TÜRKÇE
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Information
| Code | CEN136 |
| Name | Introduction to Data Science |
| Term | 2024-2025 Academic Year |
| Semester | 2. 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 |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Mehmet SARIGÜL |
| Course Instructor |
1 |
Course Goal / Objective
The aim of this course is to provide basic knowledge and skills in computer science and programming. Students are expected to develop algorithmic thinking skills and to analyse and solve problems effectively. Within the scope of the course, students: Learn the basic concepts of computer science such as abstraction, algorithms and data structures, Practises using programming languages (C, Python, SQL, JavaScript, HTML, CSS) and new technologies, Understands software development processes and basic software engineering principles such as resource management, Gain basic knowledge in areas such as data visualisation and basic statistics, It reinforces what they have learnt by making applications associated with real world problems. This course provides students with an introduction to computer science and a solid foundation in the world of programming.
Course Content
This course is the introduction to computer science and programming. It is suitable for all students who do not have any programming knowledge or have basic knowledge. The aim of the course is to gain algorithmic thinking skills and to teach effective solutions to problems.
Course Precondition
Simple algorithm knowledge
Resources
1- C Programming Absolute Beginner’s Guide, Third Edition Greg Perry, Dean Miller Pearson Education, 2014 ISBN 0-789-75198-4
Notes
2- Hacker’s Delight, Second Edition Henry S. Warren Jr. Pearson Education, 2013 ISBN 0-321-84268-5 3- How Computers Work, Tenth Edition Ron White Que Publishing, 2014 ISBN 0-7897-4984-X 4- Programming in C, Fourth Edition Stephen G. Kochan Pearson Education, 2015 ISBN 0-321-77641-0 https://www.edx.org/cs50
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Gains algorithmic thinking and problem solving skills. |
| LO02 | Can make applications in basic programming languages. |
| LO03 | Understands the basic concepts of computer science. |
| LO04 | Develop solutions for real world problems. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Adequate knowledge of mathematics, science and related engineering disciplines; ability to use theoretical and applied knowledge in these fields in solving complex engineering problems. | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Ability to identify, formulate and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering practice; ability to use information technologies effectively. | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Ability to design and conduct experiments, collect data, analyze and interpret results to investigate complex engineering problems or discipline-specific research topics. | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Ability to work effectively in interdisciplinary and multidisciplinary teams; individual working skills. | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Ability to communicate effectively verbally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and understandable instructions. | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Awareness of the necessity of lifelong learning; ability to access information, follow developments in science and technology, and constantly renew oneself. | 3 |
| PLO09 | Bilgi - Kuramsal, Olgusal | Knowledge of ethical principles, professional and ethical responsibility, and standards used in engineering practice. | 5 |
| PLO10 | Bilgi - Kuramsal, Olgusal | Knowledge of business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; knowledge of sustainable development. | 4 |
| PLO11 | Bilgi - Kuramsal, Olgusal | Knowledge of the effects of engineering practices on health, environment and safety in universal and social dimensions and the problems of the age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Course introduction and basic concepts | Course introduction and basic concepts | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 2 | Numbers and Data Representation | Binary, decimal, octal and hexadecimal number systems Computerised representation of data | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Algorithms and Flow Charts | What is an algorithm? Characteristics and types. Problem solving with flow charts | Öğretim Yöntemleri: Anlatım |
| 4 | Introduction to Programming Languages | Basic structure of programming languages, Introduction to C programming language: data types, variables and input/output operations | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 5 | Control Structures and Loops | Conditional statements (if-else, switch), Loops (for, while, do-while) | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 6 | Functions and Modular Programming | Definition, writing and calling of functions, Parameter passing and return values, Modularisation of the code | Öğretim Yöntemleri: Anlatım, Gösterip Yaptırma |
| 7 | Introduction to Data Structures | Array, linked list, stack and queue, Applications of simple data structures | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav |
|
| 9 | File Operations | Reading and writing of files, Data storage and retrieval applications | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 10 | Web Development Fundamentals | Basic web page design with HTML and CSS, Creating a simple form and style | Öğretim Yöntemleri: Anlatım, Tartışma |
| 11 | Introduction to Python Programming | Python's basic structure and data types, Problem solving with Python | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 12 | SQL and Data Management, CyberSecurity and Ethical Principles | Fundamentals of SQL and database querying, Information security and encryption basics, Ethics and professional responsibility in engineering | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Identifying concepts for data science projects in groups | Identifying concepts for data science projects in groups | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
| 14 | Project Management and Innovation | Project planning and risk management, Innovative thinking and sustainable development concepts | Öğretim Yöntemleri: Beyin Fırtınası |
| 15 | Software Development Processes, GitHub and Version Control | Introduction to software development processes, Introduction to methods such as Agile, Scrum and Kanban, Collaboration and communication in software projects, Using Git and GitHub, Basics of version control systems, Git commands. | Öğretim Yöntemleri: Anlatım, Tartışma, Beyin Fırtınası |
| 16 | Final Exams | Ölçme Yöntemleri: Yazılı Sınav |
|
| 17 | Final Exams | Ölçme Yöntemleri: Yazılı Sınav |
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 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 3 | 8 | 24 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 14 | 14 |
| Final Exam | 1 | 28 | 28 |
| Total Workload (Hour) | 150 | ||
| Total Workload / 25 (h) | 6,00 | ||
| ECTS | 6 ECTS | ||