- New required course “Information I” useful for work, a waste not only for high school students
- Amazon
- Programming languages handled in Information I
- Fable of the Tayupinko people. - The parable of the Tayupinko people
- Aside: Business Continuity and Personnel Changes.
- Japanese firms’ IT systems depend on bottom-line capabilities.
- Public key cryptography, hash functions, digital signatures
- Pigs and Encoding
- Causality and pseudo-correlation
- You can make indicators to make decisions, FQ7
- KPI is the human tongue.
- Why is it so hard to define requirements?
- Think in advance of possible changes.
- Easy and hard specification changes for programmers. This is the second unabridged manuscript of Information I. It is related to ChatGPT and machine learning. 85%E5%A0%B1%E2%85%B0%E6%9C%AC-%E6%9C%AA%E5%8F%8E%E9%8C%B2%E5%8E%9F%E7%A8%BF%E4%BE%9B%E9%A4%8A-%E3%81%9D%E3%81%AE%EF%BC%92-c5c48fd 04a69
- Search Engine and LLM Integration, Benefits and Issues
- Ask in the abstract, then apply to reality.
- ChatGPT mimics the thinking of System 1
- ChatGPT is Advanced Data Analysis and plug-ins for limited System 2
- ChatGPT is not available for FAQs.
- What is made more efficient by generative AI in labor?
- Multimodalization of Generative AI
- democracy (free speech) and Generative AI are incompatible
- Problems with Learned Models
- The bookstore of the future, the age of book generation
- We see the introduction of machine learning as a shift to the equipment industry, and we will draw up a revenue/expense plan.
Table of Contents
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Chapter 1: The Impact of Information I
- 1-1: What are today’s high school students learning?
- The Impact of the “Information I” Prototype Problem
- Flow of Information Education in High School
- Information I Objectives and Curriculum
- Relationship between IT Passport and Information I
- Explanation of the “Information” prototype problem (Simulation of crepe sales)
- New “Reading, Writing, and Soroban” by Information I
- Study acquires the knowledge of the ignorant
- 1-2: What is modern business improvement?
- Without computers, we have nothing.
- Computers outnumber the earth’s population.
- Computers are used in all professions.
- Moore’s Law, Advances in Semiconductor Integrated Circuits
- Computers that are less expensive and more powerful
- Breakthrough for Software Companies
- What is agility in a software company?
- Information ensures “modern agility”.
- 1-3: DX in its entirety What is the agility of Japanese companies?
- What was the agility of Japanese companies and the strength of Japanese companies?
- DX is a change in the source of agility
- Dysfunctional Agility of Japanese Companies
- Spreading the concept of DX
- Disruption
- Misreading of DX reports
- Reflections on the DX Report 2, and changes to the definition of DX.
- The concept of DX as a dark pot, various DX directions
- If you want to DX, don’t use the word “DX”.
- Dangers of the term “human capital,” collective efficacy, cognitive dissonance, and big-picture management
- Post-DX organization, changes in required qualities
- Information as reskilling|IT Passport, Statistics Test
- 1-1: What are today’s high school students learning?
-
Chapter 2: Getting an Overview of Information I
- 2-1: Information Society and Us
- Information Society and Problem Solving
- Laws and Institutions in the Information Society
- Information security and measures taken by individuals
- Media
- communication
- Information Design and Expression
- Content Creation
- How to represent information
- Digital Expression on Computers
- Information Equipment and Computers
- Algorithm and Basic Structure
- Program Basics
- Program Applications
- modelling (e.g. a system, etc.)
- Simulation
- Utilization of Data
- How the Network Works
- Information Systems and Services
- Information Security
- 2-1: Information Society and Us
-
Chapter 3: Understanding Information More Deeply
- 3-1: What is the difference between computers and humans?
- Very little the CPU can do
- There are so many things a CPU can do
- Algorithms are made from algorithms.
- Humans can see the “whole”. Computers cannot see the “whole.
- When there are more of them, people cannot see the “whole”.
- Computers can’t see the “whole” either, but they can.
- What is Programming? CPU Elephant Evaluation
- How does the world look from a computer’s point of view?
- Think about the problem itself and simplify the problem with statistics.
- 3-2: Statistics look at the “whole” without looking at the “totality
- Strengthening probability statistics in school education, making probability statistics compulsory
- The purpose of the revision of mathematics teaching guidelines, the widespread use of computers and probability statistics, and mathematical problem solving.
- statistical training
- 6th grade (mean, median, mode, typical)
- 6th grade (class, histogram)
- Middle school 1st year (relative and cumulative relative frequencies of histograms)
- Second grade (percentile values, interquartile range, box plots)
- Middle School 3rd Grade (sample survey/total survey, sampling, random sampling, population, sample size, sample mean and population mean)
- High School Mathematics I (Deviation, Mean Deviation, Variance, Standard Deviation)
- High School Mathematics I (scatter plots, correlation coefficients)
- High School Mathematics I (Hypothesis Testing)
- Those who look only at statistics are deceived.
- selection bias
- information bias
- publication bias
- 3-3: Requirement definition is a top-to-bottom breakdown
- V-shaped model of system development
- V-shaped model for small projects
- Hearing what you want to do
- Listen to the requests. We listen and then ignore them to solve the real issues.
- Requirement definition is breakdown and matching
- Why can mathematics and information technology solve problems?
- Computers are not zeroes and ones. Theory and De Facto Standards
- 3-1: What is the difference between computers and humans?
-
Chapter 4: Beyond Information I, What We Need to Learn Now
- 4-1: From Programming to Machine Learning
- Here is my lecture “From if statements to machine learning 」がもとになってます(明示的に許可を出してます)
- From If statement to polynomial
- Fundamentals of Machine Learning with the Perceptron
- There are cases where accuracy is poor but still valuable.
- Differences between Academia and Business
- 4-2: Social Transformation through Generative AI
- Generation AI adds to IT Passport syllabus
- Intelligence and Halcynation of ChatGPT
- From the Age of Search to the Age of Generation
- The fool questions knowledge, the wise man argues
- 4-3: Government Buzzword Commentary
- ESG、SDGs
- Industry 4.0, the Fourth Industrial Revolution
- CPS: Cyber-Physical System, Data-driven Society
- Society 5.0, super-smart society
- 4-1: From Programming to Machine Learning
- Here is my lecture “From if statements to machine learning 」がもとになってます(明示的に許可を出してます)
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