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I chose one dataset from kaggle for my class project. this is the link for the dataset. https://www.kaggle.com/iabhishekofficial/mobile-price-classification

In this dataset, there are 20 features and one target variable called "Price_range". This target variable has four categories. Low Price, Medium Price, High Price, Very High Price. Now, this dataset is already encoded as follows: Low Price - 0, Medium Price-1, High Price-2, Very High Price-2

Now, as per my understanding, I think that this is clearly a classification problem because I am not predicting the direct prices of mobile phones, instead, I am predicting the category of mobile price whether it is low or medium or so on. Now the problem is my professor is telling me that this is not a classification problem, instead, it is clearly a regression problem. So, now please help me identify the right thing.

Although I do believe that this is the CLASSIFICATION PROBLEM, help me to find out the perfect situation for this problem.

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As you said in the question If you want predict the mobile prices then you can use regression because the prices will be continuous But if you want to predict the price category of the mobile then it definitely comes into classification.

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The link you provided has the title as a classification dataset, furthermore the label column is a categorical variable not a number value

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You're right. but my professor is telling me that this is the regression problem, what should I do?
You should say that it is a regression problem and solve it as the classification problem that it is.

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