Essential Computer Science for Global LeadersⅡto begin on October 7, 2019

 Class List of Fall Semester 2019

“Essential Computer Science for Global LeadersⅡ” will begin on October 7. This is a class for students in “Minor Course of Science and Technology for Global Leaders”. But all master’s & doctoral students can take it if you have interest. The class will be conducted in English.

Theme & Objective

Prof. BasharSteady increase of the deployment of computer systems in many real world applications made computer science and engineering an inevitable discipline in the current epoch of human history. Along with electronics, it drives the information revolution following industrial and agricultural revolutions. Future progress and the ultimate shape of this planet will largely depend on how the next generation global leaders are going to be equipped with essential knowledge on computer science and engineering. In this course, light will be shed on some advanced topics involving information security, artificial intelligence, the design and control of electronic devices for some real world applications.

Message to Students

Lecture will be delivered in both Japanese and English. Simple English will be used. Inquiries can be sent to Md. Khayrul Bashar at
Email :
Tel : 03-5978-2557 ;
Office : Science Building – 3 (Room : in front of Elevator Door at 3rd Floor)
N.B. Contents or the extent of the topics may be refined subject to necessity

Lecture Outline

Essential Computer Science for Global LeadersⅡ [19S1011]
Number of Credits
BASHAR, Md Khayrul (Project Associate Professor of Ochanomizu University)
Target Audience
Graduate Students
Graduate School of Humanities & Sciences Building R408
Date & Time
Monday*, Period 3-4 (10:40-12:10)
*except for January 16 (Thu)
Year 2019
  October 7, 21, 28
  November 4, 11, 18, 25
  December 2, 9, 16, 23
Year 2020
  January 6, 16, 20, 27
Lecture Plan

(a) Data Explorations (Four (4) classes)

  • Introduction to data science, data types, typical data analysis methods.
  • Feature extraction from image data (Local Binary Pattern (LBP), Histogram of Oriented Gradient (HOG), Scale Invariant Feature Transform (SIFT) and other transforms (Fourier transform, wavelet transform etc.)
  • Feature selection and related algorithms
  • Practice sessions on data analysis (C++/Matlab/Python/R)

(b) Machine learning and applications (Six (6) classes)

  • Introduction, Some machine learning algorithms: minimum distance to mean, k- Nearest Neighbor, Maximum Likelihood and Naive Bayes, linear discriminant analysis (LDA), Decision Tree, Support Vector Machine (SVM)).
  • Basics of artificial neural network (ANN) ; Some neural network algorithms (single and multilayer perceptron (MLP), deep learning).
  • Practice sessions on machine learning algorithms.
  • Assignment / Test

(c) Internet-Of-Things (IoT) (Five (5) classes)

  • Introduction, Brief history of IoT, How it works ?;
  • Structure of IoT; Current status and future prospect;
  • Examples of IoT (fruit quality detection; human face tracking using webcam; car detection and traffic analysis)
  • Final test/report

NB: Contents may be revised or modified subject to necessity.

Out-of-class Learning
Having general idea before each lecture may be useful.
  1. Computer Vision: Algorithm and Applications – Richard Szeliski
  2. S. Haykin, Neural Networks: A comprehensive Foundation, MacMillan College Publishing Co. New York, 1994
  3. C++ How to Program by Paul Deitel and Harvey Deitel
  4. Arduino Sketches: Tools and Techniques for programming Wizardry – James A. Langbridge
  5. Make: JavaScript Robotics — Backstop Media and Rick Waldron
  6. Signal Processing for Neuroscientists – Wim van Drongelen
  7. Rajkumar Buyya: Internet of Things — Principles and Paradigm, Morgan Kaufmann, Elsevier, USA, 2016.
  8. Lecture materials will also be supplied whenever needed


Registration Period: Tue., October 1 through Mon., October 14
If you cannot register during above period, please contact Academic Affairs Office in Student Affairs Building.
*For undergraduate students, please contact Leading Graduate School Promotion Center.


Ochanomizu University Leading Graduate School Promotion Center
Tel: 03-5978-5775