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Hi πŸ‘‹ My name is Tee

For friends who've known me, it's Thanh here!

I'm a data analyst (with marketing experienceas) dubbed 'a dream chaser'🦸 Adapting to changes and always learning mean a lot to me πŸ“š I've made a long journey from πŸ‡»πŸ‡³ - πŸ‡΅πŸ‡­ - πŸ‡¨πŸ‡¦ in the past few years 🌍 Now I'm based in Toronto, Canada 🍁

I'm really passionate about data analytics and Business Intelligence, and determined to improve my technical skills in Python, SQL, data viz, statistics, and Machine Learning πŸ’» Best to apply those skills with the business side knowledge I've had!

πŸ”­ I've finished university courses in Statistics, Python, SQL, and Data Organization at Ryerson University. I’ve also completed the Data Science Bootcamp at Lighthouse Labs recently.

I'm also looking for an internship or full-time position in Data Analytics & Business Intelligence in North America πŸ§‘β€πŸ€β€πŸ§‘ Please send me a DM on LinkedIn for any opportunity you may have!

Connect with me:

My LinkedIn My Github

Skills I've collected:

mysql

TeeNguyenDA's Projects

city-music-project icon city-music-project

Use data to test the hypotheses of music preferences and compare user behavior between two cities.

credit-score-project icon credit-score-project

The project is to perform data preprocessing and prepare a report for a bank’s loan division. We'll find out if a customer’s marital status and number of children have an impact on whether they will default on a loan. The bank already has some data on customers’ credit worthiness.

diabetes-prediction-supervised-learning icon diabetes-prediction-supervised-learning

Use supervised learning techniques to build a machine learning model that can predict whether a patient has diabetes or not, based on certain diagnostic measurements.

store-sales-forecasting icon store-sales-forecasting

Use time series to predict daily sales for the Favorita grocery store in Ecuador. Data adapted from Kaggle.

wholesale-data-unsupervised-learning icon wholesale-data-unsupervised-learning

Unsupervised Learning: perform unsupervised learning techniques on a wholesale data dataset. The project involves four main parts: exploratory data analysis and pre-processing, KMeans clustering, hierarchical clustering, and PCA.

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