This repository should help people that would like to code in R and work with the National Health and Nutrition Examination Survey (NHANES). Some topics corved are SQL , logistic regression.... etc

Descriptive analytics on F.R.I.E.N.D.S TV series.

Comprehensive tutorial notes for ETC2410 Introductory Econometrics

Product Rationalization of Pro Bikes Inc using Power BI

Investigate a dataset of appoinment records for Brasil public hospitals

Machine Learning Key Projects

Analysis of Happiness scored according to economic production, social support, etc.

Power BI based Data\Business analysis of e-commerce company with focus on demographic analysis

This is a Descriptive Analytics Project which consists of various univariate, bivariate and multivariate data analysis on multiple data sets and their variables using R and its various statistical packages

Descriptive and Predictive Analytics of COVID-19 with respect to different Weather parameters

The H-1B is an employment-based, non-immigrant visa category for temporary foreign workers in the United States. For a foreign national to apply for H1-B visa, an US employer must offer a job and petition for H-1B visa with the US immigration department. This is the most common visa status applied for and held by international students once they…

A python based terminal interface to analyze the real-time performance of 3000+ company securities listed on NASDAQ. An extensive set of modules based on Pandas, NumPy, Matplotlib and Seaborn libraries. Also deployed the prediction of stock prices using Linear Regression.

Teaching notes, modules, tutorials etc for the course. For info see the link.

🐧🏠 This repository can be referred for basic data science analytics tasks such as descriptive analytics (data distributions & data preprocessing) and predictive modelling (classification or regression tasks).

This Project is all about studying and analyzing the Urbanization Rates and the percentage of Population living in Urban Areas for the Countries.

In order to create a good movie. We have chosen the score of 4.0 and above over 5.0. We will use the data to analyse what is needed to create a good movie.

Estimated probability models that help target consumers to build brand loyalty

Practical exercises and resources from the 9-course IBM Data Analyst Professional Certificate program, featuring core data skills with Python, Cognos Analytics, and end-to-end capstone project