The Big Data Analyst Associate Degree Program aims to provide students with a comprehensive education in data analysis and big data management. The academic content and curriculum of the program includes a variety of courses and practices that aim to provide students with both theoretical knowledge and practical skills.
The first year of the program aims to provide a solid foundation in basic computer science and data analysis. The courses of the first year are usually as follows:
Computer Programming: Students are taught the basics of programming languages. Commonly used languages for data analysis such as Python and R are emphasized. Students learn basic programming concepts, data structures and algorithms.
Database Management Systems (SQL): Database management and working with databases using SQL (Structured Query Language) are covered. Students gain competence in database design, data manipulation and data querying.
Statistics and Probability Theory: This course covers statistical methods and probability theory necessary for data analysis. Students learn statistical techniques and concepts necessary for data analysis.
Data Structures and Algorithms: Develop the ability to understand and use data structures and algorithms. This course is critical for data analysis and programming.
The second year focuses on more advanced and specific topics. The courses of the second year are usually the following:
Big Data Technologies: Big data processing platforms and technologies such as Hadoop, Spark are taught. This course teaches you how to manage and process large data sets.
Machine Learning: Students are introduced to machine learning algorithms and techniques. Basic machine learning topics such as supervised and unsupervised learning, classification, regression, clustering are covered.
Data Visualization: Data visualization techniques and tools are emphasized. Students learn to visualize data sets in a meaningful and effective way. Popular visualization tools such as Tableau, Power BI are used.
Advanced Data Analysis: This course introduces students to more complex data analysis methods. Advanced topics such as time series analysis, text mining and data integration are covered.
Various elective courses and projects are also offered throughout the program. Elective courses allow students to learn about more specific topics according to their interests. For example, courses on natural language processing, social media analytics or business intelligence can be taken.
The teaching materials and methods used in the educational process aim to provide students with both theoretical and practical knowledge. The courses are often hands-on, involving laboratory work, projects and group work. Work on real-world data sets allows students to apply what they have learned in practice.
The Big Data Analyst Associate Degree Program provides a comprehensive and practical education in data analysis and big data management, enabling students to specialize in this field and succeed in business life. The curriculum of the program is constantly updated according to the requirements of modern data analysis and big data technologies and aims to provide students with the most up-to-date knowledge and skills.