You as a data scientist has been hired by a company to help the managers in extracting hidden knowledge from datasets. The hidden knowledge should reveal interesting information that helps the business to grow. For example, use of sentiment analysis/association rules/prediction models/clustering techniques can take advantages of AI to develop the business Key Performance Indicator (KPI). You may also work on some benchmark dataset related to health or incidents i.e., Titanic dataset. Students will create a process in Rapid Miner generating knowledge from a dataset that will uploaded on Moodle. The dataset will include numbers, text, and other labels. You may use different techniques such as sentiment analysis, association rules, ANN, DT, FT, K-means, SOM, and etc to produce insights about the dataset and conclude with useful advices about the business. Students need to use different visualization techniques to analyse and show the space of the problem. Students are expected to implement minimum 4 techniques. Beside the report, student should upload a single process file that include all the 4 techniques. I am after the RPM file, what you did and how you did use those four techniques in rapidminer tool. You can use any dataset as an example to show this. It is explicitely needs to be done in RapidMiner tool and cannot use any other programming languages like R, Python,etc. and can use any dataset from Kaggle.com. Please mention in comment, if you need more info then what sort of info is unclear. The subject is Artificial Intelligence and a Bachelor's degree course.