src/index.qmd

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title: "About My Data Science Capstone Project"
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My Data Science Capstone Project is designed as the final course in the IBM Data Science Professional Certificate and the Applied Data Science with Python Specialization. This capstone project provides an opportunity to practice real-life data science tasks using datasets.

## Project Overview
In this course, you will take on the role of a Data Scientist for a startup aiming to compete with SpaceX. You will follow the Data Science methodology, which includes:

- **Data Collection:** Gathering relevant data for the project.
- **Data Wrangling:** Cleaning and preparing data for analysis.
- **Exploratory Data Analysis (EDA):** Analyzing data to uncover insights.
- **Data Visualization:** Creating visual representations of data to facilitate understanding.
- **Model Development:** Building predictive models.
- **Model Evaluation:** Assessing model performance and making improvements.
- **Reporting:** Presenting results to stakeholders.


## Objective
1. Your main task is to predict the success of the first stage landing of the SpaceX Falcon 9 rocket. Your data science findings and models will enable the startup to make informed bids against SpaceX for rocket launches.

2. By completing this capstone project, you will gain practical experience and add a significant project to your data science and machine learning portfolio.

## What You'll Learn
Proficiency in Data Science Techniques: Apply data science and machine learning techniques using a real-world dataset and prepare a comprehensive report for stakeholders.
Hands-on Experience: Perform data collection, data wrangling, exploratory data analysis, data visualization, model development, and model evaluation.
Machine Learning Models: Write Python code to create models such as support vector machines, decision tree classifiers, and k-nearest neighbors.
Model Evaluation: Evaluate the results of machine learning models, compare their strengths and weaknesses, and identify the optimal model.

## Skills You'll Gain
GitHub: Proficiency in using GitHub for version control and collaboration.
Jupyter Notebook: Experience with Jupyter Notebooks for interactive computing and data analysis.
K-Means Clustering: Understanding and application of k-means clustering for data segmentation.
Data Science Methodology: Mastery of the data science methodology for solving complex problems.