Analytics Software Technology

What you’ll learn:

The Analytics Software Technology course provides you with the core R programming skills that will allow you to turn raw data into understanding, insight and knowledge. The course is hands-on, using a project-based approach to learning R programming. After taking the course, you’ll have the foundational data science skills to tackle a wide variety of challenges using the best parts of R.

Who you’ll learn from:

Mike Ames
Adjunct
amesam@wfu.edu

“I’m a practicing data scientist who enjoys teaching. I work with a variety of companies using data science and machine learning to help them combat fraud, waste and abuse. I enjoy bringing real-world data challenges into my classes, and helping students deep dive with technology. My focus is on building foundational data science skills including data wrangling, exploration, and programing but I also like to throw little machine learning in the mix for good measure. In my spare time I noodle on guitar, and like to mountain bike, kickbox and kayak.

BBA Economics University of Georgia (1994), MBA University of North Carolina – Chapel Hill (2002)”

The best things about Analytics Software Technology

• R. It’s free, it’s cool, and it’s a marketable skill.
• You’ll have a variety of projects to work on.
• We’ll use real-world data, so you’ll be able to apply those skills immediately.

How you’ll learn:

I believe the best way to learn to code is to write code. The course is fast-paced and uses a combination of synchronous lectures where we’ll cover everything from importing, wrangling, and visualizing data. And asynchronous projects and assignments to reinforce the concepts. I like to bring a little real-world perspective and data into my classes.

Synchronous class twice weekly

We will review and discuss concepts together in class with a focus on coding together.

Asynchronous Materials

Class materials will be available online for asynchronous work and study.