Information Processing 2

Course title

V2820700

	ISHIWATA Tetsuya
	OZAKI Katsuhisa

Course description

This lecture concerns programming in C language and Mathematica(Computer algebra system). Students write their codes in C language, and learn applications using built-in functions in Mathematica.
In this lecture, students learn basic concepts and methods for C programming, how to use Mathematica for symbolic computation, data analysis, and visualization.
This exercise is strongly related to "Exercises in Information Processing 2."

Purpose of class

Programming is necessary for special subjects in the department of mathematical sciences after the second year. In this lecture, students learn basic structured programming using C language and symbolic computation using Mathematica.
In addition, students have experience in data analysis, numerical computations and visualization of data.

Goals and objectives

to be able to write codes with variable, if branch, for loop, function, pointer, recursive function calling.
to be able to make a code in C language, treat data, and give a mathematical analysis
to understand symbolic computation and to be able to use Mathematica for several mathematical problems and data analysis.
to be able to give a visualization of numerical data.

Language

Japanese

Class schedule

	Class schedule	HW assignments (Including preparation and review of the class.)	Amount of Time Required
1.	Introduction, Compile, Output: Compile and Execution, Basic computation, output: printf	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
2.	Variables and Data, Type Output and Input : printf, scanf Branch: if, if else Loop: for Logical expression	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
3.	Visualization of the process: flowchart Array	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
4.	Multiple loops Array, data analysis: 1 dimensional array, average, variance, standard deviation, the maximum value, the minimum value, deviation value Programming with Pseudo-random Numbers: Monte Carlo simulation:	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
5.	Group exercise 1 　　Sort, Monte-Carlo and so on...	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
6.	Functions and Procedures, Exercise for Statistics: format of functions, functions for statics	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
7.	Recursive Functions: Recursive Functions, Sequence	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
8.	Pointer	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
9.	Group exercise 2 Exercise for Probabilistic.	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
10.	Summary on C programing, Examination	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
11.	Mathematica 1 Basic calculation Solve Equations Statistical processing average, variance, standard deviation, the maximum value, the minimum value, deviation value	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
12.	Mathematica 2: Visualization of function and data	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
13.	Group exercise 3 　Data analysis using real data by C and Mathematica	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
14.	Group exercise 3 (continued) Conclusion	Preparation: Read the webpage of this lecture. Review: Check again the webpage of this lecture and finish all exercises.	200minutes
Total.	-	-	2800minutes

Relationship between 'Goals and Objectives' and 'Course Outcomes'

	Reports	Total.
1.	35%	35%
2.	35%	35%
3.	15%	15%
4.	15%	15%
Total.	100%	-

Evaluation method and criteria

The reports include the following
　Regular reports
　Group work reports and peer evaluations
　Progress questionnaires for each session

The achievement of students will be evaluated by all reports and submissions. If the score is 60% or more, you can pass.

Textbooks and reference materials

original web-site for this lecture

Prerequisites

Information Processing I and its exercise,
Exercises in Information Processing 2 (in parallel)

Office hours and How to contact professors for questions

Ishiwata: Thu. (12:35:13:05) （Make appointments in advance.）

Regionally-oriented

Non-regionally-oriented course

Development of social and professional independence

Course that cultivates a basic interpersonal skills
Course that cultivates an ability for utilizing knowledge
Course that cultivates a basic problem-solving skills

Active-learning course

About half of the classes are interactive

Course by professor with work experience

Work experience	Work experience and relevance to the course content if applicable
N/A	該当しない

Education related SDGs:the Sustainable Development Goals

4.QUALITY EDUCATION
9.INDUSTRY, INNOVATION AND INFRASTRUCTURE

Last modified : Fri Mar 18 22:43:02 JST 2022