Syllabus Reference

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Course title Introduction to data science[A]
Responsible department Common to all Colleges
Term Spring Lecture classification Pre-registration
Credit(s) 2
The main day Saturday The main period 4th period
Campus On Demand
Numbering Code DTSC-1-JL-KGU
Lecture Style Lecture
Active Learning Type B

Instructor
Full name
* Higuchi Koki

Course Theme and Description In this lecture, as an introductory subject of data science, you will learn what data science is, what kind of possibilities data science has in various fields, what kind of technology development it will lead to, and as an introduction to data science, you will learn the basics.
Course Objectives Understand the significance of studying data science by understanding the basic concepts of data science from the various information and data that overflows in the world with daily life as subjects in a data-driven society, and understanding the basic concepts related to data science. In addition, the goal is to learn appropriate data analysis methods according to the purpose of analysis, and to provide motivating learning that can lead to learning with specialized fields. Explain each analysis in data science and acquire the security and information ethics necessary for using information and data.
Method of feedback(test, report etc.) Outstanding answers will be posted on manaba with their names withheld.
Class Schedule
No.Lecture's / Class Theme and DescriptionLecture's / Class GoalHomework(Preparation)Homework(Review)
1Explain the content of the lecture based on the syllabus.
How data will change society (1) How far should business people be able to do data science?
Understand the practical level of data science required in the business world, and understand the goal point we should aim for.
You will also learn about information security, which is important for using data.
I would like everyone to take on the challenge of data analysis, so I would like everyone to cooperate with the survey. Personal information will be completely confidential, so students are encouraged to complete this survey. Let's analyze everyone by ourselves!Find websites and articles that use data to present analyses, such as the one I showed you during the lecture. Google Images search may be useful. Then, while using the data, analyze it in your own way and formulate improvement measures (management measures, policies, improvement plans for back services) from there. The material can be anything, whether it's a game, an app, a manga, an anime, a drama, or a YouTuber!
2In Excel, find the "middle" of the dataGiving appropriate instructions in classGiving appropriate instructions in class Feel free to use "everyone's data" to show the mean, median, and mode of a few questions, and then ask yourself "what can I say from that?" For example, if you were to apply the results to your business, what would you do?
3How data will change society (2) What is AI?Learn about the brief history of AI, its technical structure, and how it is put to practical use.Giving appropriate instructions in classWhat would you like to do with AI? Please take into account "what can be achieved with AI" and the prerequisites required for that, and then come up with new ideas for utilizing AI.
4Know the "variance" of your data You will be able to create bar charts and pie charts. I understand that these graphs are not childish tools, but the most important methods of statistics.Giving appropriate instructions in classFreely select three questions from "Everyone's Data" and draw a bar chart or pie chart. From there, analyze what you can read. For example, if you were to use this in corporate management, what measures could you take?
5How Data Changes Society (3) What is the Fourth Industrial Revolution?Understand the concept of the Fourth Industrial Revolution and possible social changesGiving appropriate instructions in classPlease introduce one of the news reports or actual products and services, and discuss what could happen in the Fourth Industrial Revolution around you.
6Know the "relationship" between two numbers Students will be able to understand the relationship between two types of variables, scatter plots and correlation, and apply them to management measures. Nothing in particularFrom "Everyone's Data", discover the relationship between two interesting variables in a scatter plot. From there, think about what you can say.
7How data changes society (4) Application example of AI: Visualization of success probability of kurafanunderstand the potential of AIGiving appropriate instructions in classPlease consider "AI that is likely to be useful for earnings (acquisition of sales, customers, investment, etc.)" and "AI that is likely to be useful for reducing costs in society (reducing costs and resource consumption)."
8Fundamentals of Statistics (4) Surprisingly easy to understand regression analysis and become self-effective Be able to perform regression analysis yourselfGiving appropriate instructions in classUsing "everyone's data", feel free to perform regression analysis and think about what can be said from it. You can use the one you wrote the scatter plot on one more time.
9How data will change society (5) Let's use AIYou will be able to use AI services on the web to think and do things
You will also learn what to keep in mind when using data and AI.
Giving appropriate instructions in classPlease feel free to submit the results of your analysis using one of the various AI services introduced in the lecture.
10What does "statistically significant" mean? Understand what "statistically significant" is, which is often seen in papers and is also important in today's data science practice. You will be able to do it yourself in Excel.Giving appropriate instructions in classFeel free to use "everyone's data" to perform a t-test to prove the difference between the two groups. Based on that, please discuss what kind of improvement measures are effective.
11How Data Changes Society (6) DX and Data ScienceUnderstand what the "after digital" changes that are occurring at the same time as the data science and AI revolution are, and how they relate to each other. Giving appropriate instructions in classPlease introduce one thing that you think "this is what after-digital is" and think about what kind of data utilization is behind it. Don't worry if it doesn't suit you (no points will be deducted). It is important to be able to imagine that behind the digital services you are using is data and its use.
12Practice: Strategic Theory of Probabilistic ThinkingAcquire the concept of conditional probability, which is effective in the probability analysis of occurrence of things, and be able to make measures using it.Giving appropriate instructions in class From "everyone's data", select variables that can be analyzed as percentages and probabilities, and create a model of conditional probabilities. Then, please think about what you can do to improve the probability (management measures, policies, service improvement plans, etc.).
13How data will change society (7) Human resources needed in the Fourth Industrial RevolutionUnderstand the image of human resources required in the future data era and the organization and strategy required for DX Nothing in particularIn anticipation of the coming era, if you were to work in a job that involves data, what kind of person would you be? Think about what skills you need to acquire to achieve this.
14Sampling Be able to conduct surveys properly Nothing in particular If you have a budget of 50,000 yen and decide to conduct a questionnaire using an Internet research company about "what you want to know", please design the target of the questionnaire and specific question items. (10 yen per question per person).
Grade evaluation method and criteria - Normal score (quizzes, reaction papers, reports, etc.) (80%)
- Final assignment (20%)

In addition, if the attitude of the course is not appropriate, point deduction will be taken.

In addition, "report" will be evaluated based on (1), "presentation" will be evaluated based on (2), and "reaction paper" will be evaluated based on (4).
Related Courses 「Exercises in data science」
Explanation of teaching methods No mark: face-to-face courses ★: online courses
Preparation Hours 2
Review Hours 2
Practical experiences of Instructor He was engaged in system development work, and then focused on research and analysis work using data analytics and machine learning. His main achievements include the identification of success factors by analyzing survey data on start-up companies, the statistical analysis of a survey of young people on the actual state of SNS use, and the development of employment evaluation sheets for the purpose of supporting side jobs. He also has experience in designing and developing business applications, and is involved in system construction and data utilization in a wide range of fields
How to utilize practical experiences in class Utilizing practical experience in system development and data analysis, we emphasize connecting data science to learning that is conscious of its use in the real world, rather than just theory. The purpose of this course is not to acquire advanced machine learning techniques, but to acquire the ability to properly understand data and analyze it using basic statistical methods (average, scatter, correlation, etc.).
Through this course, we aim to help students learn the basics of how to handle data and develop the ability to think about how to use data to solve problems. By solidifying the foundation of data science, you will be able to acquire the groundwork to use data in your future studies and future careers.

Rubric https://univ.kanto-gakuin.ac.jp/education/center-for-research-and-development-of-higher-education.html#10
Numbering Code Detail ・ Diploma Policy https://univ.kanto-gakuin.ac.jp/education/syllabus.html
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Reference book(s) | materials
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