Will AI really kill the tools we teach like Excel? From 2020, notice where AI was on the list. We are still holding firm on Predictive Data Analytics, ranked #2! https://lnkd.in/gthyAWf3. Every WMU SCM major now has to take this class (Excel on steroids). Our Business Analytics minor teaches Big Data w/ skill sets such as: 1. Advanced Excel (power query & pivot) & macros;
2. Data visualization (Tableau, Power BI & python w/ seaborn & matplotlib);
3. Data mining/RapidMiner, machine learning & data science;
4. Python & Jupyter notebook (data analytics & statistical libraries such as pandas, numpy);
5. Relational data models (Excel data model);
6. Graphic & statistical libraries (Seaborn, Matplotlib, Pandas, & Plotly).
So, will AI really kill the tools we teach like Excel?
Would you trust the developer who built your software with a 3rd party code generation tool? Maybe. We are not going to stop teaching Excel in very sophisticated ways. All of our supply chain majors are required to take: CIS 2640 Predictive Data Analytics (Excel on steroids): I get this kind of feedback often…https://lnkd.in/dQABdsXc.
However, our analytics faculty are on top of this AI wave. They have already built an AI course in our business college (CIS 5550) to cover all kinds of AI for business applications. The course is designed for non-technical students (a perfect fit for SCM types). After this course, AI embedded modules in existing courses will be added.
So, Excel + AI = more SCM success.
Per discussions w/ our CIS faculty, we all agree there is nothing wrong w/ using these code generators as long as you understand the generated code & know how to fix it when needed. Rarely will the generated code be enough to suit your needs. The more realistic scenario is to use the tool to generate the base code & modify it manually for the intended problems.
Many companies (especially on the SCM side) PROBABLY do not want their employees to use AI for any calculations like this. So, in all of the above scenarios, skills in our Adv Excel class (and all of our Business Data Analytics classes) are still relevant.
We have it covered with our students. Generative AI (e.g., ChatGPT, Google Bard, CoPilot, etc.) is a major focus in our new CIS 5550 course. “American college students are behind in using AI in their studies compared to their foreign counterparts.” https://lnkd.in/gngZxKry. Maybe not…This is the whole reason that we created our new AI course – to create AI awareness and skills, and it is designed for non-technical majors. We are offering the course again in the Spring 2025 semester. Per conversations with our CIS faculty…
https://lnkd.in/e2ngRKQc
Notice how Production and Supply Chain Management are NOT the front runners in AI adoption & also have the lowest demand for AI talent. Safe to say SCM has historically lagged behind other sectors in technology adoption? Note, many SCM hiring managers do not have a full understanding of the AI skill sets associated w/ a data analytics education.
Our SCM students told us many times that their hiring managers valued only the traditional Excel capabilities (lookup functions, pivot tables, etc. – that is NOT AI), & they greatly overlooked the opportunities from other analytical solutions (skill sets that our students & many employees have). This makes it a bit difficult to sell the analytical techniques that go beyond super advanced Excel, which would be our CIS 2640 class (Excel on steroids) – Applied Analytics Foundations.
For example, our data mining class is essentially a machine learning class for business, which is the core of AI. The course is designed to solve the problems that Excel falls short on.
https://www.linkedin.com/posts/sime-curkovic-61617a115_ai-adoption-is-growing-but-who-uses-it-and-activity-7148643252374487040–wYT?utm_source=share&utm_medium=member_desktop
Note (for college teaching), I would caution from combining too many AI “branches” (see screen shot) into specific single courses that are focused on functional disciplines (i.e., Marketing, Finance, etc.). These courses can be a very aggressive approach by combining too many branches of AI into one single course. You have to ask, do you want the course to be a general “overview” or a “skill-building” course? I would encourage all business disciplines to collaborate (rather than go solo) with their CIS/AI faculty. For us, we have multiple courses in the business college covering a variety branches of AI, so far:
1. AI Introduction: CIS 5550 – Artificial Intelligence in Business
2. Machine learning branch: CIS 4640 – Business Data Mining and CIS 6640 – Predictive Analytics and Data Mining
3. Automation and visualization branch: CIS 3640 – Visual Analytics and CIS 6500 – Visual Analytics
4. Big Data branch: CIS 5650 – Big Data Analytics
5. AI in Functional areas:
a. CIS 6410: Financial data analytics
b. MKTG 5980 – Artificial Intelligence in Food & Marketing
