There are active studies in areas such as machine learning and deep learning in collaboration with five universities that are Stanford and Carnegie Mellon Universities from USA, Manchester and Birmingham Universities from UK. ITU Artificial Intelligence and Data Engineering program has been established with the aim of taking place in the international academic ranking with its staff doing academic studies with these universities and joint working disciplines.

Assoc. Prof. Dr. Gülşen Cebiroğlu Eryiğit who is co-founder of Department of Artificial and Data Engineering works on Natural Language Processing. Prof. Dr. Gözde Ünal who cooperates with competent companies in their fields such as Siemens, Aygaz, Migros and Farplas works on deep learning. Assoc. Prof. Dr. Altan Çakır from the Department of Physics Engineering, who is a prominent researcher in the field of detector electronics, works on big data and statistical learning. Assoc. Prof. Dr. Berk Canberk who is also the director of ITU Artificial Intelligence and Data Science Application and Research Center conducts wireless energy and data transfer studies for the first time in the world for new generation Wi-Fi networks.

Together with the Faculty of Computer and Informatics Engineering, eleven faculties of ITU has been selected as the most successful university by QS in the area based world university rankings. In addition, for the last five years, ITU ranked first among the universities in Turkey with a total of 936 references to publications in the field of artificial intelligence according to Web of Science database. There are many academicians in ITU as well as in Faculty of Computer and Informatics Engineering who have broken new grounds in their field in national area. In addition, Faculty of Computer and Informatics Engineering cooperates with other academic units in different projects such as optimization and modeling of unmanned aerial vehicles, analysis of satellite images and other data based on deep neural networks, game design, digitization of agriculture (ITU-TARBIL) and forest information system (ORBIS).

Data engineering is an interdisciplinary engineering branch that selects, collects, stores, processes and presents the data to the required locations. The main tasks of data engineers in a system are to develop, install, test and maintain databases and data processing systems for big data. From human history until 2003, up to 5 Exabytes of data were produced all over the world. Nowadays, so much data is produced in just two days, and this amount is increasing day by day. For this reason, data mining and data communication are gaining importance day by day.

The curriculum includes courses on basic sciences (physics, chemistry, biology), mathematics, data science, artificial intelligence theory and other courses on computer science such as formal methods or automata. In addition to the compulsory courses, technical elective courses for artificial intelligence and data engineering are included in the curriculum. Some of these courses are practice based.

The program has a quota of 40 people for the 2020-2021 academic year. The program quota is limited to 40 in order to provide the highest quality education in all programs carried out in all departments within the faculty, taking into account the opportunities of the Faculty of Computer and Informatics, classrooms and laboratory infrastructures. It is expected to increase the quota in the following years.

In the field of Natural Language and Processing, there are many studies being carried out such as Turkish personal assistant applications in smart devices, separation of sentences, automotive support channels dialogue system, targeted emotion analysis in the field of telecom, extraction of information through noisy banking texts, text analysis on banking dialogue systems and legal documents. In education, there are many international projects including artificial intelligence technology studies, including centers such as NEWTON in the UK, and new generation wireless communication, drone communication, artificial intelligence-based 5G systems and autonomous aircraft. There is also a study on how Artificial Intelligence can be teached to the middle and high school students to prepare future generations. In addition, there are many international studies such as a software-based communication project with the University of Northeastern through the United States National Science Foundation.

Natural Language Processing, Computer Vision, Robotics, Recommendetion Systems, Big Data Analytics, Data Communication Networks, Reinforcement Learning, Algorithms and Theory of Computation, Game Technologies and Bioinformatics are some sub-disciplines of artificial intelligence.

They will be able to analyze the data from a critical perspective and apply mathematical models and artificial intelligence techniques to a specific problem. In addition, they will be able to evaluate problems abstractly, visualize and present analytical results. They will also specialize in ensuring data reliability in a designed system.

Companies such as Google, Amazon, Microsoft, Tesla and Uber continue their work in many areas such as machine learning, automatic navigation and guidance, transportation, logistics, strategic and military planning. In addition to these, some of the most well-known applications are IBM's Deep Blue chess application that beat Kasparov,  IBM Watson, Alpho-Go developed for Go game, Blue Brain Project conducting researches on the human brain, TurboTax finance application, Grammarly and Textio that are text editing applications, Webex that is simulatenous translation video conferencing application, Apple's Siri and Amazon's Alexa as virtual assistants, and self-driving cars. Moreover, start-up and R&D companies have come to the fore in the field of Artificial Intelligence recently. For example, SymphonyRM, Cinnamon and LogiNext are some of the outstanding start-ups in 2019 in data analysis, marketing and logistics.

Department of Artificial Intelligence and Data Engineering will be close in coorpoeration with ITU Artificial Intelligence and Data Science Application and Research Center and ITU ARI Teknokent. With its ecosystem consisting of ITU CEKIRDER, ITU MAGNET, INNOGATE, and ITUNOVA TTO, ITU ARI Teknokent  containing more than 290 R&D companies having more than 7000 personnel has developed more than 600 projects in a year  reaching a total turnover of 1 billion dollars. This ecosystem enables students to be one step ahead both during and after their education by offering many opportunities such as internship, part/full time job opportunities, seminars, trainings and conferences, entrepreneurship, company establishment, technology development activities and project cooperation. Artificial Intelligence and Data Science Application and Research Center was established in 2018 in order to build information capacity in artificial intelligence and data science, to conduct innovative researches and to develop advanced methods and technologies in this field. Thanks to its members cooperating with leading national and international institutions such as NASA, Boeing, General Electric and Turkish Airlines, it has a unique theoretical and sectoral experience.

In order to graduate from the program, students must take 135 credits (239 ECTS), and their gpa must be at least 2.0 in accordance with the Undergraduate Education and Training Regulation of Istanbul Technical University. In addition, based on the University Internship General Principles, there is a total of 40 working days internship requirements for program students.

The program aims to provide a strong ecosystem where new artificial intelligence and data science algorithms will be developed and to improve research infrastructure facilities. It aims to support industrial institutions and academic institutions by graduating students who can produce solutions and products based on advanced artificial intelligence and data engineering techniques for the needs of society, country institutions and industrial sector. With our comprehensive curriculum, it is aimed to train Artificial Intelligence and Data Engineers who will have scientific and technological background to follow rapidly developing technologies in international level. It is also envisaged to increase the global competitiveness of industrial R&D studies.

Artificial Intelligence causes radical changes in society, technology, science, business and many more areas in the 21st century. The estimates are that this technology will contribute $15.7 trillion to the global economy by 2030, and that global gross domestic product will increase by 14% and replace 30% of global employment. The high increase in the volume of data collected recently, the need to interpret this data, the fact that internet and digital platforms have become important and even major platforms in the daily life flow of societies, and autonomous systems starting to evolve with intelligent algorithms have made artificial intelligence one of the most important high-techs areas of today and the future. In addition, the fact that artificial intelligence had a critical a role in sectors such as health, energy, finance and agriculture, which are vital for society, emphasizes the importance of this field.

Artificial Intelligence and Data Engineering are two disciplines that feed on each other. Today, a great amount of data is collected and analyzed in areas such as transportation, entertainment, home and service robots, education, security, finance, trade and health, for developing artificial intelligence systems that is involved in daily life. Artificial Intelligence techniques are used to analyze the data, while artificial intelligence technologies are developed based on analysis results. For example, in some personal applications on smart devices, the text-based data are processed to analyze the user's word selections and spelling errors are detected. These errors are corrected based on the analyzed user inputs using Natural Language Processing techniques, one of the sub-branches of artificial intelligence.In this way, the user is provided with a personalized experience.

Graduated students can continue their academic studies at universities, high-tech institutes, or research centers. Moreover, they will be able to be employed in data analysis, decision support or information technology departments of either national or international organizations operating in different fields such as informatics, finance, banking, healthcare, education services or energy. Because of the rapidly increasing demands in recent years, there are employment opportunities in many positions such as machine learning engineer, business intelligence expert, developer, software architect, data analyst, data warehouse engineer, frontend developer, product manager and so on.

Artificial Intelligence is oriented on the development and application of computing technologies, inspired by humans learning, reasoning and decision making. It is a developing discipline in order to model physical systems and data in many fields such as energy, defense, education and finance, for extracting knowledge from data, for analyzing, predicting, decision making and planning. For this reason, it has a very flexible usage area with increasing interest on a global scale. At the same time, the need and deficit of data science, data engineer and artificial intelligence engineer have emerged in many sectors in our country.

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ITUNOVA consults many well-known banking, telecom, automotive and law companies such as Ericsson, Huawei, Turkcell, Vodafone, İşbank, Softtech, Yapı Kredi Teknoloji, Akbank, Denizbank, Intertech, Doğuş Teknoloji and GSI Hukuk. In addition, many information technology companies in ITU ARI Teknokent are developing projects using state of art projects artificial intelligence and data science methods. Besides, there are other units in ITU ecosystem such as ITU TARBIL (Agricultural Information and Monitoring System) and ITU UHUZAM (Research Center for Satellite Communications and Remote Sensing) actively using artificial intelligence methods in their projects.

English is the language of instruction. There will be language training before the program for students who do not meet the language proficiency requirements (TOEFL, IBT = 79).