Project 1 : Analyzing the Naming Pattern Using Python
Industry : General
Problem Statement : How to analyze the trends and the most popular baby names
Topics : In this Python project, you will work with the United States Social Security Administration (SSA) which has made data on the frequency of baby names from 1880 to 2016 available. The project requires analyzing the data considering different methods. You will visualize the most frequent names, determine the naming trends and come up with the most popular names for a certain year.
- Analyzing data using Pandas Library
- Deploying Data Frame Manipulation
- Bar and box plots with Matplotlib
Project 2 : – Python Web Scraping for Data Science
In this project, you will be introduced to the process of web scraping using Python. It involves installation of Beautiful Soup, web scraping libraries, working on common data and page format on the web, learning the important kinds of objects, Navigable String, deploying the searching tree, navigation options, parser, search tree, searching by CSS class, list, function and keyword argument.
Project 3 : Predicting Customer Churn in Telecom Company
Industry – Telecommunications
Problem Statement – How to increase the profitability of a telecom major by reducing the churn rate
Topics :In this project, you will work with the telecom company’s customer dataset. This dataset includes subscribing telephone customer’s details. Each of the column has data on phone number, call minutes during various times of the day, the charges incurred, lifetime account duration and whether the customer has churned some services by unsubscribing it. The goal is to predict whether a customer will eventually churn or not.
- Deploy Scikit-Learn ML library
- Develop code with Jupyter Notebook
- Build a model using performance matrix