Python For Data Science at edX

As a researcher in area of information technologies you have to work with data somehow. Data are everywhere and we must be able to know how to analyse them. When we perform some experiment in UX research we got a data that we need to evaluate. It is all about data when we are also working with recommendations, image recognitions, security or visualization. There is always part of our research when we do data science, so we have to know how to work with data.

But there is a lot of ways how to doing it and we can also use a lot of different tools and programming languages. Our choice depends on our experience or purpose of our research. One of these tools is Python. Python is really powerful programming language and it can be used for a lot of different purposes. Some of you already have an experience with this language and somebody (like me) not too much. But this course is for both of you. So let’s get into it :).

Course Introduction to Python for Data Science is developed by Microsoft and DataCamp and is not just another Python tutorial as you can find on the internet. It is specifically oriented to data science. By the end of this course you will know the powerful ways to store and manipulate data and to deploy powerful data science tools for your own analysis. You will be able to start your own research and get results from your experiments just by using Python and his functions and packages.

Every topic is based on three main type of interactions. First one are videos where you can find the most important theoretical information that will leads you to explore all the powers of this language in the context of data science. Second type of interaction is quiz that will check your knowledge from video lectures so you are able to finish also the third type of interaction. It is lab exercise where you can train your knowledge on online programming environment so you do not have to install anything. Quizes account for 30% of the total grade, the lab exercises accounts for 65% of the total grade, and the mandatory survey accounts for the remaining 5%. You must achieve an overall score of 70% to pass the course. You can enroll to course for free but if you want to get verified certificate you have to pay something :(.

Course is divided to many parts. And you will be learning the basic things but also the advanced topics. When you are beginner you will discover different data types and create first variables, subsets, manipulate lists, importing packages and functions. But you will also discover new packages that are really amazingly powerful when doing data science. You will learn Numpy for calculations, Matplotlib for different visualizations and plots and last but not least Pandas for easily and efficiently handle all the data.

I was new to Python and as a beginner I can recommend this course because the video lectures are very interesting and bringing just the useful information on real world examples. Lab exercises work also with real data so you can explore all the power of this language not just doing task and then close the program. In this course you are able to know why the code that you write is working and why is not. So let’s start with data science and Python.