2019 Advanced Artificial Intelligence and Data Science D

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Academic unit or major
School of Computing
Instructor(s)
Miyake Yoshihiro  Shudo Kazuyuki  Kise Kenji  Nitta Katsumi  Tsurumi Toshiyuki  Sato Akiko  Kawamoto Fumio  Nakagawa Kei  Takigawa Takayuki 
Course component(s)
Lecture
Day/Period(Room No.)
Fri9-10(W531(レクチャーシアター),G115)  
Group
-
Course number
XCO.T486
Credits
1
Academic year
2019
Offered quarter
4Q
Syllabus updated
2019/12/2
Lecture notes updated
2020/2/3
Language used
Japanese
Access Index

Course description and aims

This course is designed for students to understand the outline of artificial intelligence development in business and artificial intelligence and data science in the financial industry to consider the possibility to utilize artificial intelligence and data science in the field.
The lecturers will explain broad pictures and recent trends of the topic in each class, as shown below.

Student learning outcomes

This course aims to develop ability of each student to be more successful in the real world with the consideration of artificial intelligence and data science, and also through the opportunity for students to describe their own ideas.

Keywords

artificial intelligence, data science, AI business, user experience, FinTech, financial industry, stock price forecasting

Competencies that will be developed

Intercultural skills Communication skills Specialist skills Critical thinking skills Practical and/or problem-solving skills

Class flow

This course requires students to take an active role in their own learning. It is required to attend each class.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction, AI development in business To understand the background and purpose of this course, and the basic concepts of AI business.
Class 2 AI development from planning through case studies To understand the viewpoints necessary for AI development through a series of examples from planning to user use.
Class 3 User experience for AI development (1) To diversify AI business ideas from the user's point of view and understand the perspectives necessary for AI development.
Class 4 User experience for AI development (2) To converge the diversified ideas and understand the perspectives required for AI development.
Class 5 Introduction to AI and data science in the financial industry To understand the background, purpose, and basic concepts of asset management.
Class 6 AI technology in the financial industry To understand development examples for stock price forecasting.
Class 7 Data science technology in the financial industry To understand development examples of combination optimization of investment targets.
Class 8 AI and data science utilization platform in the financial industry To understand advanced technologies related to data utilization infrastructure.

Textbook(s)

None required

Reference books, course materials, etc.

Materials will be provided on OCW-i in advance and projected in the class room

Assessment criteria and methods

Based on quizzes evaluating students' understanding at the end of each class.

Related courses

  • XCO.T487 : Fundamentals of data science
  • XCO.T488 : Exercises in fundamentals of data science
  • XCO.T489 : Fundamentals of artificial intelligence
  • XCO.T490 : Exercises in fundamentals of artificial intelligence
  • XCO.T483 : Advanced Artificial Intelligence and Data Science A
  • XCO.T485 : Advanced Artificial Intelligence and Data Science C

Prerequisites (i.e., required knowledge, skills, courses, etc.)

none

Other

This lecture is supported by Nefrock Inc., and Nomura Holdings, Inc.

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