最後更新: 7/7/2018 22:41 所有已提交之科目評價已經更新。

CSCI 3230/ESTR 3108 人工智能之基本原理 Fundamentals of AI

Course Code
CSCI 3230/ESTR 3108
科目名稱
人工智能之基本原理
Fundamentals of AI
教員
學  分
3
課程性質
Computer Science  Steam 1必修課程
同科其他選

Workload
l   PAPER類功課
l   FINAL EXAM
l   Lab
*ESTR 3108 比 CSCI3230 多一份AI project, 其他所有野一樣. 呢份AI project 要自學好多野, e.g. tensorflow
好重

1
平均

2
極輕

評價教學內容
#1 midterm, 好容易唔主動去溫書。Lab有準備就唔難,最好識少少prologassignment好似唔會email通知,要定期上website check
#2 AI有趣但範圍太廣, 唔好比題目吸引到。
#3 bore, ppt not deep enough. don't take this course unless your stream required to; U will need a GPU to finish final project [admin案:粗口已過濾]
評價教員教學
#1 落堂可以問佢野,前提係你知自己唔明啲
#2   ppt bad, too many words on the ppt; 最好要自己溫先明講咩
#3   lesson bore [admin案:粗口已過濾]
CUSIS科目資料
Description
Basic concepts and techniques of artificial intelligence. Knowledge representation: predicate logic and inference, semantic networks, scripts and frames, and object-oriented representation. Searching: such as A*, hill-climbing, minimax and alpha-beta pruning. Planning: the frame problem and the STRIPS formalism, representation schemes and planning strategies. Neural networks: learning algorithms, neural architecture and applications. Natural language processing. Knowledge acquisition and expert systems: properties, techniques and tools of expert systems.

Learning Outcome
Students will be able to:
1.Use agents to model AI problems
2.Use search techniques such as A* to search for optimal solutions for AI problems and to play games.
3.Use various logics to represent knowledge and to do reasoning and build expert systems.
4.Use computer learning techniques to acquire real life knowledge in an appropriate representation model (e.g. decision tree and neural networks).
5.Derive learning rules from first principle.
6.Solve real life problems (e.g.classifications and prediction) by such models.
7.Estimate complexity of AI algorithms and prove theorems by contradiction and other techniques.
8.Use computer vison techniques such edge detection to extract features.
其他資料
2017Sem1:學位 130|註冊 128|剩餘2
2017Sem1:學位 32|註冊 32|剩餘0
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