Learn how to debug and fix machine learning models.
Know and understand how to use popular data science tools.
8 sections • 40 lectures • 3h 2m total length
How to Navigate Through This Course.
Installing Software on Mac OS.
Installing Software on Windows OS
Cram Session with Python
Section Resources [The Basics of Data Science.]
Creating Statistical Visualizations.
The Machine Learning Paradigm.
Splitting your dataset (Part 1).
Building Our Pipeline.
Trying out a Few Machine Learning Models with our Pipeline.
Splitting our Dataset (Part 2).
Section Resources[Data Is Everything.]
Running Our Pipeline.
How do I get rid of ?
Rerunning our Pipeline
How to get better results.
Section Resources[Really! Data! Data! Data!]
Building a Dataset
Running our Pipeline
Preprocessing our Data and Rerunning our Pipeline.
Section Resources[Finding the Right Model Parameters.]
Setting up our Data and Pipeline
Searching Over Parameters
Section Resources and Exercises [Debugging in Data Science]
Setting Up Our Data and Creating a Not-so-good Model.
Debugging our Not-so-good Model
Debugging our Model Hyper-parameters.
Section Resources and Exercises [Creating Data Science Presentations]
Creating a Presentation.
Where to go from here?
Know how to use a computer (MAC or Windows).
Exposed to Computer Programming (in any language) preferably Python.
Know Basic Statistics (mean, std, median, etc.)
This is not your typical Data Science course.
We aim to show you the very basics of Data Science with practical examples. We require you to be familiar computer programming in general but not an expert. This course includes hands on lectures demonstrating fundamental concepts of data science, and useful python libraries for data science. For each hands on lecture we provide you with the code, documentation, and excercises.
We present the information in an understandable format, so if you have no experience with Data Science but are interested in learning more about it in a short time period you are in the right place.
Why should you take this course?
You are a entrepreneur or business owner and you want to learn about how Data Science and/or Analytics can make your business thrive.
You are a student and you feel like you really do not understand the basics of Data Science.
You dread taking a course about Python and Data Science because it sounds too complicated and just want a simple explanations
You want to see how to implement projects in data Science
This course Introduces:
Debugging Machine Learning Models
Creating Data Science Presentations
Who this course is for:
Anyone who wants to learn the basics of modern data science.
This course is NOT for someone who has no experience computer programming.
Kelechi Ikegwu has a BS and is currently pursuing his PhD in Informatics at The University of Illinois at Urbana Champaign. He has worked at NASA Research Centers, other government facilities, and academia in positions all related to Data Science.
Over the course of his career he has developed a skill set in analyzing and gaining insights from data using computational methods. Feel free to contact him on LinkedIn for more information about him.