About this course: Whether being used to customize advertising to millions of website visitors or streamline inventory ordering at a small restaurant, data is becoming more integral to success. Too often, we’re not sure how use data to find answers to the questions that will make us more successful in what we do. In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions.
Taught by: Lisa Dierker, Professor
Psychology
| Basic Info |
Course 1 of 5 in the
Data Analysis and Interpretation Specialization.
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| Commitment | 4 weeks of study, 4-5 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
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Earn official recognition for your work, and share your success with friends, colleagues, and employers.
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
good to start SAS or PYthon programming. short period and project due date every weekend is good.
It was basic material but well stated and practiced.
This course covers the basic data management and visualization using SAS and Python. I like the simplicity and straightforwardness of the contents. Will continue to explore this specialization.
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It's a great course, but I would have preferred a bit more in-depth working with Python. Not all the coding examples and instructions apply to all the suggested datasets and one has to do a bit of extra research at times. But all in all, this course takes you through the most important steps of doing data analysis and visualization.