About this course: This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework. The third week will describe the gamut of functionality available in matplotlib, and demonstrate a variety of basic statistical charts helping learners to identify when a particular method is good for a particular problem. The course will end with a discussion of other forms of structuring and visualizing data. This course should be taken after Introduction to Data Science in Python and before the remainder of the Applied Data Science with Python courses: Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python.
Who is this class for: This course is part of “Applied Data Science with Python“ and is intended for learners who have basic python or programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. Only minimal statistics background is expected, and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.
Taught by: Christopher Brooks
| Basic Info |
Course 2 of 5 in the
Applied Data Science with Python Specialization.
|
| Level | Intermediate |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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|---|---|---|
| Access to course materials | Available | Available |
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Interesting topics for the final assignment, liked the way difficulty level increased week by week.
Good Course and Great Content! Be aware it requires peer-grading
I really like this approach of the specialization. Data visualization is a great topic and this was very insightful for one week.
However as with all other courses in this specialization I miss qualified feedback on my submissions.
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Excellent course with in depth explanations. It is well structured. It learn me to applied Plotting, charting and Data representation in Python from very basics to optimum level. It help me to understand details of using Python to Applied Plotting, Charting and Representing Data.