Introduction To Data Analytics detailed syllabus scheme for Computer Engineering (CE), 2017-18 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.
For 5th Sem Scheme of Computer Engineering (CE), 2017-18 Onwards, do visit CE 5th Sem Scheme, 2017-18 Onwards. For the Elective-IV scheme of 5th Sem 2017-18 onwards, refer to CE 5th Sem Elective-IV Scheme 2017-18 Onwards. The detail syllabus for introduction to data analytics is as follows.
Introduction To Data Analytics Syllabus for Computer Engineering (CE) 3rd Year 5th Sem 2017-18 DBATU
Course Objectives and Outcomes:
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Detailed Contents:
Descriptive Statistics:
Ensemble Methods: Random Forest, Neural Networks, Deep learning.
Creating data for analytics through designed experiments, Creating data for analytics through Active learning, Creating data for analytics through Reinforcement learning.
Reference Book:
- Michael Milton, Head First Data Analysis A learner’s guide to big numbers, statistics, and good decisions, O’Reilly Media.
- Hastie, Trevor, et al., The elements of statistical learning. Vol. 2 . No . 1 , New York: Springer.
- Montgomery, Douglas C., and George C. Runger, Applied statistics and probability for engineers, John Wiley and Sons.
- Anil Maheshwari, Data Analytics, McGraw-Hill Publication.
- EMC Education Services, Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data, Wiley Publication.
- Philipp K. Janert, Data Analysis with Open Source Tools A Hands-On Guide for Programmers and Data Scientists, O’Reilly Media.
For detail syllabus of all subjects of Computer Engineering (CE) 5th Sem 2017-18 onwards, visit CE 5th Sem Subjects of 2017-18 Onwards.