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  • Provider Coursera
  • Cost Paid Course
  • Session Upcoming
  • Language English
  • Certificate Paid Certificate Available
  • Effort 4-9 hours a week
  • Start Date
  • Duration 7 weeks long
  • Learn more about MOOCs

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Overview

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The capstone project class will allow students to create a usable/public data product that can be used to show your skills to potential employers. Projects will be drawn from real-world problems and will be conducted with industry, government, and academic partners.

Syllabus

Overview, Understanding the Problem, and Getting the Data
-This week, we introduce the project so you can get a clear grip on the problem at hand and begin working with the dataset.

Exploratory Data Analysis and Modeling
-This week, we move on to the next tasks, exploratory data analysis and modeling. You'll also submit your milestone report and review submissions from your classmates.

Prediction Model
-This week, you'll build and evaluate your prediction model. The goal is to make your model efficient and accurate.

Creative Exploration
-This week's goal is to improve the predictive accuracy while reducing computational runtime and model complexity.

Data Product
-This week, you'll work on developing the first component of your final project, your data product.

Slide Deck
-This week, you'll work on developing the second component of your final project, a slide deck to accompany your data product.

Final Project Submission and Evaluation
-This week, you'll submit your final project and review the work of your classmates.

Taught by

Jeff Leek, Roger Peng and Brian Caffo

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Reviews for Coursera's Data Science Capstone
3.0 Based on 4 reviews

  • 5 star 0%
  • 4 star 25%
  • 3 stars 50%
  • 2 star 25%
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  • 1
Mark B
3.0 3 years ago
by Mark completed this course.
1 person found
this review helpful
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Dwayne D
4.0 2 years ago
by Dwayne completed this course.
The positive: Completion of this project requires most of the skills you will have learned in completing the prequisite courses.

The negative: If you're "like me" (inexperienced with NLP), you should start reading up on the basics (enough to know the challenges, available tools, prevalent techniques) 1-2 weeks before Week 1 of the course. If I hadn't done this, then I would not have given myself enough foundational understanding to understand what work(s) I should use as as my guiding examples (and why). Reading the course forums and reviews, I think many people who had trouble co…
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Anonymous
2.0 3 years ago
Anonymous is taking this course right now.
So disappointing, it feels somewhat unrelated to the material covered in the 9 courses in the Data Science Specialization, so I didn't feel adequately prepared for tackling the Capstone even though I carefully completed all pre-req courses. Also, the level of complexity of the problem (ie having to read multiple academic papers on NLP and computational linguistics) is not appropriate for a course that should be focused on teaching general, practical, applicable data science skills.
1 person found
this review helpful
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Colin K
3.0 3 years ago
by Colin completed this course.
2 people found
this review helpful
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  • 1

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