KL, Malaysia • firstname.lastname@example.org • ammar-alyousfi.com • +601162078955
April, 2019 → Present
2018 → (Sep 2019, expected)
2012 → 2016
Data analysis and machine learning: Pandas, Numpy, Scikit-learn, Jupyter Notebook, SQL, Hadoop ecosystem.
Cloud computing: Google Cloud Platform, Amazon Web Services (EC2, S3).
Text analysis and NLP: Regular expressions, Wordcloud, limited experience in NLTK.
Web scraping: BeautifulSoup, Selenium.
Data visualization: Matplotlib, Google Data Studio, Seaborn, limited experience in Tableau.
Misc: Lyx (LaTeX IDE), Git, graphic design (Adobe Photoshop, GIMP), Google Analytics.
Languages: fluent in English (TOEFL: 102/120 in 2016), native Arabic, basic Malay.
YouTube Trending Video Analysis: Analyzed 40,000+ trending YouTube videos to answer interesting questions like “What are the most common words in video titles?”, “Which channels and which categories have the largest number of trending videos?”, and many more. (Python, Pandas, Matplotlib, Seaborn, WordCloud, Jupyter Notebook).
Analysis of Top Reddit posts: Analyzed the top 1,000 posts of 18 popular subreddits on reddit.com. Found the most common words and n-grams, used word clouds to show them, etc. (Python, Pandas, NLTK, WordCloud, Matplotlib, Seaborn).
Kaggle Machine-Learning Competitions: Participated in many competitions where a variety of ML techniques were used:
House Price Prediction, An End-to-End Machine-Learning Project: (Pandas, Matplotlib, Scikit-learn, XGBoost, etc.).
s3upload: Automates uploading files to AWS S3. (Python, boto3).
Focus Phase: An open-source time-tracker command-line Python application with statistics and visualizations. Published on the Python Package Index.