This introductory programming course in Python and R is designed to connect a foundational knowledge of coding to its practical application in a data analytics project framework. Each module builds Python and R programming knowledge using selected textbook readings reinforced with explanatory videos and demonstrations. Through guided instruction, students will get hands-on practice using Python and R for data manipulation, data visualization, and statistical modeling as they input the appropriate code syntax to solve data problem scenarios executed in Jupyter Notebooks. Students will progressively build programming competencies, demonstrate assimilation through knowledge checks, and extend their foundational understanding of Python and R into a practice of real-world data analytics and problem-solving.
This course is the third required course in our Data Analytics and Visualization Certificate program. As such, students looking to enroll in the Data Analytics with Python and R class must have successfully completed the two prerequisite courses: Essentials of Analytics in Excel and Data Visualization & Storytelling with Tableau.
Number of Units: 2.0 graduate level extension credit(s) in semester hours
Who Should Attend: This course provides continuing education for:
This is the third of four courses in the Data Analytics and Visualization Certificate.
Required successful completion of:
A Bachelor's degree or currently in a bachelor's program, with a basic mathematics background preferred, with at least one course, preferably, in basic statistics taken at the college level.
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Online Fixed-Date: Online fixed-date courses offer a convenient, yet rigorous style of learning that enables you to collaborate with your instructor and other students in a shared, online learning environment. These courses have fixed start and finish dates, but as an online student you will have 24/7 online access to your classroom assignments, syllabus and course resources. Our online fixed-date courses allow you to work on your assignments anytime, although you are required to complete the assignments by specific dates.
How is the learning structured? In an online fixed-date course, you and your classmates will proceed through the curriculum together, collaborating in a shared learning experience. Each online fixed-date course is asynchronous, meaning that you can work on your assignments anytime, although required to complete the assignments by specific dates. The course is designed with learning modules where all of the content is grouped into weekly assignments. Each module covers one or more topics. Within each of the learning modules, you can expect the following components:
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