- Level Professional
- Duration 13 hours
- Course by IBM
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Offered by
About
This is the final course in the IBM Data Science Professional Certificate as well as the Applied Data Science with Python Specialization. This capstone project course will give you the chance to practice the work that data scientists do in real life when working with datasets. In this course you will assume the role of a Data Scientist working for a startup intending to compete with SpaceX, and in the process follow the Data Science methodology involving data collection, data wrangling, exploratory data analysis, data visualization, model development, model evaluation, and reporting your results to stakeholders. You will be tasked with predicting if the first stage of the SpaceX Falcon 9 rocket will land successfully. With the help of your Data Science findings and models, the competing startup you have been hired by can make more informed bids against SpaceX for a rocket launch. In this course, there will not be much new learning, instead you’ll focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your data science and machine learning portfolio to showcase to employers.Modules
Welcome
1
Readings
- Course Introduction
Capstone Introduction and Understanding the Datasets
1
Videos
- Project Scenario and Overview
Collecting the Data
2
Assignment
- Check Points: Data Collection API
- Graded Quiz: Data Collection API with Webscraping
2
External Tool
- Hands-on Lab: Complete the Data Collection API Lab
- Hands-on Lab: Complete the Data Collection with Web Scraping lab
1
Videos
- Data Collection Overview
Data Wrangling
2
Assignment
- Check Points: Data Wrangling
- Graded Quiz: Data Wrangling Quiz
1
External Tool
- Hands-on Lab: Data Wrangling
1
Videos
- Data Wrangling Overview
Exploratory Analysis Using SQL
2
Assignment
- Check Points: Exploratory Analysis Using SQL
- Exploratory Data Analysis using SQL
1
External Tool
- Hands-on Lab: Complete the EDA with SQL
1
Videos
- Exploratory Data Analysis Overview
Exploratory Analysis Using Pandas and Matplotlib
2
Assignment
- Check Points: Complete the EDA with Visualization
- Exploratory Data Analysis for Data Visualization
1
External Tool
- EDA with Visualization Lab
Interactive Visual Analytics and Dashboard
2
Assignment
- Check Points: Interactive Visual Analytics and Dashboard
- Graded Quiz: Interactive Visual Analytics and Dashboard
2
External Tool
- Hands-on Lab: Interactive Visual Analytics with Folium lab
- Hands-on Lab: Build an Interactive Dashboard with Ploty Dash
1
Videos
- Interactive Visual Analytics and Dashboards
Predictive Analysis (Classification)
2
Assignment
- Check Points: Predictive Analysis
- Graded Quiz: Predictive Analysisis
1
External Tool
- Hands-on Lab: Complete the Machine Learning Prediction lab
1
Videos
- Predictive Analysis Overview
How to Present Your Findings
2
Videos
- Elements Of A Successful Data Findings Report
- Best Practices For Presenting Your Findings
Final Presentation
1
Peer Review
- Peer Review: Submit your Work and Review your Peers
Credits and Acknowledgments
3
Readings
- Congratulations and Next Steps
- Credits and Acknowledgments
- Copyrights and Trademarks
Auto Summary
Embark on a comprehensive journey into the realm of data science with the "Applied Data Science Capstone," a pivotal part of both the IBM Data Science Professional Certificate and the Applied Data Science with Python Specialization. This hands-on course immerses you in the real-world tasks of a Data Scientist, simulating the high-stakes environment of a startup competing with SpaceX. You'll engage in the full spectrum of data science activities—ranging from data collection and wrangling to exploratory data analysis, data visualization, model development, evaluation, and stakeholder reporting. Your mission: predict the successful landing of SpaceX Falcon 9's first stage, thereby aiding the startup in making competitive bids for rocket launches. This capstone project emphasizes practical application over new theoretical learning, allowing you to consolidate and showcase the skills you've acquired in earlier courses. Successfully completing this course will enrich your portfolio with a significant project, enhancing your appeal to future employers. Offered by Coursera, the course spans 780 minutes and is available through Starter and Professional subscription options. Tailored for those at a professional level, it’s an excellent opportunity for aspiring data scientists looking to demonstrate their expertise in the field.

Yan Luo

Joseph Santarcangelo