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Muhammad Ghazal

Muhammad Ghazal

Graduate

Faculty of Science, Tanta University | Tanta, Al-Gharbiyah, Egypt

Technologies

My Portfolio Highlights

My New Github

A/B Testing Report – Conversion Impact Analysis of New Landing Page

My New Github

WeRateDogs Twitter Data Analysis & Visualization

My New Github

TMDB Dataset Analysis: Trends & Profit Drivers

My New Github

A/B Testing Report – Conversion Impact Analysis of New Landing Page

Analytical daredevil, fearlessly diving into the abyss of data complexity.

My Work

Take a look at my latest work.

github

FordGo Bike Share Analysis

Python
github

WeRateDogs Twitter Data Analysis & Visualization

github

A/B Testing Report – Conversion Impact Analysis of New Landing Page

Python
github

TMDB Dataset Analysis: Trends & Profit Drivers

Python
github

Interactive Python CLI for U.S. Bikeshare Insights

Python
github

Cairo vs. Global Temperature Trends Analysis

SQLSpreadsheetsExcel
github

FordGo Bike Share Analysis

Python

My Certifications

These are the industry credentials that I’ve earned.

Other Certificates

Udacity Advanced Data Analysis Nanodegree

Udacity Data Analysis Professional Nanodegree

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

Courses

Introduction to Excel
Data Analysis in Excel
Data Preparation in Excel
Data Visualization in Excel

My Work Experience

Where I've interned and worked during my career.

Udacity | Oct 2020 - May 2021

Data Analyst Intern

Analyzing A/B Test Results: Conducted an A/B test analysis on 290K+ users that revealed nearly identical conversion rates between the new (11.88%) andold (12.04%) pages with simulation (96.03% of simulated differences exceeding the observed gap), proportions z-test, and logistic regression (p = 0.9392) confirming the lack of a statistically significant impact, even after controlling for country effects. Wrangling and Analyzing WeRateDogs Data: Transformed 3 raw Twitter datasets into master CSVs by resolving issues such as duplicate URLs and datatype mismatches, then analyzed the cleaned data to uncover a 0.93 correlation between retweets and favorites, an average dog rating of 10.53 (max 14), andidentified “pupper” as the most frequent dog stage with ~200 occurrences.. Exploring U.S Bikeshare Data: Engineered a Python CLI tool using Pandas and NumPy to analyze bikeshare data from three major U.S cities (Chicago, New York City, Washington), supporting filtering by six months and seven weekdays and automatically computing five core metrics most frequent traveltimes (month, day, hour), top start/end stations, total and average trip durations, and user demographics (user types, gender counts, birth year stats). TMDB Movies Dataset Analysis: Conducted in-depth data analysis on 10,000+ movies using Python (Pandas, Matplotlib, Seaborn), identifying key revenuedrivers with moderate correlations to vote count (0.61) and popularity (0.52); skewed net profit distribution (average: $93.9M, median: $28.5M) andvisualized genre popularity trends from 1984–2011. Exploring Weather Trends: Analyzed historical temperature data for Cairo versus global averages using SQL and Excel (applying 7‑year moving averages), revealing Cairo’s temperatures consistently exceed global means, a strong positive correlation (r = 0.913), and identifying key cooling intervals (global: 1830–1841; Cairo: 1817–1824). Ford GoBike Share System Analysis: Analyzed 174,952 bike-sharing trips across the San Francisco Bay Area, revealing that casual customers drove 35% longer trips on average (median 1,000 sec) compared to subscribers (median 650 sec), and identified user type as the strongest predictor of trip duration.
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My Education

Take a look at my formal education

Bachelor's in Computer ScienceFaculty of Science, Tanta University | 2020

About Me

Muhammad Ghazal

Remote Data Analyst skilled in Python, SQL, and Excel. I turn complex data into actionable insights that drive strategic decisions. Lifelong learner committed to innovation and excellence.

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