In this course, discover how to gain valuable insights from large data sets using specific languages and tools. Follow Chris DallaVilla as he walks through how to use R, Python, and Tableau to perform data modeling and assess performance. As Chris dives into these concepts, he shares specific case studies that come directly from his own work with clients. Plus, he shares three essential—and practical—best practices for data-driven marketing that you can use to bolster your organization's marketing performance.
- Installing R, Python, and Tableau
- Navigating the UI for R, Python, and Tableau
- Using R, Python, and Tableau
- Exploratory analysis
- Performing regression analysis
- Performing a cluster analysis
- Performing a conjoint assessment
- Stakeholder alignment
Skill Level Intermediate
- Marketing is changing right in front of our eyes and that transformation is being lead by data. Data science is often referred to as the sexiest career of the modern age. I wouldn't necessarily disagree simply because I love data's ability to explain how the world works. It only makes sense to marry the two fields. This way we can gain insights into what people want and why they want it. My name is Chris DallaVilla. I've been working with marketing and marketing data for 20 years. And in this course I'll take you through a contextualized journey in which you'll learn how to apply specific languages to gain robust insights into large data sets.
We'll tackle specific case studies that come directly from the work that I do with my clients. This course is here to give you the tools that you need to bring about a transformation for your organization. Here's an overview of what we're going to cover and by the end of this course you'll be able to effectively navigate the three leading software packages for performing data modeling and assessing performance. We'll be using R and Python. They're both leading programming languages and applications frameworks for data science and we'll be using Tableau which is market leader in data discovery and data visualization.
We're also going to cover three primary best practices for data-driven marketing in a way that you can apply them immediately and you'll be able to perform critical data modeling to identify insights and opportunities to strengthen your marketing performance. I'm enamored by a data-first approach to marketing because it can transform what are so often decisions that are made subjectively into decisions that are well informed and really in service of the business. And I'm excited you've chosen to join me for this course. So let's get started.