TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF ENGINEERING |
| COMPUTER ENGINEERING PR. (ENGLISH) | |
| Code | CEN429 |
| Name | Introduction to Data Science |
| Term | 2021-2022 Academic Year |
| Semester | 7. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. İLKER ÜNAL |
| Course Instructor |
Prof. Dr. İLKER ÜNAL
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
By the end of the course the students will learn the basic tools that they need for data analysis. At the end of the course the students apply these tools and techniques to analyze a real-world problem by using R.
Course Content
This course will cover the topics needed to solve data-science problems, which include data preparation (collection and integration), data characterization and presentation, data analysis (experimentation and observational studies), and data products using R.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learn basic programming skills with R Programming |
| LO02 | Access the data from various sources and formats |
| LO03 | Clean and organize the data for reporting and further analysis |
| LO04 | Explore and visualize the data |
| LO05 | Conduct basic statistical analysis by using R |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has capability in the fields of mathematics, science and computer that form the foundations of engineering | 4 |
| PLO02 | - | Identifies, formulates, and solves engineering problems, selects and applies appropriate analytical methods and modeling techniques, | 4 |
| PLO03 | - | Analyzes a system, its component, or process and designs under realistic constraints to meet the desired requirements,gains the ability to apply the methods of modern design accordingly. | 3 |
| PLO04 | - | Ability to use modern techniques and tools necessary for engineering practice and information technologies effectively. | 4 |
| PLO05 | - | Ability to design and to conduct experiments, to collect data, to analyze and to interpret results | 5 |
| PLO06 | - | Has ability to work effectively as an individual and in multi-disciplinary teams, take sresponsibility and builds self-confidence | 4 |
| PLO07 | - | Can access information,gains the ability to do resource research and uses information resources | 5 |
| PLO08 | - | Awareness of the requirement of lifelong learning, to follow developments in science and technology and continuous self-renewal ability | 4 |
| PLO09 | - | Ability to communicate effectively orally and in writing, and to read and understand technical publications in at least one foreign language | 0 |
| PLO10 | - | Professional and ethical responsibility, | 4 |
| PLO11 | - | Awareness about project management, workplace practices, employee health, environmental and occupational safety, and the legal implications of engineering applications, | 0 |
| PLO12 | - | Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation, and knowledge of contemporary issues | 0 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Data Science | Reading the related chapter in lecture note | |
| 2 | Statistical Inference and Introduction to R | Reading the related chapter in lecture note | |
| 3 | Data Visualization | Reading the related chapter in lecture note | |
| 4 | Data Structures | Reading the related chapter in lecture note | |
| 5 | Generic Functions in R | Reading the related chapter in lecture note | |
| 6 | Data handling | Reading the related chapter in lecture note | |
| 7 | Midterm Overview | Reading the related chapter in lecture note | |
| 8 | Mid-Term Exam | Preparation to exam | |
| 9 | Factors and lists | Reading the related chapter in lecture note | |
| 10 | Reading and collecting data | Reading the related chapter in lecture note | |
| 11 | Writing functions | Reading the related chapter in lecture note | |
| 12 | Descriptive statistics | Reading the related chapter in lecture note | |
| 13 | Rmarkdown | Reading the related chapter in lecture note | |
| 14 | Maps and animations | Reading the related chapter in lecture note | |
| 15 | Final Exam Overview | Reading the related chapter in lecture note | |
| 16 | Term Exams | Preparation to exam | |
| 17 | Term Exams | Preparation to exam |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Homework | 34 | 13.6 |
| 2. Homework | 33 | 13.2 |
| 3. Homework | 33 | 13.2 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||