You will be glad to hear that (Anaconda+Jupyter Notebook+Python+visualization libraries) is what we have been teaching in CIS 2650 since the course was created. We have no plan to change it unless industry tells us otherwise. Agreed?

Anaconda + Jupyter Notebook + Python + visualization libraries, Say what? Business Analytics, many of our Supply Chain majors are BA minors, why?

CIS courses in our BA minor:

CIS 1020 (Business Computing), CIS 2640 (Business Analysis & Reporting), CIS 2650 (Programming for Data Analytics), CIS 3640 (Business Analytics), & CIS 4640 (Business Data Mining).

First, CIS 2650 is not just a “Python” class, but instead a Python class for analytics (big difference). In a traditional Python class, people teach Python straight for the whole semester with tons of syntax, data structure, software development, etc. That type of class is mostly designed for CIS majors. What we do is different. It is Python in a popular analytics platform (more technically speaking, it is Python in Jupyter, which is an analytics platform that data science & business analytics programs do).

The reason for this design is the following:

·      We studied the top skills in analytics jobs & Python was among the top skills.

·      The visualization libraries in Python can produce the kind of visualizations not available in Tableau & Power BI. Students will be able to differentiate themselves from other schools. 

·      Tableau & Power BI recently added Python or Python+Jupyter because certain Python analytics & visualization are not available in Tableau and Power BI. Using them together makes it a powerful analytics solution (e.g., the ability to transform visualization into implementable actions). 

Here are examples:
TabPy makes it possible to use Python scripts in Tableau calculated fields.:

PyCaret makes it possible to use machine learning in Tableau:

Python can create machine learning modules & create the visualization based on the predicated result.

·      All data scientists stress the importance of Python in analytics programs. Note, “data scientist” is one of the fastest growing career paths w/ escalating salaries because not enough people are good at this stuff.

·      Python are “R” are both number one & two in analytics, but Python is easier to learn compared to R.
·      Past experience in our SCM program shows that non-technical students are able to handle the content that we designed.
·      Python+Jupyter (or its variant) are used in Big Data (Hadoop, Microsoft Azure, Amazon AWS, etc.). It can also be used w/ SAP HANA, IoT, AI, Blockchain, & smart contracts to implement SCM visibility, & other SC related solutions.


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