What will you in the Data Science Capstone Course
Build a complete data science project from start to finish using real-world data.
Apply skills in natural language processing (NLP), predictive modeling, and exploratory data analysis.
Create a user-facing data product using data science tools and best practices.
Communicate results clearly through a final presentation deck and interactive application.
Practice working independently and submitting peer-reviewed assignments in a capstone environment.
Program Overview
1. Getting Started & Understanding the Project
Duration: 1 hour
Introduction to the capstone and its objectives.
Review of SwiftKey dataset and project milestones.
2. Data Exploration and Cleaning
Duration: 3–4 hours
Clean and preprocess text data from blogs, news, and tweets.
Analyze data distribution, frequency, and language patterns.
3. Model Building and Prediction
Duration: 3–4 hours
Use NLP techniques like tokenization and n-grams.
Build predictive models for next-word suggestions.
4. Developing a Data Product
Duration: 3 hours
Create an interactive application using Shiny or other web tools.
Focus on usability, responsiveness, and prediction accuracy.
5. Communicating Your Results
Duration: 2 hours
Design a professional slide deck summarizing your project.
Emphasize methodology, findings, and user functionality.
6. Final Submission & Peer Review
Duration: 1–2 hours
Submit your app and presentation.
Evaluate peer submissions and receive feedback.
Get certificate
Job Outlook
Data Scientists: Build a robust portfolio project showcasing NLP and modeling skills.
AI/NLP Engineers: Apply advanced text analysis and prediction techniques in real contexts.
Business Analysts: Demonstrate the ability to translate data into user-ready solutions.
Freelancers & Tech Professionals: Use this capstone to pitch data apps to clients or employers.
Students: Complete your data science learning path with practical application.
Specification: Data Science Capstone
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