Hiroshima University Syllabus

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Academic Year School/Graduate School Lecture Code 2024Year Liberal Arts Education Program 30104001 Information and Data Science Courses Fundamental Data Science Fundamental Data Science NUNES TENDEIRO JORGE ナヌッシュ　テンデイル　ジョージ Higashi-Hiroshima 1st-Year,  Second Semester,  4Term (4T) Inte：Online Lecture Mainly video lectures (including practical assignments) 2.0 E : English 1 : Undergraduate Introductory 25 : Science and Technology 01 : Mathematics/Statistics B1 Basic data science, statistical methods, practical exercises using R and Excel Acquire basic knowledge and skills for data science 1. To acquire basic knowledge, skills, and attitudes regarding information science and data science, and thereby to be able to process data and handle information appropriately.2. To understand and be able to explain information ethics and social challenges for data usage. Learn the basics of data science and data analysis lesson1: Guidance and Introductionlesson2: Data acquisition and open data, data science ethicslesson3: Types of data and descriptive statisticslesson4: Descriptive statisticslesson5: Visualizing data in Rlesson6: Correlation and regressionlesson7: Simple regression analysis using Excellesson8: Principal component analysis and cluster analysis using Rlesson9: Probabilitylesson10: Random variable and probability distributionslesson11: Basic probability distributionslesson12: Bivariate probability distributionslesson13: Methods for data collectionlesson14: Point estimation and interval estimationlesson15: Interval estimationQuizzes will be assigned after each lecture. No final exam in the end of the semester Not specified handouts, lecture slides, requisite PC specified by Hiroshima University Review each lesson using lecture materials. Practical exercises will be given in the course. Therefore, a requisite PC specified by Hiroshima University (https://www.hiroshima-u.ac.jp/en/about/initiatives/jyoho_ka/hikkei_pc) is mandatory to have. Please make sure that Excel is correctly installed and ready to use. Be aware that the course contents are largely overlapped between the current course and the following courses: "Fundamental Data Science (30101001)" and "Fundamental Data Science (30830001)". Therefore, once you enroll in this course, you cannot enroll to the other previously mentioned two courses (note that the other two courses are given in Japanese). check tests (Quizzes) The course is in on-demand format, using Moodle, Microsoft Teams, and Microsoft Stream. We will notify you about the details of the course (e.g. how to watch lecture videos) via Momiji. Days and time of posting lecture materials:Lesson 1: Nov 29th, Lesson 2: Dec 4th,Lesson 3: Dec 6th, Lesson 4: Dec 11th,Lesson 5: Dec 13th, Lesson 6: Dec 18th,Lesson 7: Dec 20th, Lesson 8: Dec 20th,Lesson 9: Jan 8th, Lesson 10: Jan 10th,Lesson 11: Jan 15th, Lesson 12: Jan 15th,Lesson 13: Jan 22nd, Lesson 14: Jan 24th,Lesson 15: Jan 29th (Each lesson will be posted at 8:30 AM) Please fill in the class improvement questionnaire which is carried out on all classes.Instructors will reflect on your feedback and utilize the information for improving their teaching.
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