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Course Introduction to Python and Data Science


A long time since I don’t write related to a course, but I have done two courses of Python and Data Science, that you can find on EdX, given by Microsoft. you have the chance to do them until 31st December, and the courses are:

Let’s start for the first one …

Introduction to data science

If you have no programming skills (or some basic skills) in Python, this is the course you need to start for. I already wrote related to other Python courses and one I liked a los was introduction to interactive programming with Python (from Coursera), so, if you can, give it a try.

The course is self study at your own pace, and in theory, you can do it in 6 weeks, starting with very essential concepts for starting to programming: variables and functions. The level is increasing with each new lesson with list, imports, …. and at module 4 you can start learning data science with Numpy, Matplotlib and Pandas (this is for working with matrix and visualization of data).

In my opinion, the course will be very useful for those persons that want or need to work with data. You will learn how to store, manipulate and visualizate data, and the tools you can do for that.

The course is designed for Python 3.5, although I always recommend using the Anaconda distribution of Python, and you have both version Python 2.x and Python 3.x.

Module 1 is essential for knowing the course dinamic, it is the easiest lesson, but when you finished it, you will understand several important things such as variables, types, … Very basci, but fundamental for understanding next modules.

Module 2 is dedicated to lists, a special Python aspect you need to manage, becuase lists are widely used in Python. So put attention on this lesson.

Module 3 is dedicated to functions and packages. It is a new level of dificulty. Functions are designed to solve one tasks each, while packeges are code from other developers that we can use in order to solve our goals.

Module 4 is dedicated to Numpy, the basic packege for data science, mainly becuase you can work with matrix, so, calculating with all elements at one time is faster that using lists (one by one).

In module 5 you will use matplotlib, another basic library for data science for representing data. Although it is very basic the exercise you will do, the exercises will be really useful for understanding what you can do.

To end with, module 6 is dedicated to programming control and another useful data science library called pandas.

My conclusion after ending this first course

The course of this entrance is designed for Python and data science, and it is not a Python programming course, because basic aspects of Python are not showed in the course, such as classes or dictionaries. Of course, the basics are, but you must know what you need to learn in order to get better at Python. So, if you are a newbie to Python I encaurage you to try another Python course to know Python deeper.

Anyway, if you have basic skills, you won’t lose your time learning something really useful and easy, and it won’t take as much as a few hours and you’ll have a nice base to keep on learning.

Although this course is an introduction (you can find advanced Python courses on DataCamp , also data science with Python courses), you will learn several and basic tools for data science with Python, that you will use them in the next course.

Have a nice day!

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