M2480.001100(001)

Principles and Application of Data Science
(데이터사이언스 원리와 응용)

Fall 2021

Mon/Wed, 12:30 - 13:45

Summary

Combining computing, machine learning algorithms, and inferential thinking based on probability/statistics, data science provides a new paradigm for deriving insights and new knowledge from data and solving real-world problems. The purpose of this course is to introduce core principles and techniques of data science such as basic theoretical knowledge and analytical skills necessary for students of various majors to solve data-driven problems. In addition, students will learn data-centric thinking and decision-making based on data.

Logistics

Instructors

오민환

Min-hwan Oh

이승근

Seunggeun Lee

이재진

Jaejin Lee

김형신

Hyung-Sin Kim

차상균

Sang Kyun Cha

hyunwoo park

Hyunwoo Park

이상학2

Sanghack Lee

이준석

Joonseok Lee

Teaching Assistants

soopark

Sooyoun Park

Head TA

Classroom

  • : Online

Grading

  • : Assignment 35%, Mid-term 30%, Final exam 30%, Attendance 5%

Syllabus

Statistics & Computing

Date
Topic
Instructor
9/1
Wed

Introduction

· Course Logistics
· What is Data Science?
Min-hwan Oh
Sang Kyung Cha
9/6
Mon

Statistics for Data Science

· Probability, Random variables, Expectation & Variance
Seunggeun Lee
9/8
Wed

Statistics for Data Science

· Bias-variance tradeoff, MSE
Seunggeun Lee
9/13
Mon

Computing

· Big O (time & space complexity)
Jaejin Lee
9/15
Wed

Computing

· Searching
Jaejin Lee
9/20
Mon

Computing

· Sorting
Jaejin Lee
추석연휴
9/22
Wed

Computing

· Data structures: Array, Linked list, Queue, Stack
Hyung-Sin Kim
추석연휴
9/27
Mon

Computing

· Data structures: Binary Search Tree
Hyung-Sin Kim
9/29
Wed

Computing

· Data structures: Trees
Hyung-Sin Kim
10/4
Mon

Computing

· Data structures: Graph
Hyung-Sin Kim
대체공휴일

Database & Visualization

Date
Topic
Instructor
10/6
Wed

Database

· Intro to database
Sang Kyun Cha
10/11
Mon

Database

· SQL
Sang Kyun Cha
대체공휴일
10/13
Wed

Database

· Graph database
Sang Kyun Cha
10/18
Mon

Midterm Exam

10/20
Wed

Visualization

· Visualization I
Hyunwoo Park
10/25
Mon

Visualization

· Visualization II
Hyunwoo Park
10/27
Wed

Visualization

· Visualization III
Hyunwoo Park

Machine Learning

Date
Topic
Instructor
11/1
Mon
· Introduction to ML, Linear regression
Sanghack Lee
11/3
Wed
· Logistic Regression
Sanghack Lee
11/8
Mon
· Decision Trees, Random forests
Sanghack Lee
11/10
Wed
· Overfitting, Regularizaion
Sanghack Lee
11/15
Mon
· Nearest Neighbor Classifiers
Joonseok Lee
11/17
Wed
· Gradient descent, Cross validation
Joonseok Lee
11/22
Mon
· Neural networks, Backpropagation
Joonseok Lee
11/24
Wed
· Deep learning, Convolutional neural networks (CNN)
Joonseok Lee
11/29
Mon
· Unsupervised learning: Clustering
Min-hwan Oh
12/1
Wed
· Dimension reduction, PCA
Min-hwan Oh
12/6
Mon
· Online decision making, Multi-armed bandits
Min-hwan Oh
12/8
Wed
· Reinforcement Learning
Min-hwan Oh
12/13
Mon

Final Exam