Welcome to my repository for the Data Science Virtual Internship Program with British Airways through Forage! π
During this internship, I had the opportunity to dive deep into data science, applying various techniques to real-world airline data. This experience was both challenging and rewarding, offering valuable insights into how data science can drive impactful business decisions and improve customer experiences. Hereβs a comprehensive overview of what I worked on:
This internship provided a deep dive into the following areas:
- Data Scraping & Collection: Master the art of extracting data from web sources.
- Sentiment Analysis: Learn how to interpret and classify customer feedback.
- Data Cleaning & Preparation: Develop skills in preprocessing data for analysis.
- Model Building & Visualization: Gain experience in creating predictive models and visualizing results.
- Effective Presentation: Presenting findings and insights using PowerPoint. π€π
- Scrape Customer Feedback: Gather and analyze data from third-party sources.
- Analyze & Present Insights: Use PowerPoint to showcase your findings and recommendations. π
- Web Scraping: Utilized Python to scrape unstructured review data from Skytrax. π
- Sentiment Analysis: Processed and analyzed customer reviews to identify positive and negative sentiments. ππ‘
- Data Preparation: Cleaned the data to ensure it was ready for insightful analysis.
- Data Cleaning: Removed unwanted non-alphabetic characters. π«π
- Tokenization: Split the text into meaningful words. π
- Stopwords Removal: Filtered out common but less informative words. π«π£οΈ
- Lemmatization: Normalized words to their base form for consistency. π
- Sentiment Analysis: Applied VADER to score and classify sentiments. π
- Visualization: Created engaging pie charts, histograms, and word clouds to represent the data. π₯§ππ
- A PowerPoint presentation that highlights key insights and analysis results. π
Learn how predictive modeling helps British Airways acquire customers before they embark on their holidays. π
Understand how using data and predictive models can enable airlines to proactively acquire customers by analyzing booking data. π
- Prepare a Dataset: Manipulate and preprocess the provided customer booking data. π§
- Train a Machine Learning Model: Build and train a predictive model to forecast customer buying behavior. π€
- Evaluate and Present Findings: Assess the model's performance and interpret how each variable contributes to the predictive model's power. π
Customers today have vast access to information, changing the buying cycle significantly. Airlines must be proactive to attract customers before their travel dates. Predictive models, driven by high-quality data, are essential for this approach. You'll prepare data, build a model, and evaluate its predictive capabilities.
- A detailed PowerPoint presentation showcasing the model's performance, insights, and the contribution of each variable to its predictive power. πποΈ
Explore the internship program details and get started with Forage. π
A big thank you to British Airways and Forage for offering this fantastic learning opportunity. Your support and resources have been instrumental in my journey. ππ
Feel free to explore the repository, and donβt hesitate to reach out if you have any questions or suggestions. Letβs connect and continue learning together! π€
Happy exploring and learning! ππ