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    BIG DATA ANALYTICS ASSOCIATE`S (SHORT CYCLE) DEGREE PROGRAMME

    Qualification Awarded
    Length of Programme (Year)
    Total Number of ECTS Credits
    Type of Education
    		 Level of Qualification & Field of Study


    Associate (Short Cycle) Degree

    2

    120

    Full Time
    • TQF Qualification Type: Associate Degree
    • TQF, TQF-HE, EQF-LLL, ISCED (2011): Level 5
    • QF-EHEA: Short Cycle
    • Yönelim: Vocational
    • Sınıflandırma (ISCED 2013):054,061 Temel Öğrenme Alanı:46,48,52
    • Kategori: Ana Yeterlilik

    PROGRAMME LEARNING OUTCOMES (PLOs)

    Programme Learning Outcomes (PLOs) are those describing the knowledge, skills and competencies that students are expected to attain and/or achieve upon successful completion of the programme. In this context, Programme Learning Outcomes defined for this programme are as follows:

    (Please click on the buttons below to reach the PLOs as “Conjoined” or as “Classified” under the “Knowledge”, “Skills” and “Competencies”.)

    (Program Learning Outcomes are given below according to the classification (knowledge, skills and competencies) used for the Turkish Higher Education Qualifications Framework (TYYÇ) level descriptors.)
    Knowledge (Described as Theoritical and/or Factual Knowledge.)
    Skills (Describe as Cognitive and/or Practical Skills.)
    1) It explains fundamental concepts in mathematics, statistics, and probability; and applies this knowledge to data analysis, modeling, and interpretation of results.
    3) It compares machine learning and data mining algorithms, selects the appropriate method, and applies it to real data.
    6) It analyzes different data sources, transforms them into meaningful outputs, and presents them using appropriate visualization tools.
    8) It develops optimization models and produces solutions for industrial and sectoral problems.
    Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)
    2) It explains the principles of algorithm design and develops software for solving problems using at least one programming language.
    4) Big data platforms utilize distributed systems and cloud computing architectures to perform data processing operations.
    5) They apply natural language processing techniques to text data and develop basic NLP-based applications.
    7) It creates data-driven decision models using decision support systems.
    9) In professional practice, we operate within the framework of ethical principles, data security, and social responsibility.
    10) They keep up with current technological developments in their field, actively participate in teamwork, and develop a lifelong learning awareness.
    11) With at least an A2 level of English proficiency according to the Common European Framework of Reference for Languages ​​(CEFR), they can communicate in writing and orally on topics related to their field.
    (Program Learning Outcomes are listed below.)
    1) It explains fundamental concepts in mathematics, statistics, and probability; and applies this knowledge to data analysis, modeling, and interpretation of results.
    2) It explains the principles of algorithm design and develops software for solving problems using at least one programming language.
    3) It compares machine learning and data mining algorithms, selects the appropriate method, and applies it to real data.
    4) Big data platforms utilize distributed systems and cloud computing architectures to perform data processing operations.
    5) They apply natural language processing techniques to text data and develop basic NLP-based applications.
    6) It analyzes different data sources, transforms them into meaningful outputs, and presents them using appropriate visualization tools.
    7) It creates data-driven decision models using decision support systems.
    8) It develops optimization models and produces solutions for industrial and sectoral problems.
    9) In professional practice, we operate within the framework of ethical principles, data security, and social responsibility.
    10) They keep up with current technological developments in their field, actively participate in teamwork, and develop a lifelong learning awareness.
    11) With at least an A2 level of English proficiency according to the Common European Framework of Reference for Languages ​​(CEFR), they can communicate in writing and orally on topics related to their field.