Course Name |
Quantitative Aptitude In Competitive Exams |
Course Code |
CERMA008 |
Year |
2020-21 |
Course Designer |
Mr. Mohiyudheen N |
Couse Duration |
30 Hrs |
Course Schedule |
November to February |
Maximum Students Intake |
60 Students |
1. COURSE LEVEL
Foundational, skill-oriented certificate programme.
2. PREREQUISITE
None.
3. COURSE INTAKE & ADMISSION
Maximum 60 students will be given admission to the course based on First-Come-First-Serve basis. All the students of the MAMO College are eligible for free enrolment for the course. The enrolment notification will be issued for the course well in advance of the commencement of the course.
4. COURSE COORDINATOR
Mr. Mohiyudheen N, Assistant Professor, Department of Mathematics
5. COURSE PREAMBLE
In this course, you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
6. DURATION
Total Duration: 30 Hrs. [Contact Hrs. 20 Hrs., Lab Hours: 6 Hrs. and Assessment Works: 4]
7. CURRICULUM FOCUS
Enhance the employability of the learners through curriculum enrichment for additional skill development.
8. COURSE OBJECTIVES
Learners are exposed to
(a) Understand critical programming language concepts.
(b) Configure statistical programming software
(c) Make use of R loop functions and debugging tools
(d) Collect detailed information using R profiler.
9. SKILL EXPECTED
On the successful completion of the course, learners will be able to:
(a) Data Analysis
(b) Debugging
(c) R Programming
(d) R Studio.
10. COURSE OUTCOMES
Upon the successful completion of the course, learners will be able to:
CO No |
Course Outcome(CO) |
Skill/Knowledge Attainment Level Based on Revised Bloom’s Taxonomy |
CO1 |
Understand the basics in R programming in terms of constructs, control statements, string functions |
Understand |
CO2 |
Understand the use of R for Big Data analytics |
Understand |
CO3 |
Learn to apply R programming for Text processing |
Apply |
CO4 |
Able to appreciate and apply the R programming from a statistical perspective |
Apply |