If you’ve taken my introductory course then you understand the process used to develop a Data Science process. And you know there are a range of analytic techniques that are used to develop a product. But we haven’t yet delved into the techniques used in each of these phases. This training provides an introduction to the preparation of data, key models and methods for evaluation. The goal is to make you aware of the main categories of algorithms; we will not go into depth.
You will walk away appreciating many of the algorithms used in industry today. Use this course to obtain a review of the three key phases of data science development. This provides a perfect overview of many of the hyper-specific techniques in use today. Use this course to find out what techniques you really need.
Participants will be able to:
- Describe the three key phases of Data Science development
- Demonstrate why data preparation is important and how to implement
- Develop models that are appropriate for the type and complexity of the data
- Effectively evaluate and present models without bias or errors
This Online Training is for you because…
- Learning about hyper-specific tools or technologies don’t provide the breadth required to select an optimal solution to a problem
- You want to learn the three key phases of Data Science development
- You need to establish which algorithms to focus on for your specific problem set
- Python experience for workshops
- Introductory Data Science experience to understand terminology