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Data Science Capstone

Roger D. Peng, PhD, Jeff Leek, PhD, and Brian Caffo, PhD

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.

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What's inside

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.

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Read about what's good

what should give you pause

and possible dealbreakers

Teaches skills for making public data products

Taught by instructors who are recognized for their work in predictive analytics and data science

Builds a strong foundation for students entering the field of data analytics

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Reviews summary

Applied data science capstone project

According to learners, this capstone course offers a positive opportunity to apply data science skills to a real-world problem. Students often found the project challenging yet rewarding, appreciating the chance to build a data product and slide deck suitable for portfolios, simulating industry tasks. Many highlighted the value of synthesizing knowledge from prior courses and following the structured approach through EDA, modeling, and prediction. Key areas for improvement noted by reviewers include a warning about the limited direct instructor guidance and some negative experiences with the inconsistent quality of peer reviews. The course involves a substantial workload.

Requires a significant time commitment.

"This project required a lot more work than I initially anticipated."

"Be prepared to dedicate a considerable amount of time to complete the project requirements."

"I felt quite rushed trying to finish everything by the deadlines."

Mixed experiences with the peer review process.

"Peer review was sometimes helpful, I got good feedback..."

"The quality of peer reviews varied a lot; some were useless or unfair."

"The peer grading system was frustrating at times; I received low scores for unclear reasons."

"Getting inconsistent or unconstructive feedback from peers was a downside."

Produces valuable assets for showcasing skills.

"Building the data product and slide deck felt like preparing for a real job task, which is great for my portfolio."

"The final deliverables are perfect for demonstrating skills to potential employers."

"Having a completed data product and presentation is a major plus for job applications."

Effectively combines skills from prior courses.

"This course does an excellent job of helping you synthesize concepts learned throughout the specialization."

"The structure really forces you to apply skills from all the preceding courses."

"It helped pull together all the pieces I had learned before into a cohesive project."

Work on a practical, real-world data science problem.

"Great capstone project! I loved working on a real-world problem."

"Applying everything I learned to a real problem was the most valuable part for me."

"The project felt very realistic and relevant to industry work."

"It was challenging but rewarding to tackle a problem with a real dataset."

Some confusion regarding final project requirements.

"I could have used more detailed guidance or examples for what was expected in the data product."

"The criteria for the final slide deck and data product weren't always as clear as I'd hoped."

"Wish the expectations for the deliverables were more explicitly defined upfront."

Reviewers noted minimal direct instructor support.

"There was very little instructor interaction or guidance throughout the project."

"I wish there had been more support from the course staff when I got stuck."

"Felt like I was mostly on my own to figure things out with minimal guidance."

"Interaction with instructors was quite limited."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Science Capstone with these activities:

Follow a data science tutorial

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Following a data science tutorial will help you to learn new skills and to reinforce what you have already learned. It will also allow you to get hands-on experience with data science tools and techniques.

Browse courses on Data Science

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Find a data science tutorial that interests you
Follow the steps in the tutorial
Complete the exercises in the tutorial
Apply what you have learned to your own projects

Review Applied Predictive Modeling

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This book covers the core concepts, methods, and algorithms used in predictive modeling. By providing a solid foundation, you will be better prepared to build accurate and reliable models from your data.

View Tidy Modeling with R: A Framework for Modeling... on Amazon

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Read Chapter 1: Introduction
Work through the exercises in Chapter 1
Summarize the key concepts of Chapter 1 in your own words

Create a data visualization

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Creating a data visualization will help you to communicate your findings to others in a clear and concise way. It will also allow you to explore your data from a different perspective.

Browse courses on Data Visualization

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Choose a dataset to visualize
Clean and prepare the data
Choose a visualization type
Create the visualization
Evaluate the effectiveness of the visualization

Five other activities

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Attend a data science workshop

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Attending a data science workshop will allow you to learn new skills and to reinforce what you have already learned. It will also allow you to get hands-on experience with data science tools and techniques.

Browse courses on Data Science

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Find a data science workshop that interests you
Register for the workshop
Attend the workshop and learn new skills
Apply what you have learned to your own projects

Start a personal data science project

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Working on a personal project will allow you to apply the skills and knowledge you are learning in this course to a real-world problem. This will help you to solidify your understanding of the material and to develop your problem-solving skills.

Browse courses on Data Science

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Choose a data science project that you are interested in
Gather data for your project
Explore the data and identify patterns
Build a predictive model
Evaluate the performance of your model

Practice data science coding challenges

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Practicing data science coding challenges will help you to improve your programming skills and to learn new algorithms and techniques.

Browse courses on Data Science

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Find a data science coding challenge website
Choose a challenge and work through it
Compare your solution to others
Learn from your mistakes

Attend a data science meetup or conference

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Attending a data science meetup or conference will allow you to network with other data scientists and to learn about the latest trends in the field.

Browse courses on Data Science

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Find a data science meetup or conference in your area
Register for the event
Attend the event and network with other data scientists
Learn about the latest trends in data science

Create a blog post or article about a data science topic

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Writing about a data science topic will help you to solidify your understanding of the material and to improve your communication skills. It will also allow you to share your knowledge with others.

Browse courses on Data Science

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Choose a data science topic that you are interested in
Research the topic and gather information
Write a blog post or article about the topic
Publish your blog post or article
Promote your blog post or article on social media
Respond to comments and questions on your blog post or article

Career center

Learners who complete Data Science Capstone will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers ensure that data is properly stored, processed, and accessible. This course will teach the skills and knowledge needed to get data ready for analysis, a core responsibility of Data Engineers.

See salaries and explore the career path for Data Engineer

Data Analyst

Data Analysts are responsible for gathering, cleaning, and analysing data. The skills and knowledge taught in this course align with these responsibilities.

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Machine Learning Engineer

This course will teach the skills and knowledge needed to build and evaluate a prediction model, a key aspect of a Machine Learning Engineer's role.

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Data Scientist

Analysing data is a core aspect of data science, as described in the course's description. This course will teach the skills and knowledge needed to successfully analyse data.

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Statistician

This course will teach the skills and knowledge needed to conduct exploratory data analysis, a key responsibility of Statisticians.

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Business Analyst

Business Analysts use data to understand and improve business processes. This course will teach the skills and knowledge needed to analyse data and communicate findings, both core responsibilities of Business Analysts.

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Data Science Consultant

Data Science Consultants use their expertise to help organisations solve problems and make better decisions. This course will teach the skills and knowledge needed to build a foundation for a career as a Data Science Consultant.

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Software Engineer

Software Engineers design, develop, and maintain software applications. The skills and knowledge taught in this course may be useful in developing software that uses data.

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Product Manager

Product Managers are responsible for the development and launch of new products. This course will help build a foundation for understanding how to use data to make better product decisions.

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Market Researcher

Market Researchers use data to understand consumer behaviour and market trends. This course may help build a foundation for understanding how to use data to analyse market research.

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Quantitative Analyst

Quantitative Analysts use data to make investment decisions. This course will teach the skills and knowledge needed to analyse data, a core responsibility of Quantitative Analysts.

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Financial Analyst

Financial Analysts use data to analyse financial performance and make investment recommendations. This course will teach the skills and knowledge needed to analyse data, a core responsibility of Financial Analysts.

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Operations Research Analyst

Operations Research Analysts use data to improve the efficiency of operations. This course will teach the skills and knowledge needed to analyse data, a core responsibility of Operations Research Analysts.

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Actuary

Actuaries use data to assess risk and uncertainty. This course will teach the skills and knowledge needed to analyse data, a core responsibility of Actuaries.

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Data Journalist

Data Journalists use data to tell stories and inform the public. This course may help build a foundation for understanding how to use data to create compelling stories.

See salaries and explore the career path for Data Journalist

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Science Capstone.

The Elements of Statistical Learning

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Classic textbook on statistical learning. It provides a thorough introduction to the fundamental concepts of machine learning, including supervised and unsupervised learning, regression, and classification.

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Kindle Edition

$$$

Tidy Modeling with R

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Provides a comprehensive overview of predictive modeling techniques, including data preparation, model selection, and evaluation. It valuable resource for both beginners and experienced data scientists.

Data Science Capstone

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Applied data science capstone project

Activities

Career center

Reading list

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