Which are the top 5 most popular Data Science research topics?
Asked by Sudheer Yadav 12 months ago
Recruiting Manager, Operations at Apple
Data science courses are very popular in current times. Out of all other subject areas, the most number of applications applied for the year 2020-2021 were data science courses. It is only normal to see questions related to data science topics now. I assume by research topics you are asking in regard to the capstone project right?
Well, data science consists of many things like machine learning, AI, algorithms, detection, big data etc. Mentioning every topic is not ideal and it’ll take days just to narrow it down. So, for popular data science research topics, I have five different suggestions. I‘ll try to divide it up into beginner, intermediate and advanced levels. This way, you can get an idea as a whole.
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- Fake News Detection (beginner)
- Gender and Age Detection with Data Science (intermediate)
- Customer Segmentations (advance)
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- Impact of artificial intelligence (AI)
- Implementing big data to understand consumer behavior
The first topic, Fake News Detection in data science is not that hard to understand. Many students even build it during their studies. All you have to do here is have a strong command of Python and that's it. Take it as a research topic if you have just started with data science. You need to try different features on classifiers to see which are more effective and then use them. The concept is really simple.
Gender and Age Detection with Data Science is a very crucial topic in this subject. Data science is used very widely for decision-making stuff. Based on factors like gender and age, decisions are made to strengthen the business. You can prepare your project either as a POV of a business organization or a data science subject itself. This topic is most suitable for intermediate people that are well familiar with data science and still learning.
Customer Segmentation is an advanced-level topic in data science. It is basically concerned with digital marketing and is a very up & advanced way to target an audience. Before initiating a marketing campaign, the organization needs to know what grounds to advertise it on. Like if I start promoting aftershaves in a teenage-specific area it will be disastrous. Customer segmentation is all about creating subgroups with similar characteristics to achieve the most out of every little thing. It is one of the most popular project topics in data science.
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The last two options are universal topics in data science. Basically, from a beginner to an advanced person, anyone can choose these two topics for a project. The best thing there is that you get free reign to include anything as it is not a targeted audience topic. Anyway, I hope you find all this relevant. In case you need some extra assistance, just let men know.
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