INTRO TO R FOR DATA SCIENCES
This is a Bring Your Own Device Course. You will be required to bring your laptops to each class and download designated software prior to the beginning of class (see below). Important: you will be required to do 5-10 hours of work per week outside of class time. If you have little or no prior knowledge, you might need extra time to gain familiarity with the concepts. But don’t worry. You’ve got this!
Your take-awayThis course is a great way to help you:
• Configure a functional R environment to program efficiently in R;
• Use R to implement a variety of data-related functions commonly used in the workplace;
• Apply common software engineering best practices to manage R programs throughout their life-cycle;
• Employ a range of analytical skills needed to solve common problems faced by software developers.
Our approachThis course employs student-centered, project-based learning that's focused on the acquisition of practical, real-world skills and not just theory. You'll get close, personalized instruction from an industry pro. You’ll
acquire the skills and competencies you need to implement a basic but complete data-science project in R, covering core language concepts (variables or loops, etc), as well as visualization and data modelling. Note that you will be required to do 5-10 hours of work per week outside of class time. Those with little to no prior knowledge will require more time to gain familiarity with the concepts.
Who benefits the most?• Anyone who wants to follow the IT stream in the Big Data program.
• Individuals who want to improve the performance of their organization by harnessing Big Data.
• Professionals who want to leverage data for better decision-making.
• Entrepreneurs with projects that could benefit from data analytics.
• Students of geography, biology, psychology, humanities or any other field with big data.
• IT professionals who want to transition to Big Data from more traditional sectors.
• People who are new to programming or are novice users of Python or another programming language.
• People who are genuinely interested in Data Science and Analytics and would like to better understand what they can do with R.
Important detailsHere's all the important information you need in order to get ready for class!
During the first class, some time will be devoted to installation troubleshooting and support, but students will be expected to install the R and RStudio software prior to the first class (see instructions below).
1. R > 3.0.1, follow the download and install links:
For Windows: https://cran.rstudio.com/bin/windows/base/R-3.6.1-win.exe
For Mac OS X: https://cran.rstudio.com/bin/macosx/ (click on R-3.6.1.pkg)
2. RStudio Desktop > 1.0:
For Windows 10/8/7: https://download1.rstudio.org/desktop/windows/RStudio-1.2.5001.exe
For Mac OS X 10.12+: https://download1.rstudio.org/desktop/macos/RStudio-1.2.5001.dmg
3. R packages used in the course: in RStudio, run:
4. Computer requirements:
Operating systems: Windows 7/8/10, or MacOS 10.12+
At least 4GB of RAM
At least 5 GB of available storage
Concordia CCE Loyalty Discount
All students who meet at least one of the following conditions, will receive a 10% discount on their CCE course or workshop tuition fees:
1) Have completed a CCE, Undergraduate or Graduate course at Concordia University in a prior academic term;
2) Have completed a language proficiency test (IELTS) at CCE;
3) Have completed a CCE Professional Development Seminar/Workshop.
This discount is based on the information maintained in the Concordia University student information system.
NOTE: This discount does not apply to a language proficiency test enrollment (IELTS) nor to application fees for admission to a CCE program of study.
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