Data Science Course from Johns Hopkins University (Coursera)
This is a thorough course that covers every aspect of data science. This program's statistics component will teach you about statistical inference, or the process of drawing conclusions from data. It will cover all of the major inference theories (frequentists, Bayesian, and likelihood). Roger D. Peng, PhD Associate Professor of Biostatistics, Brian Caffo, PhD Professor of Biostatistics, and Jeff Leek, PhD Associate Professor of Biostatistics created and teach the program.
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.
Skills you will gain:
- Github, Machine Learning, R Programming, Regression Analysis, Data Science, Rstudio, Data Analysis, Debugging, Data, Manipulation, Regular Expression (REGEX), Data Cleansing, Cluster Analysis
The 10 courses that comprise this Data Science program are:
- 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 Project
Rating : 4.5/5.0
Enroll here: coursera.org/specializations/jhu-data-science
