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KAIST 산업및시스템공학과 문일철 교수
KAIST 산업및시스템공학과 문일철 교수 KOOC (KAIST Open Online Course)
  • Type MOOC course
  • Period Always open
  • hr Study freely
  • Course approval method Automatic approval
  • Certificate Issue Online

Instructor Introduction

  • KAIST 산업및시스템공학과 문일철 교수

    KAIST 산업 및 시스템 공학과 교수(2011.9~ )

Lecture plan

★강의 수강
  1. Chapter 0: 강좌 시작 전 꼭 확인해 주세요!
    1. 수료기준, 게시판 등 강좌 학습 방법 소개
  2. Chapter 1 Priority Queue and Heap
    1. Priority Queue
    1. Implementation & performance of Priority Queue
    1. Balanced Tree
    1. Binary Heap for Priority Queue
    1. Reference Structure of Binary Heap
    1. Insert Operation of Binary Heap
    1. Delete Operation of Binary Heap
    1. Complexity of Priority Queue and Heap Sort
    1. Quiz 1
  3. Chapter 2 Application 2 : Genetic Algorithm
    1. Difficult Problem
    1. Genetic Algorithm
    1. Traveling Salesman Problem
    1. Terminology and Structure of Genetic Algorithm
    1. Encoding
    1. Selection
    1. Crossover
    1. Mutation
    1. Substitution and Execution
    1. Quiz 2
  4. Chapter 3 Sorting
    1. O(N^2) Sorting
    1. Merge Sort
    1. Heap Sort
    1. Quick Sort
    1. Counting Sort
    1. Radix Sort
    1. Quiz 3
  5. Chapter 4 Hashing
    1. Limit of Divide and Conquer
    1. Hash Table
    1. Hash Function
    1. Examples of Hash Function
    1. Collision Resolution of Hashing
    1. Deletion in Hash Table
    1. Managing the Size of Hash Table
    1. Quiz 4
  6. Chapter 5 Graph and Dijkstra's algorithm
    1. Graph
    1. Representation of Graph
    1. Traversing Problem - DFS and BFS
    1. Shortest Path Problem - Dijkstra's Algorithm (1)
    1. Shortest Path Problem - Dijkstra's Algorithm (2)
    1. Minimum Spanning Tree Problem - Prim's Algorithm
    1. Quiz 5
  7. Chapter 6 Application 3 : Network Analysis
    1. Social Network
    1. Centrality
    1. K-Clique and Newman Clustering
    1. Visualization of Network Structure
    1. Quiz 6
  8. ★강의 수강 후 의견을 부탁드리겠습니다.★
    1. 강의에 대한 별점을 매겨주세요. 여러분의 의견이 많은 도움이 됩니다.
코드 실습
  1. 데이터 구조 및 분석 : Non-Linear Structure and Dynamic Programming - Setup
    1. Anaconda & Pycharm Setup
  2. CHAPTER 1 실습코드
    1. Decision Tree - Random forest implementation
    1. 오프라인 실습 수업 영상_Lecture 1: Priority Queue and Heap
  3. Chapter 2 실습코드
    1. Traveling salesman problem - Completing the testbed of TSP
    1. 오프라인 실습 수업영상_Lecture 2: Genetic Algorithm
  4. Chapter 3 실습코드
    1. Text Analysis - List based TF-IDF calculation and sorting
    1. 오프라인 실습 수업영상_Lecture 3: Sorting
  5. Chapter 4 실습코드
    1. Text Analysis - Hash based TF-IDF calculation and sorting
    1. 오프라인 실습 수업영상_Lecture 4: Hashing
  6. Chapter 5 실습코드
    1. Social Network Analysis - Local metric calculation on Seoul Metro Stations
    1. 오프라인 실습 수업영상_Lecture 5: Graph
  7. Chapter 6 실습코드
    1. Social Network Analysis - Global metric calculation on Seoul Metro Stations
    1. 오프라인 실습 수업영상_Lecture 6: Social Network Analysis

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:)