Here are some relevant and promising topics in the field of data science for your dissertation:

Topical issues could be 1. Overuse of technology and negative health effects. 2. How the church should integrate science with religion. 3. Artificial intelligence. 4. Problems with confidentiality related to technology and merging of datasets. 5. Lack of evidence for prayer and hence why does the church continue as it is when there is no evidence. 6. Information overload on the internet and deleterious effects as a result.

Your question, you are asking as a Data Science student, or you want to do a thesis that uses data science.

Carlos Jimenez-Gallardo Hi Carlos, I'm a Data Science student. I want to have a relevant topic related to this field for my dissertation.

Hi Navitha

1. you can compare ML models with Regression models and see the consistency of the fits, (many mention that ML models are black boxes, in my experience I have come up with similar models and in other cases highly divergent ones).

2. Temporal conditions of use of ML models, i.e., how long can I use ML based models, and how to realize that it loses accuracy (in regression we know and have procedures to evaluate, the accuracy of the model after some time of having used it).

3. Meta Analysis of ML models performed by professionals initiated in Data Science (too much use of AI).

4. analysis of the quality of estimation for data worked with unimodal distribution with independent variables or bimodal distributions.

5. in Big data, of all the V's used to define it, I have not seen standardized procedures for some like the V referred to Temporal VALIDITY, this is more abstract in analysis and I don't know if it is done. In this regard, the issue is how to work a variable measured over a long time, but the response conditions have changed..,

ML, Machine Learning

here are some ideas, keep in mind IDEAS,

I hope they will be useful

SUCCESS!!

I would like it very much if someone would study further on my new regression method!

https://www.physicsjournal.net/archives/2021/vol3issue1/PartA/3-3-11-339.pdf