Проекты python

Python SDK for the PostHog API

Devhaus Tracking Code is a helper code snippet that helps Webflow developers mainly to implement event tracking and send them to multiple destinations i.e. CDP tools or Product Analytics.

Product analysis done on the data of revenue from social network users and cost of user aqcuisetion. Computed KPIs such as Sessions per user, Actions per user,DAU, CAC, RoI, etc. Different methids of customer acquisition were considered and reccomendations regarding acquisition strategy were provided

Product Sales Data Analytics

Combination of different Data and Business Analytics projects, done with python and different machine learning techniques.

Analysis of large retailer's sales data. Customer segmentation using RFM analysis and k-means clustering

Career Foundry data analytics project to provide a client recommendations on a marketing strategy. Jupyter notebooks include cleaning and merging data along with creating new columns to offer the best understanding of consumers' interactions with products.

Анализ данных онлайн образовательной платформы: завершаемость курсов, успеваемость, статистика подписок/отписок + сегментация RFM

Track events with mixpanel from laravel applications

💹 seasonal patterns to GROW REVENUE • 2023

Typescript SDK for the PostHog API

Works completed within the Product Analytics and the Product Development modules of the Data Analyst course on the Karpov Courses platform

Detecting fraudulent app usage data with STL and confidence intervals and enhancing ARIMA forecasting with STL

💬 Statistics | R | SQL

🏭 This repository serves as a demonstration of how to analyze product defects and identify critical points within the product. By doing so, we can effectively troubleshoot and address potential issues to improve product quality and performance.

A comprehensive repository containing resources for the Chatify Social Media App Launch, including product analytics reports, wireframe designs, and marketing data.

Standalone HTTP service for ingesting user behaviour events, backed by Postgres, ClickHouse and Fastify.

My notes as I read through books, watch talks and generally just learn!