Essential Computer Science for Global Leaders Ⅱ 2017年10月2日開講 

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10月2日より、Essential Computer Science for Global LeadersⅡを開講します。この科目はグローバル理工学副専攻の履修科目になっていますが、博士前期・後期課程に所属し、関心のある学生であれば、どなたでも履修することができます。なお、講義は英語で行われます。

本講座の主旨

Bashar特任准教授Steady 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.

学生へのメッセージ

Lecture will be delivered in both Japanese and English. Simple English will be used. Inquiries can be sent to Md. Khayrul Bashar at
Email : basha.md.khayrul@ocha.ac.jp
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

講義概要

科目名
Essential Computer Science for Global LeadersⅡ [17S1011]
単位数
2.0単位
担当教員
BASHAR, Md Khayrul (お茶の水女子大学プロジェクト教育研究院特任准教授)
対象
博士前期・後期課程
場所
人間文化研究科棟408室
日時
月曜 3~4限(10:40-12:10)
1月11日(木)を除く
2017年
 10月2日、16日、23日、30日
 11月6日、13日、27日
 12月4日、11日、18日、25日
2018年
 1月11日、15日、22日、29日
授業計画

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
教科書・参考文献
  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

履修登録

他の後期開講科目と同様にWeb上で履修登録をしてください。
履修登録期間: 10月 2日(月) ~ 10月14日(土)
上記登録期間内に登録ができなかった場合には、学生センター棟1階学務課にご相談ください。

お問合せ

お茶の水女子大学 リーディング大学院推進センター
Tel: 03-5978-5775
E-mail: