Objective: To understand profile of the students who have already left: Descriptive analysis for the data the way you have posted. i.e. only those students who have left the course. You can create bar graph of gender for percentage of male and female who left the course and similarly another bar graph for age bands. I think excel should be good enough for this kind of work.
In my opinion instead of multiple correspondence analysis, you can try correspondence analysis of gender Vs. binary variable of those who left and stayed. One more correspondence analysis plot for age group. If you still want to do. here is a tutorial: https://www.youtube.com/watch?v=reG8Y9ZgcaQ
Objective: To find out profile of students are prone to leave the course: create a data set of all students including those who have not left. this should have 3 columns age group, gender and a binary coded variable. Also, binary variable should have 1 if student has left and 0 if student is still with us. Here is a tutorial on how to do this kind of analysis in R. I also believe that these two variables might not give you everything in terms of insights. there might be other factors such as past academic grades, annual household income number of members in family etc.
On the ethical side, i hope you are not building this kind of model for gender or age discrimination. Good luck!!