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Texts

Learning IPython for Interactive Computing and Data Visualization, by Cyrille Rossant, Packt ISBN 978-1783986989 (2015) (Required)

IPython Interactive Computing and Visualization Cookbook, by Cyrille Rossant, Packt ISBN 978-1783284818 (2014) (Required)

Software

• The Anaconda Python (version 3) distribution, including the following Python packages/frameworks:
• Spyder (Integrated Development Environment [IDE])
• IPython (interactive and collaborative computing)
• NumPy (math)
• SciPy (scientific and technical computing)
• Matplotlib (plotting/visualization)

• Warning: Do _NOT_ "mess with" any existing Python installation on your computer. If you do, expect your operating system to stop working, and for the "fix" to be a real pain, at best. You might have to reinstall your OS from scratch.

  You can install Anaconda without messing up the Python installation that came with your OS, and on which your OS is probably dependent.

• Git, which you can obtain by installing either Bitbucket (my recommendation) or Github (also good).
• Bitbucket and Github are both Distributed Version Control Systems (DVCS). To do collaborative computing, _all members of the same team must use the same DVCS.
• Installing either DVCS (making sure that you get the Git version, not the Mercurial or other version), will give you Git, which you will need to download some code and data files.

Other Resources

The Official Python tutorial.

The SciPy Lecture Notes, especially Chapter 1, "Getting started with Python for Science".

The code and data files for Learning IPython for Interactive Computing and Data Visualization Please see page xi of this book for instructions on receiving this code.

The code and data files for IPython Interactive Computing and Visualization Cookbook. Once you have the Git version of Bitbucket or Github installed, go to the command line/ terminal and enter:

• git clone https://github.com/ipython-books/cookbook-code.git to get the code, and
• git clone https://github.com/ipython-books/cookbook-data.git to get the data.
• Note that, as you use the code, you will need to move the data file(s) into the appropriate code's directory.
• Also note that, because of changes to widgets in IPython, you will need to change the code in the last cell of 01_notebook.ipynb in accordance with https://github.com/ipython-books/cookbook-code/issues/20.

You will need a suitable computer. The University's Computer Recommendations are appropriate for this course for Windows and OS X. If you use the Linux operating system this course, the recommendations for Windows computers will also be suitable for Linux.

Please see the Online Learning page for more information regarding expected student student access to the internet, and corresponding software.

Please see the Mercer's Distance Learning page for more information regarding expected student student access to the internet, and corresponding software.

Course Description

Visualization and analysis of engineering data via collaborative computing using the Python programming language and some of its many application frameworks. Python programming is covered from the beginning, but at a rapid pace.

Students in a single learning community will use the same tools (Python 3, Anaconda, IPython, NumPy, SciPy, and Matplotlib) to develop and demonstrate their capabilities in these topics.

This course is one of our courses in Data Science.

This Online Learning course begins on August 22, 2017 at 12:00 am Eastern time. All assignments are due by the end (11:59:59 pm) of the specified calendar day in the Eastern time zone. This course ends at 11:59:59 pm on December 11, 2017, in the Eastern time zone.

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Course Objectives

Breadth and Depth in Defining, Analyzing, and Solving Complex Problems:

• After successfully completing this course, you should be able to demonstrate a basic capability to apply collaborative computing, and data analysis and visualization to solve complex problems.

Communicate Technical Aspects of the Solution for Complex Software Engineering Problems to a Technical Audience:

• After successfully completing this course, you should be able to demonstrate a basic ability to communicate regarding the application of collaborative computing, and data analysis and visualization to a technical audience.

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Prerequisite(s)

SSE 550 or permission of the professor.

Please see the Online Learning page for more information regarding expected student abilities and aptitudes.

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Class Location

• This course is entirely online.
• Please see the Canvas page for information regarding access to Canvas, Mercer's online learning system.

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Grading

Item	Percent of Term Grade
Direct Activity Report 1	3
Direct Activity Report 2	3
Direct Activity Report 3	4
Project 1	30
Project 2	30
Project 3	30

Credit will be given only for original work.

The Mercer University Honor Code, including its provisions for academic honesty (including plagiarism), applies to all Mercer students.

Project reports are to be submitted complete, not as incremental partial submissions.

All course work time is categorized as either Direct or Non-Direct (but not both). More information about the Direct and Non-Direct categories is contained in the Direct and Non-Direct and Report Logs. Please read these pages very carefully.

Instruction Time

Federal and regional accreditation requirements stipulate that a 3-credit hour course must include 150 minutes of direct instruction time per week. For this course, that direct instruction time includes"

• Collaborative discussions with other students regarding the content of readings assigned for the course.
• Collaborative discussions with other students regarding the content that goes beyond readings assigned for the course, but is not part of work on the projects assigned on the syllabus.
• Collaborative development of generic technology that may be useful for your project(s), but is not, in its generic form, part of your project.

In addition to the 150 minutes of direct instruction time each week, students are expected to spend a minimum of 300 additional minutes per week completing reading and writing assignments:

• Doing the assigned reading.
• Working on the projects assigned on the syllabus.

More information about the Direct and Non-Direct categories is contained in the Direct and Non-Direct and Report Logs web pages. Please read these pages very carefully.

All deliverables (Activity Reports and Project Reports) are due on their assigned dates.

• Deliverables submitted no more than one day late may be graded, but with a 10 point penalty .
• Deliverables submitted more than one day (24 hours) late will receive a grade of zero.
• The Non-Direct Activity reports are part of the project reports. The Non-Direct Activity reports do not receive a separate grade, but are used to help in evaluating your project reports.

Use the Report Logs to help you to manage your time and keep on schedule. You should schedule your work evenly throughout the term.

More information about project grading is contained in the General Project Rubric .

If you have a question about any of this, please ask.

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Assignments

• Purpose of projects:
• Use the projects to develop your capabilities, and
• Use the projects to demonstrate your capabilities.
• Deliverables for all projects:

  All course work time is categorized as either Direct or Non-Direct (but not both). Read Direct and Non-Direct and Report Logs before continuing. Please read these pages very carefully.

  • All Direct Activity Reports include a Direct Activity Log, and may include additional supporting material at your discretion.

  • All Project Reports include a Non-Direct Activity Log, in addition to your work on the project.

  • Projects shall be delivered via the course FTP site.
  • Project reports should each be a single, standalone .pdf document, with the Bookmark feature used to support easy document navigation. Note that both MS Word and LibreOffice (which is free open-source software) support bookmarks, and will carry the bookmarks over into the pdf document when they convert your .docx, .odf, or whatever file type to PDF.
  • Project reports should focus on the development and/or maintenance that you actually do. Reports should not focus on summarizing or explaining the text or other materials.
  • Inclusion of screenshots demonstrating your work, and code you actually wrote for the project, are appropriate. Long code listings can be placed in appendices if doing so does not interfere with you presenting your work on that code in the body of the text.
  • Your report should be organized in such a way as to make the topics that you want credit for covering easy to find, and demonstrate your capabilities clearly and convincingly. Everything you want considered for credit, including code and tests (including test results), should be included in the report.
  • Each project can be a single, integrated project that tries to actually do something, or a collection of exercises that demonstrate your capabilities but don't accomplish anything else, or any combination of these two alternatives that you find convenient, unless otherwise specified in the assignment.
  • You may include other material outside of the report (on the FTP site), if you wish, but this material may or _may not_ be considered in evaluating your work.
  • For each capability that you demonstrate within a report or major section of that report, you may present only the final result of your work; you need not demonstrate every step in the development of that result.
• Some suggestions for doing a project are contained in the One Way to Do a Project page.
• Project 1 (Solo or Team)
• Read http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261 and http://www.nature.com/naturejobs/science/articles/10.1038/nj7493-523a Run the examples at http://www.nature.com/news/ipython-interactive-demo-7.21492. Nothing from this work goes into your project report, but you will not understand what we are trying to do without this reading and code execution.
• Install Anaconda for Python 3.6. Be careful; the default Anaconda download is for Python 2.7. Make sure you download and install the Python 3.6 version.
• Work your way through "Learning IPython for Interactive Computing and Data Visualziation":
• Start at the beginning of the book.
• Work your way through the section "Distributing tasks on several cores with IPython.parallel" in Chapter 5.
• Read the rest of this book.
• Note that Chapter 1 includes, "A crash course in Python", which will get you started with Python programming. You can also use the official Python tutorial as needed; see Other Resources above.
• Project 2 (Solo or Team)
• For Projects 2 and 3 of this course, use "IPython Interactive Computing and Visualization Cookbook" as your text.
• Develop and demonstrate your capabilities in the topics covered in Chapters 1- 3.
• Create a project of your own choosing, and develop it. It should be an IPython notebook project, emphasizing data analysis and/or visualization using the Python libraries referenced above. You may use one or more of the textbook recipes for inspiration if you wish, but you are free to develop a project unrelated them if you wish.
• For this project, it is better if your code is interactive.
• Using GIT (Chapter 2 of the text) for collaborative work with your team is a good idea, but not required. Either GitHub or Bitbucket is fine, but everyone on the team has to use the same version control repository (GitHub or BitBucket)!
• Imagine that this work will be shown to the hiring manager for a job that you really want, and that this manager needs these data visualization and/or analysis capabilities. Show how well you can do!
• Skim the rest of the book, with an eye to what you might do for Project 3.
• Project 3 (Solo or Team)
• For Project 3 of this course, use "IPython Interactive Computing and Visualization Cookbook" as your text.
• Develop and demonstrate your capabilities in advanced topics in data analysis and visualisation, using the remainder of the book (after Chapter 3) as a guide.
• If you have questions about this, please raise them via the course listserv.
• Implementation Language
• Python 3.6
• Please raise questions and issues via the course listserv.

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Additional Information

• Asynchronous Learning Nets (ALNs)
• • Self Study: You study the texts and any other course study material on your own(team).
  • Collaborative Projects: After your self-study, you collaborate (via the Internet [email]) with your partner(s) to produce a team product. Your collaborative work is substantial, asynchronous, and rapid.
  • This course is an online learning course. Please read this Online Learning web page regarding online learning in this course and this program.

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• What Do I Do?

• Subscribe to the course email listserv before the second day of class. Your professor will tell you how to do this.
• Study the assigned material.
• Write and read email messages about ideas, problems and solutions to do with the assigned study material.
• Do the assigned work, deliver the assigned deliverables.
• Write and read email messages (to/from the listserv) about ideas, problems, projects, and solutions to do with the assigned homework.
• Review the deliverables produced by other people.

Changes to this Syllabus:

There will be changes to this syllabus, so check back frequently, and don't forget to hit "Reload" or "Refresh".

Schedule of Assignments and Events (tentative)

Start Date	End Date	Activity/Event
August 22, 2017	December 11, 2017	Course in Progress
	August 22, 2017	Subscribe to the course listserv.
	September 18, 2017	Direct Activity Report 1 due
August 22, 2017	October 4, 2017	Work on Project 1
	October 4, 2017	Project 1 due
	October 30, 2017	Direct Activity Report 2 due Project 2 due
	December 11, 2017	Direct Activity Report 3 due Project 3 due Course ends

Notes: The course begins at midnight (12:00 am) on the first day of class (see schedule above), and ends at 11:59:59 pm on the last day of class. Assignments are due at any time during the day specified on the schedule, that is, before 11:59:59 pm on that day. All times are Macon, Georgia (Eastern time zone) times.

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Contact Information

• My Name: Dr. Paul E. MacNeil
• My E-mail: macneil_pe@mercer.edu .
• OfficeHours
• My Office Phone: 478 301-2185
• US Mail:
 
• Dr. Paul E. MacNeil
• School of Engineering
• Mercer University
• 1501 Mercer University Drive
• Macon, GA 31207

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Important Additional Information:

"Firearms/weapons are not allowed in Mercer University campus or Regional Academic Center (RAC) facilities except when required for students who are in uniform (police, law enforcement officers, etc.) in an official duty status. All other weapons are prohibited including, but not limited to, hunting weapons, BB guns, stun guns, air rifles, air pistols, paintball guns, bowie knives, daggers, dirks, slingshots, leaded canes, metal knife sharpeners, switchblade knives, blackjacks, metallic knuckles, and any sharp, pointed or edged instrument (except instructional supplies, unaltered nail files and clips, and tools used solely for preparation of food, instruction, and maintenance). All fireworks or explosives (defined as any substance prepared for the purpose of producing visible or audible effects by combustion, explosion, or detonation) are forbidden." https://police.mercer.edu/

“Students requiring accommodations for a disability should inform the instructor at the close of the first class meeting or as soon as possible. The instructor will refer you to the ACCESS and Accommodation Office to document your disability, determine eligibility for accommodations under the ADAAA/Section 504 and to request a Faculty Accommodation Form. Disability accommodations or status will not be indicated on academic transcripts. In order to receive accommodations in a class, students with sensory, learning, psychological, physical or medical disabilities must provide their instructor with a Faculty Accommodation Form to sign. Students must return the signed form to the ACCESS Coordinator. A new form must be requested each semester. Students with a history of a disability, perceived as having a disability or with a current disability who do not wish to use academic accommodations are also strongly encouraged to register with the ACCESS and Accommodation Office and request a Faculty Accommodation Form each semester. For further information, please contact Katie Johnson, Director and ADA/504 Coordinator, at 301-2778 or visit the ACCESS and Accommodation Office website at http://www.mercer.edu/disabilityservices.”

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Accreditation: Mercer University is accredited by SACSCOC.