Learn about data science techniques, applying visualizations to display data, feature engineering methods, and more! This free online Data Visualization course teaches you about visualizing data and exploring models. Data visualization is a highly useful way to explore data and can help you determine relationships between columns. With this course, you will learn how to apply visualizations to display your data and about feature engineering and constructing machine learning models. You will learn how to evaluate your model in Azure ML, R, and Python, and more!
| College | Alison |
| Course ID | 201776 |
| Course Category | Data Analytics, Business |
| Course Type | Online Learning |
| Course Qualification | CPD Certificate |
| Course Duration | 1.5-3 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 • Discuss the importance of data exploration • Recognize what you use for data visualizations in R • Recognize what you use for data visualizations in Python • Identify the different types of plots or charts you can use to visualize your data • Discuss the process of feature engineering • Identify features and methods available in R for creating Machine learning models • Identify features and methods available in Python for creating Machine learning models • Outline the process and options for evaluating your machine learning model |
| Course Code | 1660 |
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