https://github.com/yulia-momotyuk/dla-data-analysis-practice

This repository contains my homework assignments completed during the "Data Analyst in IT" course at Data Loves Academy.
https://github.com/yulia-momotyuk/dla-data-analysis-practice

analytics data-analysis data-visualization excel mysql numpy pandas postgres powerbi python seaborn sql tableau

Last synced: 2 months ago
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This repository contains my homework assignments completed during the "Data Analyst in IT" course at Data Loves Academy.

• Host: GitHub
• URL: https://github.com/yulia-momotyuk/dla-data-analysis-practice
• Owner: Yulia-Momotyuk
• Created: 2025-06-04T20:10:52.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-06-15T12:24:50.000Z (about 1 year ago)
• Last Synced: 2025-06-15T13:45:55.888Z (about 1 year ago)
• Topics: analytics, data-analysis, data-visualization, excel, mysql, numpy, pandas, postgres, powerbi, python, seaborn, sql, tableau
• Language: Jupyter Notebook
• Homepage:
• Size: 74.2 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# 📚 Homework Repository 

## Course: "Data Analyst in IT"

This repository contains my **homework assignments** completed during the **"Data Analyst in IT"** course at **Data Loves Academy**.

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## Repository Structure:

- `Excel/Google Sheets` — spreadsheets, formulas, pivot tables, visualizations

- `SQL` — database queries 

- `Vizualization Tools: PowerBI & Tableau` — visual analytics, dashboards, funnel interactive dashboards and KPI reports

- `Python` — data analysis using pandas, matplotlib, seaborn, plotly

- `Static Hypothesis Testing and A/B Testing` — the folder contains examples of static hypothesis testing and A/B testing with Python.

- `Machine Learning` — machine learning basics, linear regression, logistic regression, decision trees, classification, data manipulation, and simple models in Python using a basic dataset.

- `README.md` — repository overview

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## What I'm Learning:

- Use product and marketing metrics of an IT product to understand business processes  

- Program and analyze data using Python (plus Git as a bonus)  

- Build informative data visualizations  

- Work with SQL and BigQuery  

- Apply statistics and probability theory to practical problems  

- Analyze A/B tests  

- Build interactive reports in BI tools (Tableau and Power BI)  

- Use Google Spreadsheets/Excel (data handling, data visualization, pivot tables, VLOOKUP, working with APIs, text parsing)  

- Build basic machine learning models for forecasting, classification, and clustering  

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## Goal:

To gain hands-on data analytics skills and confidently begin a career in the **Data Analytics** field.

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## Tools & Technologies:

- SQL (PostgreSQL / MySQL)

- Excel / Google Sheets

- Power BI

- Tableau 

- Python 

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> ✨ **Data Loves Academy** is not just a course — it's a journey where data becomes insight 

## 📬 Contact

[LinkedIn](https://www.linkedin.com/in/yuliia-kononchuk-78913633b/) | [Email](mailto:kononchuk.yuliia@gmail.com)

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> **Author**: _Yuliia Kononchuk_  

> _This repository is part of my personal learning journey and professional portfolio._