1 / 11

data science online training course content

Join the best Data Science online Training course at eonlinetraining.co, Hyderabad, India at at affordable charges <br>and become data scientist

eonlinetraining
Download Presentation

data science online training course content

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. DATA SCIENCE ONLINE TRAINING COURSE CONTENT website: www.eonlinetraining.co • Contact us @ +91 9177040520

  2. 1.Introduction to signal and pattern detection • Basic commands in R • Vectors and matrices in R • Two main file types in Rstudio and importing data into R • Installing packages in Rstudio

  3. 2.Univariate analysis • Statistical concepts of Frequency Distribution/Central Distribution and Dispersion • Understanding various test • Test for mean/proportion • Difference of mean/proportions • Chi square • Regression test • Paired test • Statistical understanding and R implementation of Univariate analysis

  4. 3.Bivariate analysis • Statistical concepts of Cross tabulations and Correlation • P value interpretation • Types of correlation explained using a data set in R • Concept of hypothesis • Chi square test and worked example • Correlation explained with example • Statistical understanding and R implementation of Bivariate analysis

  5. 4.Advanced visualization • Heat maps • Geospatial maps usage and explation of importance • Small multiples • Various advanced visualization tools and techniques

  6. 5.Business story telling

  7. 6.End to end case study • Survival analysis end-to-end case study And its interpretation • Attrition analysis and its interpretation • Active and inactive customers case study and its interpretation • Repeat purchase case study • Sales trends case study • segmenting customers case study

  8. 7.MACHINE LEARNING  • Supervised Learning • Decisions tree plotting in R using a dataset • Concept of decision tree • Classification • Unsupervised Learning • Dimension Reduction • Principle component analysis and implementation in R using dataset. • Clustering • Time series analysis • supervised and unsupervised ML from statistical point and in R

  9. 8.Regression Analysis • statistical perspective of Regression

  10. 9.Feature Engineering • Feature selection • Feature extraction • Variable ranking • Feature subset selection Filter methods and wrapper methods

  11. For More details http://eonlinetraining.co/course/data-science-online-training/mail : info@keepsakesoftware.comwebsite: www.eonlinetraining.coMobile : +91 9177040520

More Related