My question is related to machine learning. Please answer the following

The CoWax application receives several requests from the Indian citizens for registering their details and slot booking for the vaccination. This data is captured in database of the application as listed below format.

$$ User ID $($Unique identification for each user of application$)$

$$ Aadhar ID of user who has registered

$$ Mobile number

$$ Name

$$ Secret Code

$$ Year of Birth

$$ Photo ID $(3$ types : Aadhar, PAN, Passport$)$

$$ ID Number

$$ Type of vaccine $(3$ types: Covishield, Covaxin, Sputnik$)$

$$ Gender $($Male$,$ Female$)$

$$ Marital Status $($Family$,$ Single, Other$)$

$$ Age Group $(18$ to $44,45$ to $60,$ above $60)$

$$ Number of doses

$$ Service Type $($Free$,$ Paid$)$

$$ Charges Per dose

$$ Date of registration

$$ Date of appointment booking

$$ Date of first dose

$$ Date of second dose

a$)$ Draw three appropriate charts for one categorical, numeric and binary attribute. What insights can be obtained based on these charts?

b$)$ Identify the redundant attributes present in the dataset?

c$)$ If you are asked to develop following three predictive models based on the above mentioned predictor attributes, then what will be the potential target attributes suitable for model building?

$$ Multiple linear regression

$$ Logistic regression

$$ Decision tree

d$)$ Draw simple dataset schema that will be considered for the development of Multiple Linear regression model along with sample record in it$.$

e$)$ Identify two potential issues that you foresee while dealing with numeric attributes given in the dataset.