BIG DATA CONCEPTS AND APPLICATIONS

Course Description

This course covers big data, which becomes increasingly available with digitalization of many aspects of human life and with increasingly growth of social media platforms. The course presents a broad understanding of big data and different approaches of big data manipulation. Students will explore how terabytes and petabytes of storage space can be occupied by big data. In this course, the Hadoop software, the Hadoop Distributed File System (HDFS) and the MapReduce technique as well as supervised and unsupervised machine-learning approaches are introduced and artificial neural networks are thoroughly investigated. By completion of the course, students are expected to be able to harvest big data sets from the internet and process by using different methods and tools.

BIG DATA CONCEPTS AND APPLICATIONS

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Reference Books & Course Materials

1. 01 Kamal, R., & Saxena, P. (2019). Big Data Analytics: Introduction to Hadoop, Spark, and Machine Learning (1st ed.). McGraw-Hill Education.

Learning Outcomes

1. L01 Explain the fundamental concepts, characteristics, and challenges of big data in real-world contexts. SOLO 4
2. L02 Describe the architecture and functions of big data ecosystem components, including Hadoop, HDFS, HBase, MapReduce, and YARN. SOLO 3
3. L03 Apply distributed computing methods to store, manage, and process large-scale structured and unstructured datasets. SOLO 3.5
4. L04 Implement data processing and analytics tasks using Spark and related big data tools. SOLO 4
5. L05 Analyze big data problems and select appropriate machine learning approaches, including classification, regression, and unsupervised learning techniques. SOLO 3.5
6. L06 Evaluate the suitability and scalability of different big data technologies for business and real-life applications. SOLO 5
7. L07 Visualize analytical results effectively for technical and non-technical audiences. SOLO 5
8. L08 Develop a data-driven solution by harvesting, processing, and interpreting large datasets while considering ethical, privacy, security, and data ownership issues. SOLO 5

Program Outcomes

1. Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems.
2. Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
3. Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose.
4. Ability to devise, select, and use modern techniques and tools needed for analysing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
5. Ability to design and conduct experiments, gather data, analyse and interpret results for investigating complex engineering problems or discipline specific research questions.
6. Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7. Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
8. Recognition of the need for lifelong learning ; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9. Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.
10. Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
11. Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.

Po-Lo Matrix