Syllabus for SSE 644
Engineering Data Analysis and Visualization
Fall Semester 2019
This course will be extensively modified from past offerings,
using Machine Learning (ML) techniques (not including neural nets/deep
learning) from Scikit-Learn for analysis, and MatPlotLib (from SciPy)
for visualization. The programming language will remain Python.
The syllabus for this course will be available at or before the
beginning of this course.
A rough outline of the course:
- Start by installing the latest version of the
Anaconda Python (3.x) Distribution .
- Start learning Python by starting to program
the SciPy Lecture Notes (section 1.2) at the command line.
- Stop using the command line well before you finish section 1.2 of the SciPy Lecture Notes.
Start learning Jupyter Notebooks (already installed by Anaconda) by
switching your programming to them.
This Jupyter tutorial, or another, may well be helpful. (Jupyter will increase
your productivity, so do not put this transition off.) Finish section 1.2.
- Visualization: After doing at least parts of sections 1.3 - 1.5 of the SciPy Lecture Notes,
start learning Matplotlib, especially from the .
Tutorials and Examples.
- Analysis: Start learning Scikit-Learn, especially from the
- More detail will be available later.
- My Name: Dr. Paul E. MacNeil
- My E-mail: firstname.lastname@example.org
- My Office Phone: 478 301-2185
- US Mail:
- Dr. Paul E. MacNeil
- School of Engineering
- Mercer University
- 1501 Mercer University Drive
- Macon, GA 31207
Back to Top