Course Outcome
CO1: Analyze performance trade-offs of large-scale data systems and evaluate distributed computing models for big data applications.
CO2: Design and evaluate distributed storage solutions using distributed file systems and NoSQL databases considering scalability, fault tolerance, and query performance.
CO3: Apply data processing techniques to implement scalable data analytics workflows and performance evaluation.
CO4: Design real-time data analytics pipelines for high-velocity data.
CO5: Implement scalable machine learning algorithms and analytical models for large-scale datasets.
CO6: Design and implement interactive visualization systems and analytical dashboards for extracting actionable insights from large-scale datasets.
Course Content: Download Syllabus
Teaching and Examination Scheme
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