
Now, learn programming languages in the comfort of your home, in any part of the world. I can help you learn programming in R Programming for your university, college or school exams.
The syllabus as shown alongside is a typical syllabus for most exams. I can modify the topics covered as per your exam syllabus.
All teaching is online through live (not recorded) lectures wherein you will be able to interact with me in real-time and get your difficulties solved immediately.
You will learn theory and practicals and see how programs develop online.
Features:
- Solved programs
- PDF Exercise sheets
- Practical Tips
- Difficulty Solving Sessions
Course Prerequisites:
- Basic math and statistics
- Logical bent of mind
SYLLABUS OF R Programming ONLINE COURSE For SCHOOL, COLLEGE, AND UNIVERSITY SYLLABUS TELEGRAM (Message): https://t.me/scitechgen Email: scitechgen@outlook.com |
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Fundamentals of Programming. What are High Level Languages and Low Level Languages? What are Compiler and Interpreter? Features of R Programming Language Introduction to R console and editor, idea of packages in R |
Fundamental Concepts Types of data- integers, characters, numeric, logical, factor, dates, etc. Types of objects: lists, vectors, matrices, data-frames, etc. Creating and working with simple vectors Merging vectors into a single data set |
Interacting with Excel Importing data from an excel sheet into R and exporting data from R to Excel. Assigning column names, extracting individual rows and columns. Basic mathematical and statistical operations- adding and subtracting across row and columns, calculating measures of central tendency and dispersion. |
Using Data Introduction to datasets in R packages Dealing with missing data Summarizing data |
Functions, Conditional Execution & Looping Writing functions and if-else statements Creating loops |
Strings Strings and operations on strings |
Visualization Introducing the basic plot function- scatter plots, lines, steps, box plots. Adding parameters to the basic plot function- creating legends, adding background colors, grid lines, viewing multiple graphs in a single pane, etc. Bar plots, histograms, pie charts. Quintiles, Percentiles, Q-Q plots. |
Probability Probability- counting, generating random variables, discrete and continuous probability functions |
Linear Regression ANOVA Linear regression and its diagnostic checks and plots. |
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