Amelia Giuseppina NOBILE | PRINCIPLES OF INFORMATICS
Amelia Giuseppina NOBILE PRINCIPLES OF INFORMATICS
cod. 0512800019
PRINCIPLES OF INFORMATICS
| 0512800019 | |
| DEPARTMENT OF CHEMISTRY AND BIOLOGY "ADOLFO ZAMBELLI" | |
| EQF6 | |
| BIOLOGICAL SCIENCES | |
| 2018/2019 |
| OBBLIGATORIO | |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2016 | |
| SECONDO SEMESTRE |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| INF/01 | 4 | 32 | LESSONS | |
| INF/01 | 2 | 24 | EXERCISES |
| Objectives | |
|---|---|
| THE AIM OF THE COURSE IS TO PROVIDE A GENERAL INTRODUCTION TO THE COMPUTER SCIENCE AND TO THE USE OF SPECIFIC TOOLS FOR THE STATISTICAL ANALYSIS OF BIOLOGICAL DATA. IN THE FIRST PART OF THE COURSE WILL BE PROVIDED SOME BASIC KNOWLEDGE ON THE ARCHITECTURE OF COMPUTERS AND ON COMPUTER NETWORKS, ON THE REPRESENTATION OF INFORMATION IN COMPUTERS, ON THE FUNDAMENTALS OF PROGRAMMING AND OF ALGORITHM DESIGN. THE AIM OF THE SECOND PART OF THE COURSE IS TO FAMILIARIZE STUDENTS WITH THE USE OF COMPUTERS FOR STATISTICAL COMPUTATION. |
| Prerequisites | |
|---|---|
| ARE NOT REQUIRED SPECIFIC PREREQUISITES: BASIC CONCEPTS OF MATHEMATICS ARE USED. |
| Contents | |
|---|---|
| FIRST PART: AN INTRODUCTION TO COMPUTER SCIENCE. COMPUTER ARCHITECTURE. COMPUTER SYSTEM ORGANIZATION. NUMBERING SYSTEMS. BINARY REPRESENTATION OF NUMERIC AND TEXTUAL INFORMATION. BINARY REPRESENTATION OF SOUNDS AND IMAGES. BOOLEAN LOGIC AND GATES. EXAMPLES OF LOGIC CIRCUIT DESIGN AND CONSTRUCTION. THE CONCEPT OF AN ALGORITHM. THE EFFICIENCY OF ALGORITHMS. REPRESENTING ALGORITHMS. PSEUDOCODE. SEQUENTIAL STRUCTURES. CONDITIONAL AND ITERATIVE STRUCTURES. EXAMPLES OF ALGORITHMIC PROBLEM SOLVING. SELECTION SORT AND BUBBLE SORT. SEQUENTIAL SEARCH AND BINARY SEARCH. INTRODUCTION TO HIGH-LEVEL LANGUAGE PROGRAMMING. BIOLOGICAL APPLICATIONS. SECOND PART: DATA MANAGEMENT IN R. DATA STRUCTURES IN R. PROGRAMMING WITH R. DESCRIPTIVE ANALYSIS FOR QUANTITATIVE AND QUALITATIVE VARIABLES. SOME GRAPHICAL REPRESENTATIONS IN R. MEAN, MEDIAN, QUANTILE AND MEASURES OF VARIABILITY. BIVARIATE DISTRIBUTION. CORRELATION. REGRESSION. |
| Teaching Methods | |
|---|---|
| THE TEACHING METHOD INCLUDES THEORETICAL LESSONS INTEGRATED CONTINUOUSLY BY EXERCISES AND PROGRAMMING EXAMPLES. |
| Verification of learning | |
|---|---|
| THE FREQUENCY OF LECTURES IS STRONGLY RECOMMENDED. THE EXAMINATION CONSISTS OF AN ORAL TEST. THE END RESULT DEPENDS ON THE KNOWLEDGE ACQUIRED BY APPLYING THE PROGRAMMING TECHNIQUES AND THE STATISTICAL METHODS TO SOLVE CONCRETE PROBLEMS. |
| Texts | |
|---|---|
| - J. GLENN BROOKSHEAR: “INFORMATICA - UNA PANORAMICA GENERALE” (11/ED.) PEARSON ITALIA, 2012 - GIUSEPPE ESPA, ROCCO MICCIOLO: “ANALISI ESPLORATIVA DEI DATI CON R”, APOGEO, 2012. - LECTURE NOTES OF THE TEACHER |
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