For this assignements, i have to solve a data mining problem using a data set fr

For this assignements, i have to solve a data mining problem using a data set from online sources (using python) and report the method , process and results. Do not use association rule , decisison tree or k -means.
For the presentation format (it is a 20 min recorded presentation, which i need a script that can read up to 20 min) with 20 slides so bascially , one minute per slides
and in the presentation format there should be
1. Title
2. An introduction to the application problem to be solved. What data is available and
what results are expected.
3. The type of the data mining methods, such as classification, clustering, outlier
detection, that can be used to approach the problem, and why.
4. An introduction of the data mining method used to solve the problem
5. The procedure of solving the problem by using the data mining method
6. The results and discussions
7. Conclusion
For the marking criteria, #4
What is the criteria for “challenging or insightful”? Does challenging mean a difficult data mining method needs to be used? or does it mean to pick a dataset from the competitions page on Python?
The meaning of “challenging” is twofold here.
1) The problem is a well-considered one and is a real problem and very close to a real problem (in contrast to a textbook or internet illustrative problem.)
2) The solution is not a simple “plug and play” — here is my data set and here are the results after applying the algorithm. A student shows a careful choice of an algorithm and parameters to achieve the best results and interpret the results. Or a student modifies an algorithm or combines algorithms to achieve the best results. If a student has tried a number of methods, and eventually chooses one. It is better to discuss why the previous ones are not good and the current one gives the best results. This will enhance the quality of the assignment.
The meaning of “insightful” is a deep and correct understanding of applications and solutions provided.
>>Also, how is “difficulty of the topic” measured? Does the dataset have to meet a certain criteria for it to be “difficult” for example picking datasets with more continuous variables instead of categorical variables?