Akademik Veri Yönetim Sistemi
The purpose of
the Introduction to Data Science course is to provide students with an in-depth
comprehension of the fundamental concepts, techniques, and tools used in the
field of data science. It covers a broad variety of topics, such as data
cleansing, shaping, and comprehension via exploratory data analysis,
descriptive statistics, and inferential data analysis. Students will learn
techniques for statistical analysis, pattern recognition, and data
representation, including linear and nonlinear models, hypothesis testing,
clustering, and dimensionality reduction. In addition, the course covers
big-data management, interactive visualizations, and advanced methods such as
machine learning, deep learning, and real-world prediction. Students will apply
their knowledge to data science assignments/projects and present their findings
throughout the course. Students will be endowed with the knowledge and skills
necessary to analyze, interpret, and extract valuable insights from large and
complex datasets while effectively managing data and utilizing advanced
modeling and prediction techniques by the end of the course.