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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.

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.

Good to know

Know what's good

, what to watch for

, 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

Data science capstone course with challenging final project

Learners say this challenging course is an excellent way to cap off a data science specialization, providing a real-world experience. The final project is a rigorous undertaking that requires students to apply all the skills learned throughout the program, including NLP, text mining, and statistical modeling. While some students found the lack of guidance frustrating, others appreciated the opportunity to work independently and develop their problem-solving skills. Overall, this course is highly recommended for those who want to gain hands-on experience in data science and demonstrate their abilities to potential employers.

The capstone project focuses on NLP and text mining, providing students with experience in these important areas.

"This capstone requires all the skills that you learned from the series of specialization in addition to self-learning about Natural Language Processing."

"It was amazing to learn something completely different from what I personally expected."

"This course was a very much useful course which helped me delve into the ocean of data science and to understand all the basic and slightly advanced topics and concepts "

The course provides students with an opportunity to apply their skills to a real-world problem and develop their problem-solving abilities.

"I've read a few negative reviews, saying it's not guided enough etc."

"I actually enjoyed finding out on my own how to tackle the problem and building a solution on my own."

"One step at a time. Very confused in the beginning. Gradually understood and learned."

Demanding but rewarding capstone project that tests students' abilities and provides a real-world experience.

"Challenging, useful - stretches the imagination as well as knowledge base and skill level."

"The course really tested me and pushed me to move past my limits to achieve something remarkable."

"Amazing course! The course really tested me and pushed me to move past my limits to achieve something remarkable."

Some students felt the lack of guidance in the final project was frustrating and made it difficult to complete.

"The course is really just a structure for the final project."

"Most learning and programming techniques for the capstone are self taught and require intense research and experimentation."

"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."

Career center

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

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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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.

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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.

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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

Good to know

Save this course

Reviews summary

Data science capstone course with challenging final project

Career center

Reading list

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