In the next few years 100 trillion+ gigabytes of data will need to be managed and processed and companies such as Apple, Amazon, Facebook and more are willing to pay top dollar to get skilled workers that are able to analyze and get insights from this data.
Skills to digest vast amounts of data and identify the important elements is very important. Once analyzed, data visualization is needed to tell a story and present the insights in a form that more people can understand the key points and make better decisions faster.
So together Data Analytics and Data Visualization is critical to companies with large amounts of raw, unorganized data.
The Python libraries that we will be learning in this course can be broken down into two large categories- Data Analytics and Visualization.
In Data Analytics we will cover Numpy, Scipy, and Pandas. On the Visualization side we will learn Matplotlib, Seaborn and Ploty. I’m really excited for you to list these libraries on your resume because you’ll see an instant jump in recruiters willing to interview you. This course will get you to the point where you can use these libraries confidently and effectively in the workplace. Completing this course will set you up to learn more advanced topics such as Machine Learning.
My name is Zain from Job Ready Programmer.com and I’ll be your instructor for this course. I’ve been working as a Data Scientist now for most of my career and I’m really excited to teach you the hottest skills you need to land a job in the data analytics space. We will be using Python - one of the most popular programming languages in the world. and focus predominantly on it’s data analytics and visualization packages in this course.
The Data Scientist job role has ranked as the number 1 job for 4 years in a row, and the demand for them is continuously growing as more and more data becomes available for us to analyze. This is why the average median salary for a mid-level Data Scientists is upwards of $130,000.