
Instructor Introduction
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KAIST 산업및시스템공학과 문일철
KAIST 산업및시스템공학과 부교수
KAIST 김재철AI대학원 겸임교수
KAIST 항공우주공학과 겸임교수
KAIST 안보융합연구원 겸임교수
한국인공지능학회 교육이사
Lecture plan
★강의 수강
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Chapter 0: 강좌 시작 전 꼭 확인해 주세요!
- 수료기준, 게시판 등 강좌 학습 방법 소개
- Orientation (Offline Orientation Video + Material)
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Chapter 1 Python Overview
- Programming and Execution Environment
- Hello World in Python
- Naming, Styling and Comments
- Variable Statements and Operators
- String
- List, Tuple, Dictionary
- Condition and Loop Satement
- Function Statement
- Assignment and Equivalence
- Class and Instance
- Module and Import
- Quiz 1
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Chapter 2 Object-oriented paradigm and software design
- Design and Programming
- UML notation 1
- Encapsulation and Inheritance
- Polymorphism and Abstract Class
- UML notation 2
- Structure and Relationship
- Quiz 2
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Chapter 3 Linked list, stack and queue
- Abstract Data Types
- Array
- Linked List 1
- Linked List 2
- Stack
- Queue
- Quiz 3
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Chapter 4 Recursion and dynamic programming
- Recursions
- Merge Sort and Problems in Recursions
- Dynamic Programming 1 (Memoization)
- Fibonacci Sequence in DP
- Process of Assembly Line Scheduling
- Assembly Line Scheduling in Recursion and DP
- Quiz 4
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Chapter 5 Application 1 : Simulation
- Comprehend a problem
- Introduction of modeling
- Examples of simulation
- Quiz 5
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Chapter 6 Binary Search Tree
- Tree as an Abstract Data Type and Structure
- Terminologies of Tree Structure
- Characteristics of Tree
- Binary Search Tree and Implementation
- Insert and Search Operation of Binary Search Tree
- Delete Operation and Minimum & Maximum of Binary Search Tree
- Tree Traversing
- Quiz 6
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Chapter 7 Algorithm Analysis
- Factors of Program's Efficiency
- Bubble Sort Algorithm
- Importance of Efficiency
- Definition of Algorithm Analysis and Examples
- Big-Oh Notation
- Growth Rate
- Examples & Rules of Big-Oh Notation
- Quiz 7
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★강의 수강 후 의견을 부탁드리겠습니다.★
- 교수님 강의에 대한 별점을 매겨주세요. 여러분의 의견이 많은 도움이 됩니다:D
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데이터 구조 및 분석 : Linear Structure and Dynamic Programming - Setup
- Anaconda & Pycharm Setup
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Chapter 1 실습코드
- Naive Bayes classifier - Conditional probability calculation
- 오프라인 실습 수업 영상_Lecture 1 : Simple Sentiment Analysis
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Chapter 2 실습코드
- Naive Bayes classifier - Classifier with prior and likelihood
- 오프라인 실습 수업 영상_Lecture 2 : Implementing Class with Diagram
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Chapter 3 실습코드
- Production line model - Stack and queue implementation
- 오프라인 실습 수업 영상_Lecture 3 : Linked List, Stack and Queue
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Chapter 4 실습코드
- Production line model - Scheduling with dynamic programming
- 오프라인 실습 수업 영상_Lecture 4 : Linked List, Stack and Queue (Continued)
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Chapter 5 실습코드
- Production line model - Probabilistic interrupt modeling
- 오프라인 실습 수업 영상_Lecture 5 : Dynamic Programming
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Chapter 6 실습코드
- Decision Tree - Decision tree node implementation
- 오프라인 실습 수업 영상_Lecture 6 : Tree
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Chapter 7 실습코드
- Decision Tree - Decision tree implementation
- 오프라인 실습 수업 영상_Lecture 7: Binary Tree
Additional Info
본 강좌는 Python3 를 기반으로 진행되는 강좌 입니다.
기초적인 내용부터 시작하기 때문에, 누구나 수강할 수 있는 강좌입니다.
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* 강좌 수료 기준 충족 시 수료증을 제공합니다:)