In getting up to speed on analytics I found that there is general agreement that it helps, particularly with machine learning, to have some proficiency in the following areas of mathematics: Calculus, Probability, Statistics, and Linear Algebra. Not having taken any of these, or used any of it, since graduate school over 30 years ago I set out recently taking courses for credit. (My programming skills, particularly relational database skills, are still adequately current. I worked with relational databases almost exclusively for 16 years straight up until 18 months ago. I am now retired and considering a third career in analytics. My first career was as an Army Officer. My second career was in software development and database consulting having retired from Microsoft after 16 years there. I have completed a Python class just recently, the MIT intro course on Edx.) I am just completing a Calculus I class that was about three quarters differential and one quarter integral topics. The school offers Calculus II which seems to be all integral stuff and a Calculus III that I think is multi-variable.
Any suggestions? How much more Calculus?
After Calculus I should I move on to Linear Algebra and Statistics courses? Do I need Calculus II and III?