Unit 1 Big Data Management Unit 2 Large Scale Data Services Unit 3 Cloud Innovations Unit 4 Big Data & Society Unit 5 Project & Development Personnel Foundations of Big Data Systems Gain a deep understanding of big data characteristics, distributed storage, and the architecture powering modern data platforms. Cloud Deployment & Programming Master public, private, and hybrid cloud environments while building scalable applications using Scala. Big Data in Practice Develop hands-on skills in Hadoop, Spark, and workflows for managing and transforming large data sets. Learning Outcomes Module Summary Duration: 4-6 weeks By completing big data management, you will:Critically evaluate big data design principles, distributed storage, and reliability trade-offs.Demonstrate cloud deployment models and develop scalable data-intensive apps in Scala.Execute data operations and workflows in Hadoop and Spark for large-scale analysis. Cloud Service Platforms Explore major services like AWS, Azure, and GCP for data architecture and resource optimization. Machine Learning for Data Engineering Integrate AI, machine learning, and deep learning into engineering workflows for scalable solutions. Data Pipeline Development Design ETL and ELT pipelines, leveraging modern tools for flexible, scalable data flows. Learning Outcomes Module Summary Duration: 4-6 weeks By completing large scale data services modules, you will:Critically deploy and optimize cloud-based data services.Apply ML/DL algorithms for structured and unstructured data.Build robust, efficient data pipelines for real-world projects. Project Lifecycle Management Plan, manage, and adapt full-cycle data engineering projects from business case to delivery. NoSQL Database Systems Develop expertise in MongoDB, Redis, Zookeeper and apply NoSQL models for distributed, flexible data storage. Data Governance & Compliance Learn frameworks, policies, and controls for organizational data quality and regulatory compliance. Learning Outcomes Module Summary Duration: 4-6 weeks By completing cloud innovations modules, you will:Execute and document full data project lifecycles and business-aligned solutions.Critically evaluate NoSQL architectures for diverse data types.Design and audit data governance strategies in real environments. Data Security Practices Evaluate threats and design security strategies, including cryptographic and blockchain-based solutions. Green and Sustainable Computing Analyze energy consumption in data centers and implement sustainable, resource-efficient engineering. Ethical Data Practices Address fundamental ethical issues—privacy, accountability, and fairness—in data-driven solutions and AI. Learning Outcomes Module Summary Duration: 4-6 weeks By completing big data and society modules, you will:Assess risks, threats, and apply security best practices for cloud data.Design and implement energy-efficient, sustainable data solutions.Create responsible, transparent systems that address data ethics. Capstone Master Thesis Plan and deliver an independent project that synthesizes all program domains, solving a real data engineering challenge. Industry Collaboration Work directly with stakeholders or on advanced research to propose, implement, and evaluate robust data solutions. Review & Presentation Compile findings into a professional paper and presentation for technical/non-technical audiences. Learning Outcomes Module Summary Duration: 4-6 weeks By completing big data and society modules, you will:Analyze complex business problems and design scalable data solutions.Evaluate performance and impact of engineering solutions.Communicate technical decisions and outcomes confidently to varied stakeholders.
