Michelle Lynn Gill, Ph.D.
Biophysicist and Data Scientist
Links are provided to completion certificates.
This is a five course specialization utilizing Python and TensorFlow that teaches theoretical and practical aspects of deep learning.
- Neural Networks and Deep Learning: Certificate
- Improving Deep Neural Networks: Certificate
- Structuring Machine Learning Projects: Certificate
- Convolutional Neural Networks: Not Yet Released
- Sequence Models: Not Yet Released
Stanford University, Andrew Ng
This eleven-week course course is focused on the theoretical foundations of machine learning and includes weekly lectures, quizzes, and graded homework. Matlab/Octave is used. Certificate
Mathematical Biostatistics Bootcamp I
Johns Hopkins University, Brian Caffo
This is a challenging, four-week statistics course utilizing biomedical case studies as a teaching basis. Certificate
Data Science Specialization
Johns Hopkins University, Jeff Leek, Roger Peng, and Brian Caffo
This is a nine course specialization with additional capstone project. Each four-week course involves weekly lectures and quizzes, as well as peer-assessed projects. The R programming language is used.
- The Data Scientist’s Toolbox: Certificate
- R Programming: Certificate
- Getting and Cleaning Data: Certificate
- Exploratory Data Analysis: Certificate
- Reproducible Research: Certificate
- Statistical Inference: Certificate
- Regression Models: Certificate
- Practical Machine Learning: Certificate
- Developing Data Products: Certificate
Machine Learning Foundations Specialization
University of Washington, Emily Fox and Carlos Guestrin
A machine learning specialization utilizing Python as the foundation language. Each course involves weekly lectures, quizzes, and homework.