Applied Data Science Lab

Excited to share that I have completed the Applied Data Science Lab at WorldQuant University. Through this program, I strengthened my skills in Python programming, data analysis, machine learning, statistical modeling, data visualization, interactive data application development, and working with real-world datasets to solve practical problems.

The lab includes eight end-to-end, hands-on data science projects, in which I worked with data from files, SQL, NoSQL databases, and APIs. I also gained experience exploring and cleaning data, writing functions, and building ETL pipelines to prepare training datasets. Additionally, I developed machine learning models for both supervised and unsupervised learning problems and created visualizations to communicate data insights and model predictions clearly to non-technical audiences.

Across the projects, I applied techniques such as linear and logistic regression, decision trees, random forests, k-means clustering, time-series modeling (including ARMA and GARCH), A/B testing, and principal component analysis. I also practiced using tools and technologies such as Python, SQL, MongoDB, Plotly Dash, APIs, and the Linux command line.

Upon completion of the Data Science Lab, I earned a Credly verifiable badge, and I look forward to using the skills I acquire in future research.🚀