This self-learning course by DataCamp has equipped me with essential data science skills using Python. It covers data manipulation, visualization, and machine learning through hands-on projects with popular libraries like pandas, Seaborn, Matplotlib, and scikit-learn. The Python skills learned from this program allow me to use Python for various work assignments and personal projects.
This self-learning course has equipped me with essential web development skills for both front-end and back-end technologies, including HTML, CSS, and JavaScript. I had the opportunity to build interesting web-based projects throughout this course. The skills learned from this program also allow me to use web technologies as the user-interface platform for desktop applications and my Python models.
A life insurance cashflow projection tool powered by Python can be used as an alternative to Excel and Prophet software. Web technologies (HTML, CSS, and JavaScript) are used as the UI framework for the model and bundled as a desktop application using Electron.js.
A personal webpage built from scratch using HTML, CSS and Javascript, while Figma is used to draft the page design before coding. To streamline the process, Webpack is used to compile assets from various directories sources into a single folder for publishing.
A classic to-do application for managing personal tasks. The UI is built with HTML and CSS, while JavaScript handles the application logic, including enhanced features such as due-date alerts and task summaries by various metrics. I also packaged a desktop version of this web application using Electron.js.
This project from DataCamp involves using Python's scikit-learn library to train data and build a model to predict customer healthcare costs. The project's requirements include testing the model's accuracy on a new dataset, providing hands-on experience in handling machine learning assignments.
This past DataCamp competition served as a practice for machine learning skills. In this project, I used Python to propose recommendations for better segmenting customers based on the provided data.
- Topics | Python Asynchronous programming, Python GPU programming, OpenAI API, Web App cloud hosting.
- Development | Profile random generator, Web scrapping (e.g. use provider's API or Python's Selenium )
- Tools | React, Node.js, Azure, SheetJS.