Data Science at Scale - Capstone Project
Apply comprehensive data science skills to solve real-world problems through a hands-on predictive modeling project.
Apply comprehensive data science skills to solve real-world problems through a hands-on predictive modeling project.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science at Scale Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
3.8
(25 ratings)
2,521 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Design and implement end-to-end data science solutions
Develop predictive models for real-world problems
Apply data wrangling and feature engineering techniques
Evaluate and improve model performance
Create comprehensive project documentation
Skills you'll gain
This course includes:
5.5 Hours PreRecorded video
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
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There are 6 modules in this course
This capstone project course challenges students to apply the entire data science pipeline to a real-world problem. Working with actual stakeholders through Coursolve, students tackle the prediction of building condemnations. The project encompasses data preparation, organization, transformation, model construction, and results evaluation. Students learn to handle ambiguous requirements, develop feature engineering strategies, and create practical solutions that can be deployed in real-world scenarios.
Project A: Blight Fight
Module 1 · 30 Minutes to complete
Week 2: Derive a list of buildings
Module 2 · 1 Hours to complete
Week 3: Construct a training dataset
Module 3 · 1 Hours to complete
Week 4: Train and evaluate a simple model
Module 4 · 1 Hours to complete
Week 5: Feature Engineering
Module 5 · 1 Hours to complete
Week 6: Final Report
Module 6 · 1 Hours to complete
Fee Structure
Instructor
Director of Research
Bill Howe is the Director of Research for Scalable Data Analytics at the University of Washington's eScience Institute and holds an Affiliate Assistant Professor position in Computer Science & Engineering. He leads research focused on data management, analytics, and visualization systems tailored for scientific applications. Howe has received multiple awards from Microsoft Research and honors for his contributions to scientific data management.
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3.8 course rating
25 ratings
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