I need the correct R code for the Logistic Regression Model. Thank you!

Scenario

You are a data analyst researching risk factors for heart disease at a university hospital. You have access to a large set of historical data that you can use to analyze patterns between different health indicators $($e$.$g$.$fasting blood sugar, maximum heart rate, etc.$)$and the presence of heart disease. You have been asked to create different logistic regression models that predict whether or not a person is at risk for heart disease. A model like this could eventually be used to evaluate medical records and look for risks that might not be obvious to human doctors. You have also been asked to create a classification random forest model to predict the risk of heart disease and a regression random forest model to predict the maximum heart rate achieved.

There are several variables in this data set, but you will be working with the following important variables:

Variable $|$What does it represent?

age: The person$$s age in years

sex: The person$$s sex $(1=$male, $0=$female$)$

cp: The type of chest pain experienced $(0=$no pain, $1=$typical angina, $2=$atypical angina, $3=$non$-$anginal pain$)$

trestbps: The person's resting blood pressure

chol: The person's cholesterol measurement in mg$/$dl

fbs: The person's fasting blood sugar is greater than $120$mg$/$dl $(1=$true$,0=$false$)$

restecg: Resting electrocardiographic measurement $(0=$normal, $1=$having ST$-$T wave abnormality, $2=$showing probable or definite left ventricular hypertrophy by Estes' criteria$)$

thalach: The person's maximum heart rate achieved

exang: Exercise$-$induced angina $(1=$yes, $0=$no$)$

oldpeak: ST depression induced by exercise relative to rest $(\text{'}$ST$\text{'}$relates to positions on the ECG plot$)$

slope: The slope of the peak exercise ST segment $(1=$upsloping, $2=$flat, $3=$downsloping$)$

ca: The number of major vessels $(0-3)$

target: Heart disease $(0=$no$,1=$yes$)$

$$Model #$1-$First Logistic Regression Model

Report the results of the regression model. Address the following questions in your analysis. Round all numbers to four decimal places.

$$Write the general form and the prediction equation of the logistic multiple regression model for heart disease $($target$)$using variables age $($age$),$resting blood pressure $($trestbps$),$exercised induced angina $($exang$),$and maximum heart rate achieved $($thalach$).$Note: Use the equation editor to write the regression equation.

$$Now write the prediction model equation in terms of the natural log of odds to express the beta terms in linear form.

Note: Use the equation editor to write the regression equation.

$$What do the following terms, from the general form of the model above, mean in terms of an individual having a heart disease?:

pi $$pi $/1-$pi

$$Create this logistic regression model. Write the prediction model equation $($in terms of the natural log of odds$)$using outputs obtained from your R script. Round all figures to four decimal places.

$$Interpret the estimated coefficient of the maximum heart rate achieved variable.

Model #$1-$First Logistic Regression Model

You have been asked to create a logistic regression model for heart disease $($target$)$using the variables age $($age$),$resting blood pressure $($trestbps$),$exercised induced angina $($exang$)$and maximum heart rate achieved $($thalach$).$