Internship Practices and Sectoral Experience

As the Data Science and Analytics Program of Kamil Özdağ Faculty of Science, we place great importance on enabling our students to reinforce their academic knowledge with real-world experience. In this regard, two mandatory internships constitute an integral component of the undergraduate curriculum. Each internship requires a minimum of 20 working days, completing a total of 40 working days. These internships aim to enhance students’ practical competencies in the fields of data science and data engineering through participation in different organizations, institutional structures, and project environments.

Competencies Targeted in Internships:

During the internship period, students are expected to:

In the first internship, gain competencies in data science such as developing machine learning and deep learning algorithms, performing data preprocessing tasks, creating artificial intelligence–based solutions, and designing analytical dashboards.

In the second internship, acquire data engineering skills including the design of data pipelines, the use of modern data storage technologies, and the development of large-scale data infrastructures.

With the preliminary approval of the departmental internship committee, students may also complete both internships within the same institution, provided that they work in different departments, undertake distinct projects, and are supervised by different mentors. For the internship to be considered valid, each internship must consist of 20 uninterrupted working days; extra days completed in one internship cannot be transferred to compensate for the duration of the other.

Internship Process and Evaluation:

Although internships are primarily carried out during the summer term, students with at least three full weekdays available may undertake their internship during the academic semester as well. Students who complete their internship within the semester are required to contact the departmental internship committee at the end of their internship to initiate the evaluation procedure. Upon completion of each internship, a detailed internship report prepared in the prescribed format and an official evaluation form obtained from the host institution will constitute the primary criteria for assessing student performance and learning outcomes.

Internship Placement Options and Support Mechanisms:

Students may undertake internships at public institutions, private sector organizations, research centers, and technology companies that meet the minimum criteria established by our department. To promote the enhancement of sectoral experience, private sector internships are supported through platforms such as the National Internship Program coordinated by the Presidential Human Resources Office. Our department further aims to provide internship opportunities by developing collaborations with various industry partners.

Students may also secure their own internship placements. In such cases, the field of activity and the content of the internship must align with the learning objectives of the program and be approved by the Departmental Internship Committee. University–industry collaborations, technoparks, and data science–oriented R&D centers are among the potential internship environments. This process contributes to the development of our students as competent professionals in the field of data science and analytics by enabling them to integrate theoretical knowledge with practical application.