Course
BasicLearn the world’s most popular data analysis language so you can mine through data faster and more effectively. No IT background needed.
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Data is everywhere—in sales figures, market research, transportation cost, logistics, and more. Let’s face it: business aggregates data rapidly. Collecting data is one thing, but using it for planning and decision-making is a completely different story. Forget about Excel pivot tables and charts. If you want to make good decisions based on data you own, you need to know how to derive insights from that data. That’s why we’re introducing a new course on the Python programming for data analysis.
Python is a powerful general-purpose programming language that is becoming world’s most popular language for data analysis. It’s a very simple and elegant language that promotes good coding habits. That’s why it’s especially recommended for beginners. Python is very popular among data scientists because it combines data science libraries and algorithms with the expressive power of a regular programming language.
Python is the hottest analytical skill on the job market—it not only solves real data problems but also creates business-ready reports and stunning graphics, all with cutting-edge algorithms that you don’t even need to understand to use.
This interactive Intro to Python course covers all the basics of Python you need to know to mine through data and perform data analysis. You’ll start your Python programming journey by learning how to import data into Python, use data frames, and, most importantly, think analytically.
You don’t need any programming or data science background to learn Python with us! Open yourself to more data science and big-data job opportunities, and take your career to the next level. No additional software or talking-head tutorials—just you, your browser, and 141 interactive exercises. Start learning now!
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Course progress
Exercises completed
1.
Discover how to write simple programs using Python, the most popular language for data analysis and data science.
2.
Learn how to work with tabular data in Python. In this part, you'll know DataFrame, the basic data structure of the popular data analysis library pandas.
3.
Compute basic statistics and group rows of DataFrames.
4.
Learn how to deal with errors in your datasets.
5.
Understand the basics of matplotlib to quickly create visualization.
6.
Consolidate and check your knowledge of Python and pandas.