Requirements
- Have completed Survival Python or have equivalent Python experience
- You will need to be able to install software on your machine
- The Anaconda distro of Python
Description
You know Python. You know Excel. You may even know how to crunch numbers in R using the Tidyverse if you have a statistics background.
But when it comes to applying all this knowledge to the world of data science, you know you need more than these tools to be successful. What makes matters worse is that you are not exactly sure of what order you should be learning which data science tools. It can be a challenge to know exactly where to focus, and how to apply what you do know.
At Mass Street University, we guide statisticians and developers interested in exploring how to process and analyze data—efficiently. In Python for Data Analysis, we focus you on precisely what you need to know, and teach you how best to utilize what you already do know.
In the course, we will teach you how to combine your existing knowledge of Python with tools like Pandas and Numpy. If you have only worked with the basic Python data types, approaching some of the higher order data types can be intimidating. The structure of our course takes you from the simplest tools to the more complex to ensure you stay focused on what you need while you build on your font of data science knowledge.
JupyterLab is one tool you may not be familiar with, and it is a popular data analysis notebook that supports many languages, including Python. Notebook technology is relatively new to the world of data science, and we will go over how JupyterLab will allow you to write much smaller amounts of code efficiently.
There are a ton of data science tools that interact very well with Python to make data science a breeze when explored and taught properly. And at Mass Street University, we make sure that this dynamic is managed as efficiently as possible. Enroll today in Python for Data Analysis to stay focused on what you need to excel in data analysis.
Who this course is for:
- Students who have just finished Survival Python.
- Developers who are familiar with Python but have never worked in data science and want to learn the most commonly used tools.
- Statisticians looking to migrate from R to Python.
Course content
- 05:48Instructor Introduction
- 00:55Course Overview
- 01:22Why You Should Take This Course
- 03:19How To Get Help With This Course
- 02:05Getting The Course Material
Instructor
![Bob Wakefield](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.5 Instructor Rating
- 505 Reviews
- 19,774 Students
- 4 Courses
Bob Wakefield has over 18 years of experience building data systems for numerous organizations across various industries. On many occasions, he has applied his formidable knowledge to radically advance an organization's analytic and data management capabilities. Because Bob prefers to stay on the bleeding edge of technology, he is able to provide his clients state-of- the-art data solutions. While Bob’s expertise lies in data architecture and engineering, he masterfully provides a full range of analytic solutions covering the entire data pipeline.
Bob is a graduate of Kansas State University, Kansas University, and Rockhurst University. He holds a Bachelors in Business Administration with a focus on Management Information Systems, an MBA with a corporate finance concentration, and a graduate certificate in Data Science. Bob is a proud veteran of the United States Air Force.
In his spare time, Bob enjoys cycling and retro gaming. When he’s not doing that, he can often be found flying his A-10 Warthog simulator.
Bob is a private pilot and commercial unmanned aerial systems pilot. He has over 100 hours in the following aircraft: Schweizer 2-33, Schweizer 1-26, Cessna 150, Cessna 152, Cessna 172, Cessna 175, Cessna 182RG, Pitts S-2C, Extra 300.