Progressive Graduate Minor in Data Science and Artificial Intelligence, Tokyo Institute of Technology

(Japanese site) 東京工業大学 データサイエンス・AI特別専門学修プログラム

News

  • (updated on September 30, 2021) XCO.T487, XCO.T488, XCO.T489, and XCO.T490 are for master/undergraduate students, and XCO.T677, XCO.T678, XCO.T679 and XCO.T680 are for doctoral students.
  • (updated on September 23, 2021) Please see (this site) for the details of "Tokyo Tech Advanced Human Resource Development Fellowship for Doctoral Students".
  • (updated on September 24, 2021) If you want to apply for this progressive graduate minor, please read "Request for approval: Registration for Progressive Graduate Minor" in page 6 of Course registration, and finish the application to Student Division. Actual procedures are as follows.
    (1) receive an email of informal consent from your supervisor, and fill in this form for another email from the course coordinator
    (2) register "Form 15" from application of forms" in Tokyo Tech Web System for Students and Faculty
    (3) after the registration, send the form and two emails of informal permission to Student Division of Tokyo Tech (kyo.dai@jim.titech.ac.jp) by email
    The above two emails (from your supervisor and from the course coordinator) are the substitute of seals. You don't need to submit paper with seals.
  • (updated on April 7, 2021) Online briefing of this Progressive Graduate Minor was held on April 7, 2021 (slides).

Overview

Because of recent dramatic development of data science (DS) and artificial intelligence (AI), several fields of research and industry try to introduce DS and AI aggressively.

From 2019, Tokyo Institute of Technology starts New data science/AI graduate education program in collaboration with industries(Education, Tokyo Institute of Technology).

  • Basic subjects (Fundamentals of data science, Exercises in fundamentals of data science, Fundamentals of artificial intelligence, Exercises in fundamentals of artificial intelligence) are for learning mathematical background of DS and AI, as well as skills of programming.
  • Applied subjects (Advanced Artificial Intelligence and Data Science A, B, C and D) are for learning the forefront applications of DS and AI in industry.
  • Other subjects are for learning knowledge of wide range of topics related to DS and AI.

The goal of "Progressive Graduate Minor in Data Science and Artificial Intelligence, Tokyo Institute of Technology" is to learn graduated level knowledge of DS and AI in order to cultivate students with advanced abilities for solving socially important issues and for creating new industry.

Schedule

the first quarter, 2021
Briefing
Application to this Graudate Minor
Advanced Artificial Intelligence and Data Science C
Subjects in 1Q
the second quarter, 2021
Advanced Artificial Intelligence and Data Science B
Subjects in 2Q
the third quarter, 2021
Fundamentals of data science, Fundamentals of artificial intelligence (English courses in the school of computing)
Exercises in fundamentals of data science, Exercises in fundamentals of artificial intelligence (Japanese courses in the school of computing)
Advanced Artificial Intelligence and Data Science A
Subjects in 3Q
the fourth quarter, 2021
Fundamentals of data science, Exercises in fundamentals of data science, Fundamentals of artificial intelligence, Exercises in fundamentals of artificial intelligence (Japanese courses in other schools)
Advanced Artificial Intelligence and Data Science D
Subjects in 4Q
the 1st quarter
MondayTuesdayThursdayFriday
8:50-10:30High Performance Scientific Computing  High Performance Scientific Computing  
10:40-12:20Practical Parallel Computing  Practical Parallel Computing  
14:20-16:00 Bioinformatics Bioinformatics
16:15-17:55Distributed Algorithms, Cloud Computing and Parallel ProcessingTheory of Statistical MathematicsDistributed Algorithms, Cloud Computing and Parallel ProcessingTheory of Statistical Mathematics, (Practical Artificial Intelligence and Data Science A(May))
18:05-19:45   Advanced Artificial Intelligence and Data Science C   (Practical Artificial Intelligence and Data Science A(May))

the 2nd quarter
MondayTuesdayThursdayFriday
8:50-10:30           
10:40-12:20 Statistical Learning Theory Statistical Learning Theory
14:20-16:00Advanced Data Engineering  Advanced Data Engineering  
16:15-17:55Multimedia Information ProcessingAdvanced Artificial Intelligence and Data Science BMultimedia Information Processing(Practical Artificial Intelligence and Data Science B-1)
18:05-19:45      (Practical Artificial Intelligence and Data Science B-2)

the 3rd quarter
MondayTuesdayThursdayFriday
8:50-10:30   Natural Language Processing, Advanced Information Security   Natural Language Processing, Advanced Information Security
10:40-12:20  Advanced Artificial Intelligence   Advanced Artificial Intelligence
14:20-16:00Fundamentals of artificial intelligence (school of computing, English)  Fundamentals of data science (school of computing, English)  
16:15-17:55Applied Probability, Exercises in fundamentals of artificial intelligence (school of computing, Japanese)Advanced Artificial Intelligence and Data Science AApplied Probability, Exercises in fundamentals of data science (school of computing, Japanese)(Practical Artificial Intelligence and Data Science C-1)
18:05-19:45      (Practical Artificial Intelligence and Data Science C-2)

the 4th quarter
MondayTuesdayThursdayFriday
8:50-10:30            
10:40-12:20Complex NetworksInformation VisualizationComplex NetworksInformation Visualization
14:20-16:00Mathematical Models and Computer Science, Fundamentals of data science (other schools, Japanese)   Mathematical Models and Computer Science, Fundamentals of artificial intelligence (other schools, Japanese)
16:15-17:55Computer GraphicsExercises in fundamentals of data science (other schools, Japanese)Computer GraphicsExercises in fundamentals of artificial intelligence (other schools, Japanese)
18:05-19:45   Advanced Artificial Intelligence and Data Science D   Advanced Artificial Intelligence and Data Science D

Target Students

Master students, doctoral students and professional degree students of Tokyo Institute of Technology are the target students of this program. Students of all schools and courses are allowed.

Students who do not apply for this program are also allowed to study the following eight subjects: Fundamentals of data science, Exercises in fundamentals of data science, Fundamentals of artificial intelligence, Exercises in fundamentals of artificial intelligence, Advanced Artificial Intelligence and Data Science A, B, C and D.

List of Courses

Specialized subjects (400 series)

Code Subject Unit Department / Graduate Major of Standard Requirement Remark
XCO.T487 Fundamentals of data science (3Q, school of computing, English)
Fundamentals of data science (4Q, other schools, Japanese)
1-0-0 A
XCO.T488 Exercises in fundamentals of data science (3Q, school of computing, Japanese)
Exercises in fundamentals of data science (4Q, other schools, Japanese)
0-1-0 A
XCO.T489 Fundamentals of artificial intelligence (3Q, school of computing, English)
Fundamentals of artificial intelligence (4Q, other schools, Japanese)
1-0-0 A
XCO.T490 Exercises in fundamentals of artificial intelligence (3Q, school of computing, Japanese)
Exercises in fundamentals of artificial intelligence (3Q, other schools, Japanese)
0-1-0 A
XCO.T483 Advanced Artificial Intelligence and Data Science A 1-0-0 B
XCO.T484 Advanced Artificial Intelligence and Data Science B 1-0-0 B
XCO.T485 Advanced Artificial Intelligence and Data Science C 1-0-0 B
XCO.T486 Advanced Artificial Intelligence and Data Science D 1-0-0 B
MCS.T403 Statistical Learning Theory 2-0-0 Department of Mathematical and Computing Science, Graduate major in Artificial Intelligence
MCS.T410 Applied Probability 2-0-0 Department of Mathematical and Computing Science
MCS.T402 Mathematical Optimization: Theory and Algorithms 2-0-0 Department of Mathematical and Computing Science, Graduate major in Artificial Intelligence
MCS.T412 Information Visualization 2-0-0 Department of Mathematical and Computing Science
MCS.T418 Practical Parallel Computing 2-0-0 Department of Mathematical and Computing Science, Graduate major in Computer Science
ART.T459 Natural Language Processing 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
ART.T464 Information Organization and Retrieval 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
ART.T462 Complex Networks 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
ART.T463 Computer Graphics 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
ART.T543 Bioinformatics 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
CSC.T438 Distributed Algorithms 2-0-0 Graduate major in Computer Science

Specialized subjects (500 series)

Code Subject Unit Department / Graduate Major of Standard Requirement Remark
MCS.T507 Theory of Statistical Mathematics 2-0-0 Department of Mathematical and Computing Science
MCS.T506 Mathematical Models and Computer Science 2-0-0 Department of Mathematical and Computing Science, Department of Systems and Control Engineering
ART.T548 Advanced Artificial Intelligence 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
ART.T547 Multimedia Information Processing 2-0-0 Graduate major in Artificial Intelligence, Graduate major in Computer Science
CSC.T523 Advanced Data Engineering 2-0-0 Graduate major in Computer Science
CSC.T521 Cloud Computing and Parallel Processing 2-0-0 Graduate major in Computer Science
CSC.T526 High Performance Scientific Computing 2-0-0 Graduate major in Computer Science
CSC.T525 Advanced Information Security 2-0-0 Graduate major in Computer Science

Remark A: Compulsory subjects, B: Elective compulsory subjects.

Please make your study plan based on the instructions of the staff of this program. If there is no staff nearby, please submit your question(s) to this form.

Requirement

More than 8 units from the list of subjects should be obtained, including 4 units from "A: Compulsory subjects", plus more than 2 units from "B: Elective compulsory subjects" (excluding the subjects that are compulsory in your Department / Graduate major). As the transitional measure, units of the eight subjects (from XCO.T483 to XCO.T490) obtained in academic year 2019 can be counted as the part of requirement for completing this program in academic year 2020. Students of "Tokyo Tech Academy for Convergence of Materials and Informatics (TAC-MI)" have to take units of "TCM.A404 Materials Informatics" instead of taking units of "XCO.T487 Fundamentals of Data Science" and "XCO.T488 Exercises in Fundamentals of Data Science".

Guide

Please read List of Study Guides and Student Handbooks.

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