About this course
To become an expert data scientist you need practice and experience. By completing this data science capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will also test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.
Unlike the rest of the Professional Certificate Program in Data Science, in this data science capstone course, you will receive much less guidance from the instructors. When you complete the project you will have a data product to show off to potential employers or educational programs, a strong indicator of your expertise in the field of data science.
About Data Science
Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science professionals apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence.
”Every company has big data in its future and every company will eventually be in the data business”.
- Thomas H. Davenport
Why Data Science is Important?
More and more companies are coming to realize the importance of data science, AI, and machine learning. Regardless of industry or size, organizations that wish to remain competitive in the age of big data need to efficiently develop and implement data science capabilities or risk being left behind.
What you will learn from this course?
This course on data science capstone is very different from previous courses in the series in terms of grading. There are three graded components to this course: the Movielens prep quiz (10% of your grade), the Movielens project (40% of your grade), and the choose-your-own project (50% of your grade, available to Verified learners only).
After completion of the data science capstone course you will be able to learn the following:
- How to apply the knowledge base and skills learned throughout the series to a real-world problem
- How to independently work on a data analysis project
- Fundamental R programming skills
- Statistical concepts such as probability, inference, and modeling and how to apply them in practice
- Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr
- Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio
- Implement machine learning algorithms
- In-depth knowledge of fundamental data science concepts through motivating real-world case studies
Syllabus of the data science capstone
The data science capstone project progresses through the course of two week
Data Science Capstone: Movielens Project (all learners)
- In this section, you will do a short preparatory quiz to familiarize yourself with the dataset and we’ll be using and then complete a project using a dataset from Movielens. After submitting your project, you will review projects from your peers.
Choose-Your-Own Project (Verified learners only)
- In this section, you will work on your own project using a dataset of your choosing. Your project will be reviewed both by your peers and by a staff TA.
Prerequisites for data science capstone
This course is part of the Professional Certificate Program in Data Science and they recommend the preceding courses in the series as prerequisites.
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Specification: Data Science Capstone from Harvard