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KF7032 Big Data and Cloud Computing
Task:
Learning Outcomes:
The learning outcomes (LOs) for this module are:
LO1 Apply big data analytic algorithms, including those for visualization and cloud computing techniques to multi-terabyte datasets.
LO2 Critically assess data analytic and machine learning algorithms to identify those that satisfy given big data problem requirements.
LO3 Critically evaluate and select appropriate big data analytic algorithms to solve a given problem, considering the processing time available and other aspects of the problem.
LO4 Design and develop advanced big data applications that integrate with third party cloud computing services.
LO5 Critically assess and interpret primary research to identify its applicability to a given big data problem scenario.
Training Tasks
Training Task 1: Peer Reviewed Task (4%)
The objective of this task is to ensure that students have mastered these skills which are required for final module assessment:
1. Process a data set using the recommended software environment for the module.
2. Explaining the logical reasoning behind your code.
1. You will create a Jupyter notebook based the scenario below (which is derived from the first 6 weekly worksheets) explaining your code using Markdown cells (i.e., formatted text, not just comments) in the notebook.
2. You will post your notebook to the module Blackboard discussion.
3. You will then peer review the submission preceding yours on the discussion board, and the one following it, using the marking scheme below and post these mark sheets following those submissions.
4. There are two marks for a fully working submission, or one mark for a non-working or incomplete notebook, and one mark per completed review.
KF7032 Big Data and Cloud Computing
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