Integrating Business Analytics in Mechanical Engineering Education: Evaluating the Outcome of a Value-Added Course
DOI:
https://doi.org/10.16920/jeet/2026/v40i1/26140Keywords:
Mechanical Engineering Department, K.k.wagh Institute Of Engineering Education And Research, Savitribai Phule Pune UniversityAbstract
Optimizing strategies with help of data is the only way to do business and business analytics plays a key role in it. This research tests the success of a course designed around adding value to the student's program in the field of business analytics, using a blend of Advanced Excel and Python with a particular focus on Business Analytics. Advanced Excel offers tools like the Pivot Table, Data Analysis ToolPak, Solver and VBA Macros for data management, while Python grabs the tools Pandas, NumPy, Matplotlib, and machine learning frameworks like Scikit-learn and TensorFlow for analytics. To show how all these tools could be integrated for the purpose of business intelligence, a mini project to predict sales in the auto industry was conducted that used Exploratory Data Analysis (EDA) and regression modeling. Student performance can be analyzed quantitatively with the finding that there is a significant increase in the student quiz score, after receiving hands-on training, the quiz score is 84.2% as compared to 62.5% before hands-on training. An improvement paradigm is confirmed by the paired t-test (t = 4.76, p < 0.001). Feedback analysis indicated that 92.89% of students indicated that Python was useful in their predictive modeling and 87.23% said that working with advanced excel helped them improve in data interpretation. Overall, the results demonstrate the success of value-added courses in aligning academic studies and training with the needs of the industry and building of competencies needed to take data-based decisions in real-life situations.
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