Python for Data Science

Data science is a multidisciplinary field that uses math and programming to extract knowledge and insights from data. Data scientists use statistics, analytical skills, machine learning, and domain knowledge to deepen their understanding of the world around us through data. Data science is becoming more popular; every day, gigabytes of data are generated and processed.

Python 3 is the most widely used and fastest growing programming language in the world today. This is not a surprise, because it is perfect for data analysis and data science. This mini track will teach you the basics of Python. You will get to know the foundations of programming used in data science: what variables are, how to invoke functions, and how to write your own functions. You will discover the basics of popular Python libraries for data science: pandas and matplotlib. The pandas library is for statistics and data processing; matplotlib is a data visualization library.

This mini track lays the programming foundations needed to start working in the field of data science. After completing this mini track, you will be able to write simple data processing scripts and data visualizations. You will be prepared to further your education in programming, in Python or in another language of your choice.

We believe that the right way to learn programming is through practice. Our courses are fully interactive for this reason. Each exercise has a little bit of theory, an example, and a problem for you to solve by writing your own code. You will have faced many coding challenges by the end of each course.

What’s in it for me?

• A smooth entry into the world of data science. No prior experience, extra software, or practice data sets needed.
• A well-defined learning plan with 4 fully interactive courses. This mini track contains everything you need to start doing data science in Python. The courses are logically arranged, and the instructional process is perfectly designed for beginners to gain confidence and experience, while building solid foundations for further exploration on your own.
• Proven learning efficiency. Don’t learn just the concepts. Get hands-on practice with our real code editor and real-life exercises.
• Online certification. After successfully completing each course, you will receive a certificate you can add to your LinkedIn profile.
• A trusted support system. Every course comes with access to our resource base, support from a mentor and from a community of students, and technical support. You can also join our learning community and participate in on-task discussions.
• Hints and more. If you get stuck, you can leverage the included exercise hints. Or use the Discuss tab to ask questions and share insights with other members of the LearnPython community. You can also drop us a line at contact@learnpython.com — we'll be more than happy to help!

Objectives:

• Learn the basics of programming for data science using Python 3.
• Understand the basics of pandas, a popular Python library for data science.
• Learn how to use data frames in pandas.
• Learn basic statistics functions in pandas for computing descriptive statistics for a data set.
• Learn how to group data in pandas and how to compute statistics for grouped data.
• Understand the basics of data visualization in Python.
• Learn to work with different file formats in Python: CSV, JSON, Excel, etc.

Who should take this mini track?

• Beginner data scientists who want to learn data science and Python.
• Seasoned data scientists who want to start using Python in their work.
• People who want to process data with Python.
• IT beginners interested in learning the basics of coding.

Requirements:

• A web browser
• An internet connection