Major: Big Data Analytics (Büyük Veri Analitiği)
Program Overview
A cutting-edge, interdisciplinary program designed to train students in collecting, processing, analyzing, and interpreting large datasets to drive data-driven decision-making. Combines statistics, programming, machine learning, and business intelligence to prepare graduates for careers as data scientists, data analysts, business intelligence specialists, and big data engineers in Turkey’s rapidly growing tech and corporate sectors.
Key Learning Objectives
- Master data collection and preprocessing techniques.
- Learn statistical analysis and predictive modeling.
- Gain expertise in programming for data science (Python, R, SQL).
- Develop skills in machine learning and AI algorithms.
- Understand big data technologies (Hadoop, Spark, NoSQL).
- Explore data visualization and business intelligence (Tableau, Power BI).
- Apply data ethics, privacy, and compliance (GDPR, KVKK).
Core Courses
- Introduction to Big Data Analytics
- Overview of big data, its applications, and industry trends.
- Data Collection and Preprocessing
- Web scraping, APIs, ETL processes, and data cleaning.
- Statistical Analysis for Big Data
- Descriptive/inferential statistics, hypothesis testing, and regression analysis.
- Programming for Data Science
- Python (Pandas, NumPy, SciPy), R, and SQL.
- Machine Learning and AI
- Supervised/unsupervised learning, deep learning, and NLP.
- Big Data Technologies
- Hadoop, Spark, NoSQL databases (MongoDB, Cassandra), and cloud-based analytics.
- Data Visualization and Business Intelligence
- Tableau, Power BI, and D3.js for interactive dashboards.
- Data Ethics and Privacy
- GDPR, KVKK, bias mitigation, and responsible data use.
- Business Analytics and Decision-Making
- Predictive analytics, prescriptive analytics, and data-driven strategies.
- Capstone Project in Big Data Analytics
- Solve a real-world problem using big data tools and techniques.
- Practicum/Internship
- Hands-on experience with tech companies, financial institutions, or research labs.
Assessment Methods
- Data cleaning and preprocessing assignments
- Statistical analysis and machine learning projects
- Big data technology implementations (Hadoop, Spark)
- Data visualization and business intelligence reports
- Capstone project presentations
Tools & Resources
- Software: Python (Jupyter, TensorFlow, PyTorch), R, SQL, Hadoop, Spark, Tableau, Power BI
- Platforms: AWS, Google Cloud, Azure, GitHub
- Books:
- Big Data: Principles and Best Practices of Scalable Real-Time Data Systems by Nathan Marz
- Python for Data Analysis by Wes McKinney
- Data Science for Business by Foster Provost
Prerequisites
- Interest in data, programming, or analytics.
- Basic math and statistical knowledge helpful but not required.
Program Duration
2–4 years (associate/bachelor’s/master’s), including hands-on projects and internships.
Certifications (Optional)
- Google Data Analytics Professional Certificate
- Microsoft Certified: Azure Data Scientist Associate
- AWS Certified Data Analytics – Specialty
- Cloudera Certified Data Analyst
- Tableau Desktop Specialist
Career Paths
- Data Scientist (predictive modeling, AI, machine learning)
- Data Analyst (business intelligence, reporting)
- Big Data Engineer (Hadoop, Spark, data pipelines)
- Business Intelligence Specialist (dashboards, data visualization)
- Machine Learning Engineer (AI models, NLP, computer vision)
- Data Consultant (strategy, analytics, digital transformation)
- Research Analyst (academia, market research)
- Data Privacy Officer (compliance, ethics, GDPR)
Why This Major?
Turkey’s tech and business sectors are increasingly data-driven, creating high demand for skilled big data professionals who can turn raw data into actionable insights. This program provides hands-on training in cutting-edge tools and techniques, preparing graduates for high-impact, future-proof careers in a global and innovative field. With strong industry connections and certification prep, students gain a competitive edge in a lucrative and dynamic profession. Ideal for those passionate about technology, analytics, and problem-solving.
