Data Analytics in Nanoscience detail syllabus for Nanoelectronics (Nano), 2017 scheme is taken from VTU official website and presented for VTU students. The course code (17NT741), and for exam duration, Teaching Hr/week, Practical Hr/week, Total Marks, internal marks, theory marks, duration and credits do visit complete sem subjects post given below.
For all other nano 7th sem syllabus for be 2017 scheme vtu you can visit Nano 7th Sem syllabus for BE 2017 Scheme VTU Subjects. For all other Professional Elective-III subjects do refer to Professional Elective-III. The detail syllabus for data analytics in nanoscience is as follows.
Course Objectives:
- To understand the basics of big data analytics, methods and tools that data scientists use
- To learn the concepts, principles and practical applications of data analytics in nanotechnology
- To learn the method and procedures of using open source software for big data analytics
Module 1:
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Module 2:
DATA ANALYTICS LIFECYCLE Life cycle, discovery, data preparation, model planning, model building, communicate results, operationalize, global innovation networks and analysis, discovery
Module 3:
DATA ANALYTIC METHOD USING R Introduction to R, exploratory data analysis, statistical methods for evaluation.
Module 4:
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Module 5:
CONVERGENCE OF NANOTECHNOLOGY AND BIG DATA ANALYSIS Big Data; biosensors; computer-aided diagnosis; data analysis; data visualization; healthcare; nanotechnology
Course Outcomes:
After successfully completing this course, students will be able to:
- Understand the fundamentals of data analytics and big data
- Develop structured lifecycle approach to data analytics problems
- Apply appropriate analytic technique and tools to analyse big data in nanotechnology
Graduate Attributes (as per NBA):
- Engineering Knowledge.
- Problem Analysis.
- Design / development of solutions (partly).
- Interpretation of data.
Question paper pattern:
- The question paper will have ten questions.
- Each full Question consisting of 20 marks
- There will be 2 full questions (with a maximum of four sub questions) from each module.
- Each full question will have sub questions covering all the topics under a module.
- The students will have to answer 5 full questions, selecting one full question from each module.
Text Books:
- Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data, EMC Education Services, 2015. (http://as.wiley.com/WileyCDA/WileyTitle/productCd-111887613X.html)
- Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data, EMC Education Services, 2015. (http://as.wiley.com/WileyCDA/WileyTitle/productCd-111887613X.html.
- Rodrigues JF, Paulovich FV, de Oliveira MC, de Oliveira ON, On the convergence of nanotechnology and Big Data analysis for computer-aided diagnosis, Nanomedicine (Lond). 2016 Apr;11(8):959-82. doi: 10.2217/nnm.16.35. Epub 2016 Mar 16 (https://www.ncbi.nlm.nih.gov/pubmed/2697966)
Reference Books:
- Ramona Nelson, Nancy Staggers, Health Informatics – E-Book: An Interprofessional Approach, Elsevier, 2014
For detail syllabus of all other subjects of BE Nano, 2017 regulation do visit Nano 7th Sem syllabus for 2017 Regulation.
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