This repository is mainly for projects I have done under Practicum100 program by Yandex, Udacity data analyst nano degree and self learning.
For a more visually pleasant experience for browsing the portfolio, check out https://rakibulsitab.com/
Practicum100 is a 9-month intensive program designed to train 100 talents to be successful Data Analysts in Germany.Practicum100 online data analyst program prepares me for a career as a data analyst by helping me collecting and structuring data, forming and testing hypotheses, identifying patterns, and drawing conclusions.I am developing proficiency in Python and its data analysis libraries (Numpy, pandas, Matplotlib) and SQL as I build a portfolio of projects .
Tips: For data analyst projects with python, I would recomend you to install numpy , pandas , scipy , scikit learn , matplotlib , seaborn , plotly , missingno , scipy , nltk libraries.
This project is to prepare a report for a bank’s loan division.I was provided a dataset from Practicum100 which is based on some data on customers’ credit worthiness. I found out if a customer’s marital status and number of children has an impact on whether they will default on a loan.My report have been considered when building a credit score for a potential customer. A credit score is used to evaluate the ability of a potential borrower to repay their loan.I complete the entire data analysis process by sharing the findings.
Hundreds of free advertisements for vehicles are published on a site every day.I've analysed data collected over the last few years and determine which factors influence the price of a vehicle.The datasets was provided by Practicum100 which is based on a free vehicles advertisement website.
Telecom operator Megaline offers its clients two prepaid plans, Surf and Ultimate. The commercial department wants to know which of the plans brings in more revenue in order to adjust the advertising budget.The datasets was provided by Practicum100 which is based on 500 Megaline clients.
Project 4: Spot the potential big winners and plan advertising campaigns to earn maximum profit for a video games online stores
The online store Ice, which sells video games all over the world. User and expert reviews, genres, platforms (e.g. Xbox or PlayStation), and historical data on game sales are available from open sources. I identified the patterns that determine whether a game succeeds or not.The datasets was provided by Practicum100 and contains the abbreviation ESRB. The Entertainment Software Rating Board evaluates a game's content and assigns an age rating such as Teen or Mature.
A new ride-sharing company Zuber that's launching in Chicago. Our task is to find patterns in the available information. We want to understand passenger preferences and the impact of external factors on rides. We'll study a database, analyze data from competitors, and test a hypothesis about the impact of weather on ride frequency.
We're working as an analyst in the analytical department at Yandex.Afisha. We want to understand and optimize marketing expenses.
We are an analyst at a big online store. Together with the marketing department, we've compiled a list of hypotheses that may help boost revenue.
We’ve decided to open a small robot-run cafe in Los Angeles. The project is promising but expensive, so we and our partners decide to try to attract investors. We’re interested in the current market conditions
The designers would like to change the fonts for the entire app, but our managers are afraid the users might find the new design intimidating. To make a decision we did an A/A/B test and funnel analysis.
Project 10 : Evaluating how the introduction of an improved recommendation system impacts the behavior and conversion of users on this international online store.
The purpose of this project is to determine whether the introduction of an improved recommendation system impacts the behavior and conversion of users on this international online store.
The coronavirus took the entire world by surprise, changing everyone's daily routine. City dwellers no longer spent their free time outside, going to cafes and malls; more people were home, reading books. That attracted the attention of startups that rushed to develop new apps for book lovers. We've been given a database of one of the services competing in this market. It contains data on books, publishers, authors, and customer ratings and reviews of books. This information will be used to generate a value proposition for a new product.
Company XYZ have contacted with our data consulting firm.To boost their sales and targeting customers, they are interested to do a product range analysis.They want to see some KPI , such as revenue, average check, and ARPPU.
In order to fight churn, Model Fitness has digitized a number of its customer profiles. Our task is to analyze them and come up with a customer retention strategy using machine learning model. link : https://github.com/rakibul-sitab/Data-Analyst-Portfolio/tree/main/Machine%20learning%20projects/Analyze_customer_churn_and_come_up_with_a_customer_retention_strategy
Project 2 : Build a best machine learining model to predict the right real estate price for the property owners.
Imagine that we work for a real estate platform. Instead of using real estate agent services, property owners submit their own listings, and buyers can respond to them directly. If a transaction goes through successfully, the platform takes a cut. Website analytics showed that property owners often fail to base their prices on the market value. This practice is always bad for the website: inexpensive items are sold quickly, but the platform's cut is also lower because of this. Overpriced items, on the other hand, are never sold, which means no profit at all. The service needs to prevent sellers from underselling and overpricing. We need to figure out an algorithm to help property owners determine the right price
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent