Curriculum of Aviation Logistics

Program Map
First Year First Semester Classes
Course Code Course Title Credit
DSC 703 Statistics with R Application 3
DSC 705 Mathematical Application with MATLAB 3
DSC 707 Analysis and Design of Algorithms 3
AVL 703 Production and Operations Management 3
AVL 705 Operations Research Methods 3
First Year Second Semester Classes
Course Code Course Title Credit
AVL 702 Supply Chain Management 3
AVL 704 Air Cargo Operations Management 3
AVL 712 Airport Operations and Management 3
ELEC I Elective Course I 3
ELEC II Elective Course II 3
Second Year First Semester Classes
Course Code Course Title Credit
AVL 700 Capstone Project 3
AVL 701 Master’s Thesis 6
Required Courses
In this course, Descriptive and Inferential Statistics, Measurement Scales, Visualizing data, frequency histograms, Measures for central tendency: mean, median, mode, Measures of variability: range, quartiles, standard deviation, skewness and variance, Data Visualization, Probability Methods, Discrete Probability Distributions, Continuous Probability Distributions, Distributions of Sample Statistics, Confidence Interval Estimation, Hypothesis Testing, Simple Linear Regression, Multiple Linear Regression and Analysis of Variance will be taught by using R programming applications.
Click for detail of course
This course focuses on the mathematical methods and models that are required to understand investigate models. Topics may include limits, sequences and series, set theory; univariate and multivariate calculus; matrix algebra and systems of linear equations; static and dynamic optimization; differential-difference equations and applications in models.
Click for detail of course
This course covers the main approaches to design and analysis of algorithms including important algorithms and data structures, and results in complexity and computability. The main content consists of Search and Sorting, Eid Al-Adha break, Divide and Conquer Algorithms, Graphs, Project Proposal, Dynamic Programming, Greedy Algorithms, Randomized Algorithms, P and NP, Work with NP Hard Problems, Partial Recursive function, Computations and Unsolvable Problems.
Click for detail of course
This course covers the main approaches to design and analysis of algorithms including important algorithms and data structures, and results in complexity and computability. The main content consists of Search and Sorting, Eid Al-Adha break, Divide and Conquer Algorithms, Graphs, Project Proposal, Dynamic Programming, Greedy Algorithms, Randomized Algorithms, P and NP, Work with NP Hard Problems, Partial Recursive function, Computations and Unsolvable Problems.
Click for detail of course
Course themes include strategic impact of operations management; global trends/practices in operations management; product/service design and development; design of production and work systems; total quality management; supply chain management.
Click for detail of course
In comparison with the air passenger sector, air cargo is a more complex industry because of the uncertainty and complexity in forecasting that the industry involves. In order to clarify the characteristics of air cargo operations, in this course, air cargo market characteristics, economic and technical regulation, passenger and freight airlines, integrated carriers, Post Offices and forwarders, air cargo alliances and mergers, aircraft and flight operations, airport and ground operations/ ground handling and IT systems for cargo processing, distribution and marketing, pricing and revenues, airline costs will be covered.
Click for detail of course
In this course, formulating, analyzing, and solving mathematical models that represent real-world problems will be examined. For the purpose of enabling good decision making in supply chain, business analysis in Excel, linear and integer programming, network flow problems, optimization problems will be provided and as an optimization software GAMS will be used.
Click for detail of course
The course will provide students extensive knowledge of airport elements and their interrelations, assessment of capacities of airport elements, airport operations related to aviation logistics. Airport Physical and Technical Characteristics, Physical Characteristics of Passenger and Cargo Terminals, Types of Cargo and Special Handling Requirements, Airport Operations, Airport and Airline Relations, Air Cargo and Airport Long-term Strategic planning are main themes that will be covered in this course.
Click for detail of course
Elective Courses in Business Analytics
The course focuses on detailed understanding of accounting information system, accounting concepts, accounting principles, accounting cycle, recording of transactions and financial statement concepts.
Click for detail of course
The objective of the course is to make students to learn and enhance “information gathering activity” that is intended to guide strategic and/or operational marketing decisions. The topics included are: target markets, competitive strategies, product, price, place (distribution) or promotion, the nature and scope of marketing research and its role in decision support systems.
Click for detail of course
Elective Courses in Aviation Logistic
This course aims students to understand the specific characteristics of the transportation systems for freight transportation. All major techniques in the areas of unimodal and multimodal transportation modes, the increasing use of intermodal transport and the development in information technology and global transportation planing will be discussed discussed.
Click for detail of course
This course provides students with the knowledge of introducing the industry and its stakeholders, marketing and sales in air cargo, e-opportunities for air cargo initiatives, i.e. technological aspect for air cargo revenue management. Furthermore, the operation and management side of air cargo revenue management will be analyzed in order to make decisions about the optimal pricing and capacity in the air cargo industry.
Click for detail of course
This course covers the topics of management of one of the main element of aviation, namely airlines In this course, the airline types, management style and organization structures, airline economics from the perspective of pricing, revenue and cost structures, and planning processes, alliances and networks and usage of IT in airline operations will be given.
Click for detail of course
This course is intended to give a point of view about the concepts and importance of economics of the air transportation. The course content includes the following subjects in a master degree level: air transportation demand and supply, international economics of aviation, airline business models, airlines network, air cargo economics, liberalization in aviation industry. The detailed course outline is given in the tentative course outline part of the syllabus.
Click for detail of course
Elective Courses in Data Science
This course covers the statistical tools needed to understand empirical research and to plan and execute independent research projects. Topics include statistical inference, regression, dimension reduction, data clustering, similarity, neighbours and machine learning and evaluation of policies and programs.
Click for detail of course
The course content includes statistical inference in nonlinear models, nonlinearity in regression, dimension reduction, data clustering, similarity, neighbours and homogeneity/heterogeneity and evaluation of policies and programs. Students will learn the principles and best practices for how to use big data in order to support fact-based decision-making. Emphasis will be given to applications in various data which has nonlinearity in big data.
Click for detail of course
Topics may include essentials of stochastic integrals and stochastic differential equations. Probability distributions and heavy tails, ordering of risks, aggregate claim amount distributions, risk processes, renewal processes and random walks, markov chains, continuous Markov models, martingale techniques and Brownian motion, point processes, diffusion models, and applications in various subject related data science.
Click for detail of course
This course covers machine learning and statistical pattern recognition. Topics include: supervised learning, unsupervised learning, learning theory; reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing and evaluation of policies and programs.
Click for detail of course
This course provides an understanding of the application of software technologies that enables users to make better and faster decisions based on various data. This course covers the statistical tools needed to understand empirical research and to plan and execute independent research projects. Topics include statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of policies and programs.
Click for detail of course
This course covers the degree develops practical workplace competencies that meet current and future challenges through a real world coursework utilizing personalized academic mentoring and tutoring. The coursework focuses on introduction level of multivariate statistics, factor analysis, principal component analysis, period-grams, state space, frequency domain, Fourier function, functional regression analysis, bootstrapping and asymptotic theory of tests and estimators.
Click for detail of course