Front-End Developer | React.js | Data Analysis | Machine Learning | Software Engineering
Hello! I'm Ali Abdo, a passionate Front-End Developer and Data Analyst with a deep love for crafting beautiful, intuitive web applications and deriving insights from data. My main focus is on leveraging powerful frameworks like Next.js to build dynamic, scalable, and performant web solutions, while also applying data analysis techniques to solve complex problems. π
I hold a Bachelor of Law from Tanta University (2018 - 2022) and have earned several professional certifications in Front-End Development, Data Analysis, and Machine Learning.
As a front-end enthusiast and data analyst, I specialize in:
- Creating Engaging Web Experiences with Next.js π₯οΈ
- Designing User-Friendly Interfaces using HTML, CSS, and Tailwind CSS π¨
- Developing Robust Backend Solutions with Node.js and Express.js π§
- Analyzing Data to uncover insights and trends using Python, NumPy, Pandas, and various data visualization libraries π
- Exploring Machine Learning Techniques to build predictive models using scikit-learn, TensorFlow, and Keras π€
In addition to front-end development, I'm passionate about Data Analysis and have hands-on experience in:
- Data Cleaning and Preprocessing: Preparing raw data for analysis using Python and Pandas. π§Ή
- Exploratory Data Analysis (EDA): Uncovering patterns and relationships in data using statistical methods and visualization techniques. π
- Data Visualization: Creating insightful charts and graphs to communicate findings effectively using libraries like Matplotlib and Seaborn. π
- Statistical Analysis: Applying statistical tests and methods to draw meaningful conclusions from data. π
- Machine Learning: Developing predictive models and applying machine learning algorithms to solve real-world problems. π§
- Exploring Cloud Technologies like Docker, Kubernetes, and OpenShift βοΈ
- Adopting Best Practices in DevOps and Agile Methodologies to streamline development workflows βοΈ
- Working with NoSQL Databases for flexible and scalable data management ποΈ
- Continuous Learning in the fields of Data Science and Machine Learning π
I'm driven by curiosity and a desire to tackle new challenges. I stay up-to-date with the latest advancements in technology and continuously seek out opportunities to learn and grow. I believe in building performant, accessible, and innovative solutions to solve real-world problems and make a positive impact. π
Here are some of the certifications I have earned to further my skills and knowledge:
- Machine Learning Specialization (Offered by Stanford University and DeepLearning.AI)
- Data Camp Data Analyst Professional Certificate (Issued Number: DA0023219375492)
- Meta Front-End Developer Professional Certificate
- Udacity Professional Front-End Web Developer Nanodegree
- IBM Back-End JavaScript Developer Certificate
Feel free to reach out to me if you're interested in collaborating or just want to chat about tech!
- Description: A social media platform built using Next.js, TypeScript, Tailwind CSS, and Clerk Auth for user authentication. It includes features like user profiles, posts, comments, and likes.
- Technologies: Next.js, TypeScript, Tailwind CSS, Clerk Auth
- Live Demo: Social Media App
- Description: A web application that summarizes articles using OpenAI's GPT-4. Users can input article text or URLs to receive concise summaries.
- Technologies: OpenAI GPT-4, JavaScript, React.js
- Live Demo: Summarize Articles
- Description: A data analysis project investigating Netflix movies and guest stars in "The Office." The project explores datasets to uncover insights and trends.
- Technologies: Python, Pandas, DataCamp
- Live Demo: Data Analysis Project
- Description: An end-to-end machine learning project for predicting heart disease. It demonstrates the application of foundational machine learning and data science concepts for classification.
- Technologies: Python, scikit-learn, Pandas, NumPy
- Repository: GitHub Repository
- Description: A deep learning project leveraging convolutional neural networks (CNNs) to classify chest X-ray images for pneumonia detection.
- Technologies: Python, TensorFlow, Keras, CNNs
- Repository: GitHub Repository
- Description: A repository showcasing an end-to-end Scikit-Learn workflow, including data preparation, model selection, evaluation, and improvement techniques.
- Technologies: Python, scikit-learn, Pandas, NumPy
- Repository: GitHub Repository