Global Programs
Professor
Kim Jae-Kwang
Learning Period
11-01-2022 ~ 03-05-2031
Course Introduction
In Course 3 of the Machine Learning for Recommender Systems Specialization, offered by Sungkyunkwan Univ., you will: a) understand the data preprocessing of the raw data for recommender systems.b) apply the recommender systems (content based filtering and collaborative filtering).measure the performance of the methods for the recommender systems such as mAP, nDCG, and ED.understand the basic concepts of machine learning.c) understand a typical memory-based method, the K nearest neighbor method. - 김재광 성균관대학교 소프트웨어학과 교수 주 (Week) 학습 내용 (Contents) Week 1 Introduction to Recommender Systems Week 2 Collaborative Filtering Week 3 Recommender System with Deep Learning Week 4 Further Understanding of Recommeder Systems 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
11-01-2022 ~ 03-01-2028
In this course you will: a) understand the naïve Bayesian algorithm.b) understand the Support Vector Machine algorithm.c) understand the Decision Tree algorithm.d) understand the Clustering.Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability. - 김재광 성균관대학교 소프트웨어학과 교수 주 (Week) 학습 내용 (Contents) Week 1 Naïve Bayes Week 2 Support Vector Machine Week 3 Decision Tree Week 4 Clustering 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
11-01-2022 ~ 03-01-2027
In this course, you will: a) understand the basic concepts of machine learning.b) understand a typical memory-based method, the K nearest neighbor method.c) understand linear regression.d) understand model analysis.Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability. - 김재광 성균관대학교 소프트웨어학과 교수 주 (Week) 학습 내용 (Contents) Week 1 The basic concepts of machine learning Week 2 The k-Nearest Neighbors Week 3 Linear Regression Week 4 Logistic Regression 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
14 Course(s)
BYUN DANIEL H
Stories are increasingly told across a variety of formats - books, comics, events, films, games and TV programmes. This is known as transmedia storytelling or multiplatform storytelling. This course will help you tell compelling stories across multiple platforms. We’ll look at examples such as The Avengers, The Matrix and Transformers - and put theory into practice, by retelling the popular fable, The Three Little Pigs, in a multiplatform format. You’ll learn with Daniel H Byun - the film director also known as 변혁. - 변혁 성균관대학교 영상학과 교수 Film Director. Received his PhD degree in Aesthetics from University of Paris 1. Currently an associate professor in the department of Film and Media at Sungkyunkwan University, Seoul. 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
PARK SOJEONG
This course will give you the cultural and historical background to begin your journey into Korean philosophy, and there is no prerequisite knowledge on philosophy required. Anybody who either has an interest in Korean culture, maybe through K-Dramas or K-pop, or an interest in philosophy from a cross-cultural perspective, are all welcome. Despite the growing interest in Korean culture, there are few courses which explore the fascinating topic of Korean philosophy. On this course, you’ll be introduced to concepts in Korean philosophy through an exploration of the Korean language, culture and perspective. The Korean cultural, social, and political environment has informed and transformed the intellectual assets of China and the West. You’ll explore the creative tensions that Koreans have experienced, and broaden your worldview as you discover a new philosophical approach. 박소정 성균관대학교 유학동양한국철학과 교수 I am a professor of Korean philosophy at Sungkyunkwan University in Seoul, Korea. I am interested in teaching Korean philosophy in a comparative perspective, and sharing this knowledge to non-Koreans. 주 (Week) 학습 내용 (Contents) Week 1 What is Korean Philosophy? Week 2 How does Innovation occur Cultural Boundaries? Week 3 What are the Core Debates of Korean Philosophy? Week 4 How do you think through Korean Philosophy? 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
NIELSEN YOUNGJU LEE
In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to use various regression methodologies for investment management that you might need to do in your job every day and make you ready for more advanced topics in machine learning. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics and R programming. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. Students are also expected to know of the instructors' 1st course, 'Fundamental of data-driven investment.' The instructor will explain the detail of R programming. It will be an excellent course for you to improve your programming skills but you must have basic knowledge in R. If you are very good at R programming, it will provide you with an excellent opportunity to practice again with finance and investment examples. 영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수 삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드 주 (Week) 학습 내용 (Contents) Week 1 Understanding the big picture of the algorithm-driven investment decision-making process using machine learning and review of regression methodology Week 2 Regression and beyond 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
In this course, the instructor will discuss the fundamental analysis of investment using R programming. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to do the elemental analysis for investment management that you might need to do in your job every day. Additionally, the study note to do using Python programming will be provided. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. The instructor will explain the detail of R programming for beginners. It will be an excellent course for you to improve your programming skills. If you are very good at R programming, it will provide you an excellent opportunity to practice again with finance and investment examples. Professor Youngju Nielsen creates the course with the assistants of Keonwoo Lim and Jeeun Yuen. =========================================================================================== Coursera Course recommendations before this course for those who are not familiar with basic R programming: https://www.coursera.org/projects/getting-started-with-r https://www.coursera.org/learn/business-analytics-r https://www.coursera.org/specializations/statistics-with-python 영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수 삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드 주 (Week) 학습 내용 (Contents) Week 1 Analyzing Past Returns and Forecasting Future Returns Week 2 Understanding the Risk Using Factors Week 3 Portfolio Analysis and Optimization Week 4 Performance Analysis 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
- Discover how predictive analytics could transform your business As businesses accrue more and more data about their customers – from their behavioural history to their transactions – being able to use ‘Big Data’ is becoming increasingly key to low-term business success. - Learn how predictive analytics helps business Predictive analytics encompasses a variety of statistical techniques in big data analysis and machine learning. Alongside data science experts at Sungkyunkwan University (SKKU), you’ll get foundational training in the concepts and principles that underlie data science and statistical modelling techniques. - See how data science can boost business performance The course will take you through a series of real-world business problems, solving each by using key predictive analytics methods. These include statistical methodologies and algorithms such as artificial neural networks, clustering, text mining, decision trees, and natural language processing. - Explore the relationship between predictive analysis and machine learning You’ll discover the essentials of machine learning, which can be a vital tool in analysing and making use of data. Discover the difference between supervised machine learning – where you can collect data based on previous experience – and unsupervised machine learning – where you can find new data patterns. - Gain practical big data skills Along the way, you’ll learn how to use predictive tools to extract knowledge from data, connect actual business problems with data science solutions, and lead a data science-orientated team. - 영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수 삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
Financial markets have become increasingly complex - it’s not easy to know where to start when it comes to investing. In today’s world the demand of accurate data-driven quantitative analysis across the world is steadily rising: it’s become crucial to understand and be able to use statistical and mathematical information accurately and promptly. This course will teach you the essentials of modern investment theory and help you learn to apply them in real life using financial data and programming. ##Understand modern investment theory On the course you’ll start by learning about key concepts in modern investment theory and quantitative investing like return, risk and portfolio optimisation. ##Get used to statistical techniques and practice using programming language R Once you’ve learnt basic investment concepts we’ll look at applying them using statistics and programming using open source language R will be introduced. You’ll practice by doing assignments every week using actual securities data from Yahoo Finance. ##Discover how to construct an investment portfolio Using your new knowledge of quantitative investing and your ability to analyse investment characteristics using programming, you’ll be able to build your own diversified investment portfolio based on return analysis. ##Learn from an expert in the field Through the course you’ll be taught by an educator who has worked in quantitative finance for more than 15 years in Wall Street global investment banks, before she joined [SKKU](https://www.futurelearn.com/partners/sungkyunkwan-university) in 2015. She was Chief Investment Officer at a hedge fund and head of systematic trading groups at global banks such as Citi and J.P. Morgan. - 영주닐슨 Nielsen, Youngju 성균관대학교 경영전문대학원 교수 삼성자산운용 자문위원 주간조선 칼럼니스트 퀀타비움캐피탈 뉴욕 파트너, 최고 투자책임자 •Citi 뉴욕 G10 시스템트레이딩헤드 •JP 모건 뉴욕 채권시스템트레이딩헤드 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
LEE KEUM-HEE
This course introduces Korean characters,'Hangeul', and provides high-level knowledge related to Hangeul. In this course, the background of 'Hangul' is created, who made the Hangeul, and according to what principle it is systematically explained. It also introduces anecdotes related to Korean tourist destinations related to Hangeul and teaches how to write Hangeul. Learners can increase their understanding of Korea, learn Hangeul accurately, and cultivate high-level knowledge of Hangeul. 이금희 성균관대학교 국어국문학과 교수 I am a professor of Korean Language and Literature at Sungkyunkwan University in Seoul, Korea. I currently teach classes on Korean language to undergraduate students, and on Korean grammar instruction to postgraduate students in Korean language education. The main subjects of my research are syntax and semantics in the Korean language. 주 (Week) 학습 내용 (Contents) Week 1 INTRODUCTION TO HANGEUL Week 2 CREATION AND DISTRIBUTION OF HANGEUL Week 3 PRINCIPLES OF HANGEUL'S CHARACTER CREATION Week 4 READING AND WRITING HANGEUL 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
KIM KYONG HWON
Through this course, you can understand Korean more deeply and get advanced Korean language skills. This course is for advanced Korean learners who are interested in Korean language and culture. The course consists of 5 lessons, each lesson has the main topic of language, job, science, pop culture, and international issues. You can listen to and understand news and dialogues, and learn the expressions used in them in each lesson. Also, on the last day of each week, you can share your opinions with other learners through discussion activities. Take your Korean up a notch with this course! - 김경훤 성균관대학교 학부대학 교수 주 (Week) 학습 내용 (Contents) Week 1 언어 Week 2 직업 Week 3 과학 Week 4 대중문화 Week 5 국제 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
11-01-2022 ~ 07-01-2027
This course is designed for anyone who wants to learn Korean. This course is useful for learners who want to improve their communication skills on personal topics frequently encountered in their daily life after learning basic Korean. Through this class, you can use expressions such as introducing, talking about experiences, and comforting, and you will be able to increase your understanding of basic Korean culture. This course is organized in the order of core expression, conversation, grammar, and self-assessment. The entire course is six weeks long, and consists of two sub-themes within one major topic, so there are a total of 12 lessons. Improve your Korean language skills with this course! - 김경훤 성균관대학교 학부대학 교수 주 (Week) 학습 내용 (Contents) Week 1 인사와 소개(Greeting and Introduction) Week 2 여행(Travel) Week 3 음식(Food) Week 4 성격과 외모(Personality and Appearance) Week 5 배려와 실수(Consideration and Mistake) Week 6 감사와 위로(Appreciation and Consolation) 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)
This course is an introductory course to Korean language that aims to cultivate basic communication skill for those that are interested in learning Korean language. The course is composed of essential expressions that are often used in everyday life, and designed to teach grammars using basic dialogues which reflect colloquial characteristics of Korean language so by end of this course, a student will be able to express him/herself on ordinary topics.Also, the course provides dialogues used in both formal and informal situations to help students to express in Korean language appropriately in particular situations, and provides various material to help students to understand unique culture of Korean language. - 김경훤 성균관대학교 학부대학 교수 주차(No) 강좌명(Topic) 1 저는 대학생이에요. I am a university student. 1) 인사하기 (Greeting) 2) 자기소개하기 (Introducing yourself) 제 가족사진이에요. This is my family picture. 1) 사실 여부 묻고 답하기 (Asking for a fact and answering accordingly) 2) 예/아니요로 답하기 (Answering yes-or-no questions) 3) 가족 소개하기 (Introducing family members) 2 한국어 사전은 있어요. There is a Korean language dictionary. 1) 존재 여부 묻고 답하기 (Asking for and answering the existence of particular object) 2) 물건의 위치 묻고 답하기 (Asking for and answering the location of particular object) 어디에 가요? Where are you going? 1) 어디에 가는지 묻고 답하기 (Asking where a person is going and answering accordingly) 2) 누가 오는지 묻고 답하기 (Asking who is coming and answering accordingly) 3 식당에서 점심을 먹어요. I am having a lunch at a restaurant. 1) 동작 말하기 (Describing what someone is doing) 2) 장소 말하기 (Describing where the action is taking place) 몇 시에 만날까요? What time shall we meet? 1) 약속하기 (Making an appointment) 2) 일상생활(하루 일과) 말하기 (Daily life activities) 3) 시간 표현 익히기 (Various time related expressions) 4 얼마예요? How much is it? 1) 가격 묻고 답하기 (Asking for prices and answering accordingly) 2) 숫자, 단위 명사 익히기 (Numbers and counting units) 3) 물건 사기 (Buying things) 예쁘지만 좀 작아요.예쁘지만 좀 작아요. They are pretty but a bit small. 1) 형용사 익히기 (Adjectives) 2) 물건의 상태 묘사하기 (Describing characteristics of particular subject) 3) 어떤 것에 대해 권유하기 (Making certain suggestions) 5 어떤 음식을 좋아해요? What kind of food do you like? 1) 맛 관련 어휘 익히기 (Various taste related expressions) 2) 부정 표현하기 ‘안’ (Negative expression) 3) 좋아하는 것, 좋아하지 않는 것 말하기 (Expressing what a person likes and dislikes) 많이 맵지 않아요. It isn’t too spicy. 1) 부정 표현하기 ‘-지 않다’ (Negative expression using ‘-지 않다’) 2) 음식 고르기 (의지 표현 ‘–겠-’) (Choosing food) 3) 음식 주문하기 (Ordering food) 6 어제 늦게 자서 좀 피곤해요. I went to bed late so I am a little tired. 1) 과거의 일 설명하기 (Describing past events) 2) 이유 묻고 답하기 (Asking for and answering causes for such events) 경주에 가 봤어요. I have been to Gyeongju. 1) 경험 표현하기 (Describe past experiences) 2) 희망 표현하기 (Describing wishes) 문의: 성균관대학교 교무처 교육개발선터 (Center for Teaching & Learning)
KIM SANGWOO
Joining this course presents opportunity to learn about energy harvesting that refers to a technology that converts the energy discarded in our daily lives into useful electrical energy that we can use. As we all know, most of low-power electronics, such as remote sensors, are driven by batteries. However, even when it comes to long-lasting batteries, they face an issue that is a regular replacement. It can turn out to be costly as there are hundreds of sensors in remote locations. Whereas, energy harvesting technologies supply unlimited operating life of low-power equipment and even remove the need to replace batteries where it is costly, unfeasible, or unsafe. The whole sessions cover the concept of energy harvesting technologies, which has gained popularity over the last few years, and thus will be beneficial for those who seeks for understanding principles and their applications. 김상우 성균관대학교 신소재공학과 교수 주 (Week) 학습 내용 (Contents) Week 1 Energy and Thermodynamics Week 2 Materials property and Energy Harvesting Week 3 Energy Harvesting _ Triboelectric Nanogenerator Week 4 Application of TENG 문의: 성균관대학교 교무처 교육개발센터 (Center for Teaching & Learning)