akash1070 / data-analytics-virtual-experience-program-by-quantium

Data Analytics Virtual Experience Program by Quantium

Data Analytics Virtual Experience Program by Quantium

• This is program consists of 3 tasks
• All these code files were my personal submissions for this program. Except the data files which were assigned by Quantium.

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Code and Resources Used

Python Version: 3.7

Packages: pandas, numpy, seaborn, sklearn, matplotlib, datetime, scipy

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Deployment

Task 1 - Data preparation and Customer Analytics

Conduct analysis on your client's transaction dataset and identify customer purchasing behaviours to generate insights and provide commercial recommendations.

Task 2 - Experimentation and Uplift Testing

Extend your analysis from Task 1 to help you identify benchmark stores that allow you to test the impact of the trial store layouts on customer sales.

Task 3 - Analytics and Commercial Application

• Use your analytics and insights from Task 1 and 2 to prepare a report for your client, the Category Manager.

Final Report

• Use analytics and insights from Task 1 and 2 to prepare a report for the client, the Category Manager.
• Delivered the insights and recommendaions to the client in PowerPoint presentation along with easy to understand data visualizations.

Authors

• @Akash Kumar Jha

Installation

To install the libraries used in this project. Follow the below steps:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np

Running Flask Api

To run tests, run the following command

  python app.py

🚀 About Me

Data Scientist Enthusiast | Petroleum Engineer Graduate | Solving Problems Using Data

Hi, I'm Akash! 👋

🔗 Links

Tech Stack

Other Me

👩‍💻 I’m interested in Petroleum Engineering

🧠 I’m currently learning Data Scientist | Data Analytics | Business Analytics

👯‍♀️ I’m looking to collaborate on Ideas & Data

🛠 Skills

1. Data Scientist
2. Data Analyst
3. Business Analyst
4. Machine Learning

Future Plans

⚡️ Looking forward to help drive innovations into your company as a Data Scientist

⚡️ Looking forward to offer more than I take and leave the place better than i found