My Statement of Accomplishment from Machine Learning course of Coursera

Published on: August 26, 2012

It was hard to finish all the material on time and more when I started the course two or three weeks late and of course I had only the weekends to see the lectures, take some notes (I don’t know how to study without my own handwrite notes) and finish all the assessments. However, the course of Machine Learning offered by the platform of open-learning Coursera and given by Andrew Ng, Professor of Computer Science of Stanford University was one of the most incredible learning experiences of my life.

Here is my Statement of Accomplishment document:

The following is a the syllabus for the class:

• Introduction to Machine Learning. Univariate linear regression. (Optional: Linear algebra review.)
• Multivariate linear regression. Practical aspects of implementation. Octave tutorial.
• Logistic regression, One-vs-all classification, Regularization.
• Neural Networks.
• Practical advice for applying learning algorithms: How to develop, debugging, feature/model design, setting up experiment structure.
• Support Vector Machines (SVMs) and the intuition behind them.
• Unsupervised learning: clustering and dimensionality reduction.
• Anomaly detection.
• Recommender systems.
• Large-scale machine learning. An example of an application of machine learning.

I know that 20th August a new course is started. If you have interest on the topic I really recommend it.