Data Science and Analytics 2025 Base Scores and Rankings

The Data Science and Analytics Program is an interdisciplinary engineering field designed to analyze large datasets, extract meaningful insights from them, and use this information in strategic decision-making processes. In this program, students receive comprehensive training in data collection, processing, analysis, and building predictive models using this data.

Students in the Data Science and Analytics program gain knowledge in areas such as statistics, data mining, machine learning, artificial intelligence, programming, data visualization, and big data technologies. Additionally, topics like data security and ethics are also part of this education.

Graduates in this field can work in roles such as data analyst, data scientist, business analyst, or machine learning engineer across various sectors, including banking, healthcare, e-commerce, telecommunications, and manufacturing.

The Data Science and Analytics program is ideal for students who enjoy working with data, possess strong analytical thinking skills, and excel in problem-solving.

Data scientists work with datasets to develop strategies that optimize business operations. Their tasks include collecting data from various sources, pre-processing data, analyzing data, and reporting the results. Data scientists also use techniques like machine learning, artificial intelligence, and data mining to discover patterns and relationships in the data. The responsibilities of a data scientist include:

1. Engaging in data mining
2. Cleaning data using programming languages (e.g., Python or R)
3. Conducting statistical analysis using machine learning algorithms
4. Developing and training machine learning models using programming and automation techniques
5. Building big data infrastructures using tools like Hadoop and Spark
6. Developing deep learning frameworks
7. Creating architectures capable of managing large amounts of data
8. Exploring future trends and developing predictive models

Data scientists need to know tools that help them manage large amounts of data more easily. Here are some of the tools commonly used by data scientists:

• Programming: Python, SQL, Scala, Java, R, MATLAB
• Machine Learning: Natural Language Processing, Classification, Clustering, Ensemble Methods, Deep Learning
• Data Visualization: Tableau, SAS, D3.js, Python, Java, R libraries
• Big Data Platforms: MongoDB, Oracle, Microsoft Azure
• Data Warehousing: Informatica/Talend, AWS Redshift

Data Science Engineering offers a wide range of job opportunities. Graduates can take on data-driven roles in various sectors. Here are some career opportunities in Data Science Engineering:

• Data Scientist: Professionals who analyze data, create models, and extract meaningful insights from this data to shape business strategies. They can work in various sectors, particularly in finance, healthcare, e-commerce, and technology.
• Data Analyst: Involved in the collection, processing, and analysis of data. They prepare reports and visualizations that assist businesses in their decision-making processes.
• Machine Learning Engineer: Develops algorithms and models that learn from data. By applying these models, they can make predictions and create automated decision systems.
• Big Data Engineer: Develops infrastructures and systems capable of processing large datasets. This role involves designing scalable solutions for storing, processing, and analyzing data.
• Business Intelligence Specialist: Provides insights to improve business performance by analyzing data. They create reports and visualizations to present the necessary data for strategic decisions to upper management.
• Data Engineer: Builds and manages the data infrastructures necessary for data collection, storage, and accessibility. This process includes tasks like cleaning, transforming, and organizing data.
• AI Specialist: Develops artificial intelligence algorithms and models and integrates these technologies into business processes. They can work particularly in automation and data analytics.

The Data Science and Analytics program is a newly established program in Turkey. To be eligible for this program, students must take both the Basic Proficiency Test (TYT) and the Field Proficiency Test (AYT). This program is a bachelor's degree that can be chosen based on a numerical score type.

For the minimum scores and rankings of the Data Science and Analytics program, you should check the results of 2024. For example, the last student admitted to the Data Science and Analytics program at Manisa Celal Bayar University in 2024 had a score of 340.46037 and a ranking of 164,822. The last student admitted to the Data Science and Analytics program at Istanbul Technical University in 2024 had a score of 504.33451 and a ranking of 8,932.