Course description
Data Science Specialization
This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you'll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.
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Upcoming start dates
Suitability - Who should attend?
You should have beginner level experience in Python. Familiarity with regression is recommended
Outcome / Qualification etc.
What You Will Learn
- Use R to clean, analyze, and visualize data.
- Navigate the entire data science pipeline from data acquisition to publication.
- Use GitHub to manage data science projects.
- Perform regression analysis, least squares and inference using regression models.
Training Course Content
- The Data Scientist's Toolbox
- R Programming
- Getting and Cleaning Data
- Exploratory Data Analysis
- Reproducible Research
- Statistical Inference
- Regression Models
- Practical Machine Learning
- Developing Data Products
- Data Science Capstone
Course delivery details
This course is offered through Johns Hopkins University, a partner institute of Coursera.
Suggested pace of 7 hours/week
Expenses
Please visit the Institute website for more information about tuition fees