-on programming
<br>
<br>Contents:
<br> 
<br>1. Sorting (Selection Sort, Bubble Sort, Merge Sort, Quick Sort, Heap Sort,
<br>   Radix Sort)
<br>2. Simplex Method for Linear Programming (Optimization)
<br>3. Graph search, Shortest Path, Minimum Spanning Tree, Max Network Flow,
<br>   Matching, Min-Cut
<br>4. Fast Multipole Method (FMM) for N-body Simulation Problem
<br>5. Dynamic Programming (Viterbi decoding for error correction, 
<br>   Two-Dimensional DP)
<br>6. Page-rank Algorithm (Web search)
<br>7. Discrete Fourier Transform (DFT) and
<br>   Fast Fourier Transform (FFT) for Signal Processing
<br>8. Compression (Lossless and Lossy Algorithms for Data, Image, Video)
<br>9. TBD 
<br>10. TBD 
<br>
<br>** The order is tentative