Data scientists need to deal with complex problems, and the problem solving process basically involves four main steps: data collection and cleaning, data exploration, data modeling and data visualization.
Python for data science provides you with all the necessary tools to carry out this process effectively with dedicated libraries for each step that we will discuss later in this article..
Comes with powerful statistical and numerical libraries like Pandas, Numpy, Matplotlib, SciPy, scikit-learn, etc. and advanced deep learning libraries like Tensorflow, PyBrain, etc.
Free Introduction to Python Data Science
Start your data science journey in Python.
In this course we will see from scratch how to start programming in Python. The objective of this free introduction is that you can start using python as a tool to improve your statistical and graphical analysis.
In this course you will learn to:
- Install software to program in python with jupyter notebook
- Create lists of numeric variables, text and boleanas in python
- Perform numeric operations with the numpy package
- Analyze data using dataframes with the pandas package
- Design basic graphs with Matplotlib
Who is this course for?
- Aspiring analysts or data scientists in statistical consulting
- Students in the last semesters of technical careers in science
- People interested in understanding Python programming
Requirements
- The course is done in windows. But the concepts are valid for linux and MAC
This course is available for free without the need for any coupon, through the "FREE" option.
We recommend that you first read the differences between a free and a paid course to avoid misunderstandings:
Free courses
- Online video content
Paid courses
- Online video content
- Certificate of completion
- Instructor Questions and Answers
- Direct message to the instructor
To obtain the course for free, click on the following button:
