Hello, I'm Mazen Elsafty

Bachelor's Degree in Information Technology

Pursuing a Bachelor's Degree in Information Technology with a specialization in Information Technology and Data Management.

GPA : 3.69

IBM Data Scientist , Soft Skills , English

The Digital Egypt Pioneers Initiative (DEPI), launched by the Egyptian Ministry of Communications and Information Technology, aims to cultivate a skilled workforce in digital technology and data science through advanced training programs and certifications.

• IBM Data Science Grant Program:
  • Completed a comprehensive grant-supported program by IBM under DEPI.
  • Focused on mastering tools and techniques for data analysis, machine learning, data visualization, data cleaning, exploratory data analysis (EDA), statistics, web scraping, Python programming, and SQL.
• Hands-on Tools and Libraries:
  • Gained proficiency in Anaconda and Jupyter Notebook environments.
  • Worked extensively with libraries such as Pandas, NumPy, Scikit-learn, Beautiful Soup, Requests, and SQL Magic.
  • Applied machine learning techniques, including supervised and unsupervised models, cross-validation, grid search, and model tuning.
• Real-World Project Experience:
  • Ames House Price Prediction: Built predictive models to estimate house prices based on key features.
  • Finding Donors Predictor: Developed models to identify potential donors for charity organizations.
  • Chicago Web Scraping Project: Scraped real estate data from Chicago listings and created a structured dataset.
  • Medical Representative Analysis: Analyzed performance metrics and trends for medical representatives.
  • SMS Spam Classifier: Created a machine learning model to classify SMS messages as spam or legitimate.
• Technologies and Techniques:
  • Employed advanced data preprocessing, cleaning, and feature engineering techniques.
  • Utilized machine learning pipelines to streamline workflows.
  • Worked on model evaluation and tuning to optimize performance.
• Professional Development:
  • Received specialized training in freelancing, soft skills development, and English proficiency to support career growth and communication skills.
• Through this initiative, I have built a robust foundation in data science and honed my ability to apply theoretical concepts to solve practical problems effectively. My work exemplifies a commitment to leveraging data-driven insights to address real-world challenges.

Data Scientist

CodeAlpha is a leading technology and software development company specializing in innovative solutions in data science, machine learning, and software engineering.

• Machine Learning Models:
  • Developed and implemented a linear regression model to predict housing prices, working on feature engineering, data scaling, and model evaluation to enhance prediction accuracy.
• A/B Testing Analysis:
  • Analyzed and compared product performance in an A/B testing scenario using Bayesian analysis and Chi-Square tests.
  • Delivered actionable insights that guided the marketing team in optimizing strategies for better customer engagement.
• Stock Price Prediction:
  • Built and trained a Long Short-Term Memory (LSTM) model to predict Microsoft stock prices.
  • Utilized temporal dependencies in stock market data to improve prediction accuracy.
  • Employed time-series data processing techniques, such as sequence generation, lag features, and rolling statistics.
• Data Preparation and EDA:
  • Collaborated in data collection and preprocessing, including handling missing values, outlier treatment, and feature selection.
  • Conducted exploratory data analysis (EDA) to identify patterns and trends, ensuring data quality and insight generation.
• Technologies and Tools:
  • Programming Languages: Python.
  • Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow, and Keras.
  • Data Analysis Techniques: Bayesian analysis, Chi-Square tests, time-series analysis, and data preprocessing.
  • Development Environments: Jupyter Notebook and Anaconda.
  • Machine Learning Techniques: Regression models, deep learning (LSTM), cross-validation, and hyperparameter tuning.
• At CodeAlpha, I worked on diverse projects, leveraging cutting-edge tools and techniques to deliver impactful solutions. This experience significantly enhanced my technical expertise and my ability to contribute effectively to collaborative, data-driven environments.

Data Scientist

Bharat Intern is a premier internship platform that bridges the gap between education and industry. It provides students and young professionals with meaningful opportunities in diverse fields such as technology, data science, marketing, and more.

• Titanic Survival Prediction Project:
  • Developed machine learning models, including Logistic Regression, Decision Trees, and Random Forests, to predict passenger survival on the Titanic.
  • Conducted data preprocessing, feature engineering, and model evaluation to improve predictive accuracy.
• CNN-Based Image Classification Project:
  • Built a Convolutional Neural Network (CNN) to classify images of cats and dogs, gaining hands-on experience with deep learning.
  • Utilized frameworks such as TensorFlow and Keras, focusing on model architecture, optimization, and validation.
• Skill Development:
  • Strengthened expertise in data preprocessing, including handling missing values, normalization, and data augmentation for image data.
  • Gained experience in model training, fine-tuning, and leveraging collaborative teamwork to deliver high-quality outcomes.
• Technologies and Tools:
  • Programming Languages: Python.
  • Libraries: Pandas, NumPy, Matplotlib, Scikit-learn, TensorFlow, and Keras.
  • Machine Learning Techniques: Supervised learning, deep learning, and neural network optimization.
  • Development Environments: Jupyter Notebook and Anaconda.
• At Bharat Intern, I had the opportunity to work on impactful projects, enhancing my technical expertise and teamwork abilities in a dynamic, learning-oriented environment.

Data Analyst

NeuronetiX is an innovative technology company specializing in data analytics and artificial intelligence solutions. The company leverages cutting-edge technology to transform data into actionable insights, driving decision-making across diverse industries.

• Data Analysis and Insights:
  • Performed comprehensive data cleaning, preprocessing, and exploratory analysis to identify patterns and trends in large datasets.
  • Applied statistical techniques to derive actionable insights and informed strategic decision-making.
• Data Visualization and Reporting:
  • Designed interactive dashboards and reports using Power BI and Excel, enabling stakeholders to explore key metrics effectively.
  • Created compelling visualizations to communicate complex data trends and findings clearly.
• Technical Expertise:
  • Utilized Python libraries such as Pandas, NumPy, and Matplotlib for data manipulation and visualization.
  • Automated repetitive data tasks to improve efficiency and accuracy in data workflows.
• Technologies and Tools:
  • Programming Languages: Python.
  • Libraries: Pandas, NumPy, Matplotlib, and Seaborn.
  • Data Visualization Tools: Power BI and Excel.
  • Techniques: Data cleaning, statistical analysis, and exploratory data visualization.
• At NeuronetiX, I honed my analytical and technical skills, contributing to data-driven projects that empowered businesses to make informed decisions. This experience deepened my understanding of real-world data challenges and solutions.