shujian.github.io/aipcourse.html at main · shujian/shujian.github.io · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<link rel="stylesheet" href="styles.css">
</head>
<title>
HomePage of Programming for Artificial Intelligence
</title>
<h1 id="programming-for-artificial-intelligence">Programming for
Artificial Intelligence</h1>
<hr />
<h2 id="course-description">Course Description</h2>
<p>The course is designed for freshmen in AI as a second programming
course. The course include two main threads. One is to learn and
practice programming in different styles, including the procedure
abstraction, functional programming, data abstraction with
object-oriented programming, etc. The other is to learn and practice
basic tasks in artificial intelligence, such as search, planing,
reasoning, regression, classification, clustering, dimension reduction,
association rule mining, etc.</p>
<p>The course is taught every Spring semaster in School of Artificial
Intelligence, Nanjing University, since 2019. It is jointly built by
Shujian Huang, Li Zhang and Zhen Wu.</p>
<hr />
<h2 id="objectives">Objectives</h2>
<ul>
<li>Develop proficiency in programming methods and techniques using
Python and other programming languages.</li>
<li>Gain a solid grasp of fundamental methods for data representation,
analysis, and computation.</li>
<li>Build foundational skills in artificial intelligence techniques to
solve essential problems.</li>
<li>Acquire an understanding of real-world applications in areas such as
text and image processing, making initial attempts at problem-solving
within these domains.</li>
<li>Establish a strong foundation in mathematics and programming to
support advanced research in artificial intelligence.</li>
</ul>
<hr />
<h2 id="outline">Outline</h2>
<h3 id="fundamentals-of-python-programming">1. Fundamentals of Python
Programming</h3>
<ol type="1">
<li>Introduction to programming for artificial intelligence;</li>
<li>Python basics: syntax, data types and operations;</li>
<li>Fundamental data structures such as sequences: strings, lists,
tuples, and range objects, dictionaries, sets, as well as stacks,
queues, and linked lists;</li>
<li>Control structures;</li>
<li>Packages, modules, functions, and variable scope;</li>
<li>Object-oriented programming;</li>
<li>Exception handling.</li>
</ol>
<h3 id="basics-of-scientific-computing-and-data-analysis-with-scipy">2.
Basics of Scientific Computing and Data Analysis with SciPy</h3>
<ol type="1">
<li>Data representation with Numpy;</li>
<li>Scientific computing, data processing, and analysis with
SciPy/SemPy;</li>
<li>Data statistics and visualization with Pandas.</li>
</ol>
<h3 id="fundamental-methods-in-artificial-intelligence">3. Fundamental
Methods in Artificial Intelligence</h3>
<ol type="1">
<li>Numerical computation and optimization methods;</li>
<li>Supervised learning: regression analysis and classification;</li>
<li>Unsupervised learning: clustering and dimensionality reduction;</li>
<li>Data mining: dimension reduction, association rule mining and
anomaly detection.</li>
</ol>
<h3 id="applications-of-artificial-intelligence">4. Applications of
Artificial Intelligence</h3>
<ol type="1">
<li>Text processing methods and examples;</li>
<li>Image processing methods and examples.</li>
</ol>
<hr />
<h2 id="instructor-contact-information">Instructor Contact
Information</h2>
<ul>
<li>Shujian Huang (<a href="index.html">homepage</a>)</li>
<li>Email: huangsj at nju dot edu dot cn</li>
<li></li>
<li>Zhen Wu(<a href="https://wuzhen247.github.io/">homepage</a>)</li>
<li>Email: wuz at nju dot edu dot cn</li>
</ul>