Data Analytics with Python and R

Course Available
2 Units
Online Fixed-Date

Course Description

Boost Your Python and R Data Analytics Knowledge and Programming Skills

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.

Course Details

Number of Units: 2.0 graduate level extension credit(s) in semester hours

Who Should Attend: This course provides continuing education for:

  • Working professionals who have completed at a minimum a bachelor's degree, which may include but not be limited to financial/data and/or business analysts, accountants, client relationship managers, and account managers from a wide variety of industries
  • Current undergraduate students looking to boost their resume with fundamental data analytics skills and knowledge
  • Marketing professionals, financial and/or business analysts
  • Anyone interested in data analytics with R and Python is also welcome

Course Materials:

  • by Chirag Shah available at or your local bookstore

Required Applications:

  • Python can be downloaded from the open-source Python website at , however the full version can consume 3GB+ of disk space.  For DAV-801B, students only need to use Miniconda, a minimal installer for Python, requiring only 400MB of disk space. Miniconda can be downloaded at .
  • R for Windows and Mac can be downloaded at .
    RStudio for Windows or Mac can be downloaded at .

Technical Requirements

Required Applications:

Prerequisites:

This is the third of four courses in the Data Analytics and Visualization Certificate.

Required successful completion of:

  • DAV-X800 Essentials of Analytics in Excel
  • DAV-X801A Data Visualization & Storytelling in Tableau

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.

Course Options

Course Date Units Price
DAV-X801B – 011 21 Jan 202510 Mar 2025 2 $1375

Data Analytics with Python and R

21 Jan 202510 Mar 2025
2
$1375
Online Fixed-Date
Online

Once you have enrolled in your course, to access the course Welcome Letter, which includes directions on how to access the New Student Orientation and your online course.

What You Will Learn

  • Describe machine learning and its applications in data analytics
  • Analyze business problems using data visualization, pattern discovery, and data exploration using Python and R
  • Utilize data analytics to address business decisions with efficient and applicable tools
  • Apply statistical modeling concepts such as regression and classification on various real-world data sets

Instructors

Professional development courses offered by the º£½ÇÂÒÂ×’s Division of Professional & Continuing Education are taught by faculty that possess a depth and breadth of academic and real-world professional experience.

Why USD?

The Professional and Continuing Education program nurtures key partnerships on the local, national, and international level. The goal is to better serve working professionals who seek to enhance or build their careers and help achieve their highest value and potential. Contact us today to learn more.

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Learning Method Information

Courses offer a convenient, yet rigorous style of learning that allows you to structure your education to suit your schedule while keeping you on pace toward achieving your educational.

Online Fixed-Date

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:

  • Module introduction that outlines what you can expect to learn in the module.
  • Required readings (textbook, articles, journals, etc.) and presentations (audio and/or video).
  • Assignments with due dates (which may include: written assignments, journal entries, research, blogs, etc.) based on the readings and presentations.
  • Discussion forum where you answer prompts from the instructor and interact with your classmates.
  • Module conclusion to review the topics and what you should have learned.
  • Typically, there is a final project, paper, or exam due in the last module that culminates all of the topics covered in each of the learning modules. You’ll find that the design of the learning modules has a rhythm to help you manage your time in the course.