Essential Computer Science for Global LeadersⅡto begin on October 2, 2017 (Date & Time changed)

 Class List of Fall Semester 2017

“Essential Computer Science for Global LeadersⅡ” will begin on October 2. 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 [17S1011]
Number of Credits
BASHAR, Md Khayrul (Project Associate Professor of Ochanomizu University)
Target Audience
Graduate Students
Graduate School of Humanities & Sciences Building R408
except for November 30 at Graduate School of Humanities & Sciences Building R102
Date & Time
Monday*, Period 3-4 (10:40-12:10)**
*except for November 30 (Thu) and January 11 (Thu)
**except for November 30 (Thu) and December 11 (Mon) Period 5-6 (13:20-14:50)
Year 2017
  October 2, 16, 23, 30
  November 6, 13, 27, 30 (13:20-14:50)
  December 4, 11(10:40-12:10, 13:20-14:50), 18, 25
Year 2018
  January 11, 15, 22, 29
Lecture Plan

Data Explorations (Four (4) classes)

  • Introduction to data science, Exploratory data analysis and some EDA tools (Box plot, histogram, PCA etc.)
  • Feature generation and feature types (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 (filters, wrappers and decision tree etc.)
  • Interactive sessions or demonstration : data/ signal analysis (Matlab)

Data science and machine learning techniques and their applications (Six (6) classes)

  • Machine learning basics ; Some machine learning algorithms (regression and classification : Bayesian, k- Nearest Neighbor (k-NN), Decision Tree, Support Vector Machine (SVM)).
  • Interactive sessions or demonstration : Biometric recognition system / disease classification
  • Introduction to artificial neural network ; Some neural network algorithms (Single & Multilayer perceptron (MLP), deep learning).
  • Interactive sessions or demonstration : Biometric recognition system / disease classification/
  • Assignement / Test

Internet-Of-Things (Last 5 classes)

  • Introduction to arduino electronics and sketch; Programming basics on device control (C/C++) ;
  • Develop a simple Arduino system for fruit quality detection
  • Introduction to internet of things (IoT)
  • Interactive sessions or demonstrations on human face detection and tracking using webcam-acquired video stream; car detection and traffic analysis.
  • Final test or report
  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: Mon., October 2 through Sat., October 14
If you cannot register during above period, please contact Academic Affairs Office in Student Affairs Building.


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