As an aspiring Technical Project Manager, I completed the IBM Data Science Applied Capstone Project. In this project, I took on the role of a data scientist for a fictional space exploration company, leveraging real-world data from the SpaceX REST API and web-scraped records to analyze and predict the outcomes of rocket launches. Here’s what I accomplished:
Data-Driven Insights
Utilized Python libraries like Pandas and BeautifulSoup for data wrangling and cleaning.
Built interactive dashboards using Plotly Dash to visualize launch trends and performance metrics.
Predicted successful rocket landings using machine learning models, adding significant value to decision-making.
Strategic Problem Solving
Optimized datasets through API integration and advanced filtering techniques, focusing on meaningful insights.
Tackled challenges like handling missing data and creating features through exploratory data analysis.
Delivered actionable insights on cost efficiency and operational outcomes for stakeholders.
Results-Oriented Execution
Demonstrated the ability to manage an end-to-end technical project, from data collection to analysis and deployment.
Built scalable solutions to answer critical business questions—key skills for leading cross-functional teams in tech.
This capstone project has enhanced my technical fluency and reinforced my ability to align data-driven insights with business objectives—a crucial skill for technical project managers.
