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Unleash the power of data and drive insightful decisions. This Data Science track provides a comprehensive journey through machine learning, statistical analysis, and data visualization. Master Python's powerful libraries for EDA, model building, and model optimization. Dive deep into complex supervised and unsupervised learning algorithms, and learn to evaluate and improve their performance. Equip yourself with MLOps skills to build and deploy robust ML models.

Build scalable data pipelines and architecture. In the Data Engineering track, master the use of advanced SQL, cloud-based databases, and big data processing techniques. Gain in-depth knowledge of popular tools and frameworks for batch and real-time data processing. Understand how to design and implement ETL processes and handle data ingestion, storage, and retrieval efficiently and effectively.

Transform raw data into actionable insights. The Data Analytics track equips you with in-depth knowledge of data cleaning, data analysis, and data visualization. Gain hands-on experience with Excel, SQL, and Business Intelligence tools. Learn how to handle large datasets, extract meaningful insights from them, and effectively communicate these insights. Dive into advanced EDA and statistical concepts to enhance your data analysis skills.

Efficiently store, retrieve, and manage data. In the Data Management track, you'll learn SQL's power for data manipulation, aggregation, and querying. Understand relational databases, NoSQL databases, and the use of cloud databases in handling big data. This track equips you with the skills needed to effectively manage data and ensure its availability, reliability, and security.