ETEM 4100 - Data Analytics with Alteryx (QR)

(3) Credit Hours

The course content includes data extraction, data cleaning, data profiling, designing data processing pipelines including data transformation and standardization models, probability and regression models, the application of AI models (supervised and unsupervised learnings) including the use of Naïve Bayes, Support Vector Machine, K-Means Approach, K Nearest Neighbor, Neural Networks and Decision Trees. In addition, students will learn various prompt engineering techniques.This course will use a widely recognized industry tool called “Alteryx”. After successful completion of the course, students will be able to (1) perform data munging and exploratory data analysis, (2) apply the basics of ETL (Extract-Transform-Load) process, (3) perform both supervised and unsupervised learning experiments to make predictions on real-world based on historical data, (4) communicate business insights using real data, in both written and oral presentations, (5) construct writing, problem-solving, design, technical writing prompts with the help of prompt engineering.Spring semester. Junior standing. Differential course fee will be assessed.
General Education Category: Quantitative Reasoning