Module 6 Overview & Assignment ExpectationsFocus Module 6 examines how AI and IoT converge to enhance industrial operations, building on AI/ML in healthcare (Module 5), big data tools (Module 3), and cloud foundations (Module 1). Key themes: predictive capabilities, real-time monitoring, reduced downtime, and data-driven optimization in manufacturing, logistics, energy, etc.Assignment Details (6-2 Assignment: AI […]

Module 5 Overview & Assignment ExpectationsFocus Module 5 explores emerging technologies like AI, machine learning (ML), and IoT, with the assignment centering on how AI/ML transforms a specific industry context (healthcare is the most common choice). It builds on prior modules by linking AI/ML to big data processing (Module 3), cloud scalability (Module 1–2), and […]

Project One Overview & ExpectationsAssignment Title Variations (from student docs): Cloud Computing Evaluation Paper Feasibility Proposal on Cloud Computing Models Exploring Cloud Computing & Big Data Challenges Key Requirements (based on templates and examples): 6–10 pages (including cover, sections, references). Structured sections: Introduction, Cloud Computing Overview (deployment & service models), Benefits & Drawbacks, Risks/Challenges, Big […]

Module 4 Overview & Discussion Expectations Focus Module 4 explores data storage and management in big data environments, contrasting traditional relational (SQL) databases with non-relational (NoSQL) systems. It ties into previous modules by showing how databases support big data tools (Module 3) in cloud-migrated setups (Module 2).Assignment Details (4-2 Discussion) Prompt (typical): “What are the […]

Module 3 Overview & Assignment Expectations Focus Module 3 introduces core big data concepts (from Big Data, Big Analytics Chapters 1–3) and examines tools that process, store, query, and analyze large-scale data. It builds on Module 1 (cloud) and Module 2 (migration) by exploring technologies that leverage cloud environments for big data workloads.Assignment Details (3-2 […]