Learn the fundamentals of Python and the pandas library for use in data science projects with this free online course. This free online training introduces the Python programming language and the popular Python pandas library for developing various data science and machine learning projects. We will start by setting up a JupyterLab environment, reviewing the basic Python fundamental syntax and then move on to loading large dataset files, performing initial data exploration, cleaning the data, transforming columns and rows and more.
| College | Alison |
| Course ID | 201562 |
| Course Type | Online Learning |
| Course Qualification | CPD Certificate |
| Course Duration | 3-4 hours |
| Course Fee | Free |
| Entry Requirements | Like all courses on the Alison Free Learning platform this is a free, CPD-accredited course. A Graduate can choose to buy a certificate or diploma upon successful completion of a course, but this is not required or necessary. At Alison we believe that free education, more than anything, has the power to break through boundaries and transform lives. Alison is the world’s largest free online empowerment platform for education and skills training, offering over 5000 CPD accredited courses and a range of impactful career development tools. It is a for-profit social enterprise dedicated to making it possible for anyone, to study anything, anywhere, at any time, for free online, at any subject level. Through our mission, we are a catalyst for positive social change, creating opportunity, prosperity, and equality for everyone. |
| Career Path | What You Will Learn In This Free Course • Explain the fundamental syntax of Python • Discuss the JupyterLab development tool • Arrange and manage projects with Jupyter notebooks • Analyse examples of data science projects in Python • Arrange tabular datasets from CSV files into a DataFrame object • Classify, select, filter and clean raw data • Describe how to transform data in rows and columns as a pre-processing step before using algorithms • Compare, group and sort data in multiple dimensions • Arrange and export the output data to CSV files • Summarise an end-to-end data exploration |
| Course Code | 4555 |
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