| Grade |
Semester |
Course Name |
Module Name |
Category |
Credit |
Course Overview |
| 2 |
1 |
Healthcare Bigdata Theory |
Core Data Science |
Major Elective |
3 |
This course fosters basic knowledge for getting prepared for future healthcare led by data science by learning concepts of healthcare bigdata, which is the key resource in 4th industry in healthcare, clinical data, claim data, dielectric data, and their characteristic, utilization status, and value. |
| 2 |
1 |
Mathematics for AI |
AI Convergence |
Major Elective |
3 |
This course covers linear algebra, differentiation, and probability essential for artificial intelligence. The students will learn mathematicalexpressions, and parts that were not covered in high school mathematics will be explained easily with examples. |
| 2 |
1 |
Basic Python Programming |
Core Data Science |
Major Elective |
3 |
In this course, students will learn basics and utilization method of a programming language called Python. It is one of the languages used by programmers, and it is getting more popular. This course introduces basic grammars, such as variables, calculation, loop statement, and function. The students will also learn how to use “Library” used in various application fields, such as probability/statistics-based data analysis. |
| 2 |
1 |
Understanding of Epidemiology and Disease |
Medical Information |
Major Elective |
3 |
This course fosters medical and health knowledge and professional communication skills by learning theoretical principles of epidemiology, which identifies distribution and risk factors of disease, and learning characteristics of main diseases. |
| 2 |
1 |
Basic Data Analysis |
Data Analysis |
Major Elective |
3 |
In this course, students will learn various statistical analysis techniques for data analysis. The students will also learn basic statistical concepts and learn how to analyze data by using statistical techniques. The students will also foster ability to use analysis techniques in R language. |
| 2 |
2 |
Basic Health Data Analysis |
Medical Information |
Major Elective |
3 |
The students will understand concepts and principles used in healthcare data analysis and learn essential statistical analysis methods used in medical field. The course fosters ability to use the adequate analysis method depending on structure and characteristic of medical data, and students will be able to use SPSS program for analysis. |
| 2 |
2 |
Basic R Programming |
Data Analysis |
Major Elective |
3 |
The students will learn programming language R for data management, statistical analysis, visualization, machine learning, and deep learning-based prediction model development to build up ability to find insights from data. |
| 2 |
2 |
Basic AI |
Core Data Science |
Major Elective |
3 |
This course uses EBS textbook to cover mathematics and Python. It also covers AI application and deep learning-based calculation graph additionally. There will be 1-week lecture on Python grammar. |
| 2 |
2 |
Data Mining |
Core Data Science |
Major Elective |
3 |
The students will learn basic concepts and methodologies of data mining that explores useful knowledge from massive amount of data. The students will also foster practical ability to use R and data mining methods. |
| 3 |
1 |
Database and SQL |
Data Analysis |
Major Elective |
3 |
This course covers Database, a program developedto store and manage data. In this course, students will learn main content related to operational principle and optimization of Database. This course also includes practice of SQL (Structured Query Langauge) for using Database. |
| 3 |
1 |
Advanced Python Programming |
Data Analysis |
Major Elective |
3 |
In this course, students will use various libraries to learn the whole process from data preprocessing to data modeling and data visualization. In data analysis, students will use conventional statistical analysis, machine learning (feature engineering), and other various methods for exploratory data analysis. |
| 3 |
1 |
Pathophysiology and Principle of Drug Treatment |
Medical Information |
Major Elective |
3 |
In this course, students will learn causes, mechanism, and progress of main chronic and acute diseases and learn basic principles of drug treatment by focusing on frequently used drugs. The students will enhance their understanding on medical clinical data, utilization ability, and professional communication skills based on basic knowledge of diseases and drug treatment. |
| 3 |
1 |
Machine Learning Theory and Practice |
AI Convergence |
Major Elective |
3 |
This course uses a famous textbook titled “Study Machine Learning Alone”, and it consists of author’s coding experience and engineering college-level descriptions. This course helps deeper understanding of machine learning. |
| 3 |
1 |
Data Visualization |
Data Analysis |
Major Elective |
3 |
In this course, students will learn visualization for efficient data refinement and visualization techniques for expressing objective information within data. The students will learn ability to use R language to express image, diagram, or animation for delivering data analysis results and information. |
| 3 |
1 |
TensorFlow Practice |
AI Convergence |
Major Elective |
3 |
In this course, students will learn concepts of neural network related to visual and linguistic intelligence. This course also covers TensorFlow grammar and mechanism. This course also enhances understanding of advanced courses on neural network. |
| 3 |
2 |
Understanding of Medical Informatics |
Medical Information |
Major Elective |
3 |
Medical Informatics is a convergence study that covers all data generated in medical fields, such as medical record, image medicine data, and prescription data. In this course, students will learn structure, type, and purpose of healthcare data, healthcare terms and classification system, standard, clinical decision-making system, medical informatics knowledge, recent technical progress, and future values of medical information. |
| 3 |
2 |
Advanced Biomedicine and Future Medicine |
Pharmaceutical and Biodata |
Major Elective |
3 |
In this course, students will learn basic drug treatment, concept and development principle of biomedicine, current status, industry, and related systems. The students will also explore future medicine led by development and convergence of biomedicine and biomedical science. |
| 3 |
2 |
Cloud Computing |
AI Convergence |
Major Elective |
3 |
This course covers Tensorflow.js which runs artificial intelligence on webs. This course includes two weeks of lectures on basic grammar of Java Script. It also covers Cloud web technologies, including AWS and Node.js. |
| 3 |
2 |
Text Mining |
Data Analysis |
Major Elective |
3 |
This course covers a technique for extracting information from data which has form and structure different from numeric data with certain standard and form. The students will also learn techniques for standardizing and extracting characteristics of unstructured data as well as techniques for processing data based on natural language processing. |
| 3 |
2 |
Natural Language Processing |
AI Convergence |
Major Elective |
3 |
This course uses a textbook by Gihyun Kim who is a famous author for natural language processing. This course covers from basic natural language processing to the latest technologies. |
| 3 |
2 |
Business Intelligence |
Data Analysis |
Major Elective |
3 |
In this course, students will learn process and method of collecting, storing, analyzing, and utilizing bigdata. The students will also practice data mining, data visualization, data tools, infrastructure, and examples of supporting decision-making through data analysis. |
| 4 |
1 |
New AI Drug Development |
Pharmaceutical and Biodata |
Major Elective |
3 |
The new drug development field is actively using artificial intelligence in discovering substances. There are also new protein structure estimation methods, such as AlphaFold. This course covers application of these items and brief explanation of artificial intelligence technologies. |
| 4 |
1 |
Medical Data Ethics and Security |
Medical Information |
Major Elective |
3 |
The development of medical information technology resulted in distribution and joint use of digitized health information for medical purpose and other various purposes. This further emphasized ethics and security in medical data. This course covers advanced technologies, systems, strategies, etc., for fostering medical data industry and related research in compliance with information protection and ethics. The students will also learn information ethics, systems, regulations, etc., to be observed in generation, collection, processing, and utilization of medical data. |
| 4 |
1 |
Capstone Project I |
Core Data Science |
Major Elective |
3 |
This course is a project course that covers all knowledge learned from basic and major courses. In this course, students will design a long-term project for system, software, application, etc., used in healthcare and bioindustry fields. |
| 4 |
2 |
Understanding and Utilization of Blockchain |
Business Intelligence |
Major Elective |
3 |
In this course, students will learn concepts, limitations, application, and future prospect of blockchain technologies, mechanism of cryptocurrency, proof-of-work algorithm, smart contract, NFT, metaverse, blockchain and information protection, and blockchain and healthcare. |
| 4 |
2 |
Understanding of Medical Image Data |
Medical Information |
Major Elective |
3 |
The image diagnosis is successfully commercialized in precision medicine field. This course covers deep learning techniques applied to medical image technologies, such as diagnosis, division, matching, etc., in medical image. |
| 4 |
2 |
Capstone Project Ⅱ |
Core Data Science |
Major Elective |
3 |
The students will work on the personal or team project designed in Capstone Project I, release it on Android/iOS market, construct prototype, and achieve other performances under the set schedule. |
