Data Visualization and Analysis (IE 451)

2019 Fall
Faculty of Engineering and Natural Sciences
Industrial Engineering(IE)
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Kemal Kılıç,
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Formal lecture,Interactive lecture
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Introduction to styles of data analysis techniques and information visualization; Histograms, stem and leaf diagrams, boxplots, quantile plots; assessing distributional assumptions about data; Plotting high- dimensional data with special emphasis on parallel coordinate plots, scatter matrices, star glyphs, treemaps; Class project with real-world data-set provided by the instructor or developing information visualization software program.


The course will address unsupervised learning, supervised learning, association rule mining and feature subset selection problems and introduce various techniques proposed as solutions and present their implementation particularly in the context of operations management. Data Visualization will also be introduced as part of the curriculum.
Among others, probabilistic and statistical methods, clustering algorithms, classification algorithms, multiple linear regression, a priori algorithm, metaheuristics (such as genetic algorithms, simulated annealing, etc.) in the context of feature subset selection will be covered as part of the toolbox that are widely utilized in data mining.


Apply the basic concepts of existing methodologies for data visualization and analysis, as well as machine learning

Model and interpret data, by applying statistics, information visualization, and machine learning techniques.
Extract and clean data from diverse domains
Explore data through visualizations
Conduct challenging technical projects that involve intense data analysis and interpretation.
Apply their knowledge on the best-practices in the real world, regarding the application of theory.
Work independently, as well as in a team, in completing challenging data analysis projects.


1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 1

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 5

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 4

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 4

1. Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 5

2. Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 4

4. Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 3

5. Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 4

6. Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 3

7. Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 3

1. Demonstrate an understanding of economics, and main functional areas of management. 1

2. Assess the impact of the economic, social, and political environment from a global, national and regional level. 1

1. Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 5

2. Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 3

3. Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 5

1. Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 2

2. Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 2

3. Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 4

1. Pursue open minded inquiry and appreciate the importance of research as an input into management practice. 2

2. Know how to access, interpret and analyze data and information and use them to make informed decisions. 5

3. Work effectively in environments characterized by people of diverse educational, social and cultural backgrounds. 3

4. Identify, select, and justify strategies and courses of action at the divisional, business, and corporate levels of analysis and to develop effective plans for the implementation of selected strategies. 2

1. Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 5

2. Demonstrate knowledge of discrete mathematics and data structures. 3

3. Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 5


  Percentage (%)
Final 30
Midterm 50
Assignment 20



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