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R PROGRAMMING COURSE COURSE ( 1 MONTH )

Instructor Name

Dr.Omics
Category

Core Courses

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Course Requirements

  • Motivation to Learn: A strong desire to engage with and understand the material.
  • Basic Knowledge: Familiarity with biology and molecular biology concepts.
  • Interest in Technology: Eagerness to learn about the latest technologies in Next-Generation Sequencing (NGS).
  • Software: Free software will be utilized, so no additional software purchases are necessary.
  • Hardware: A laptop with a minimum of 4GB RAM and 100GB of hard disk space.

Course Description

  • Introduction to R Programming: Dive into R as a powerful tool for statistical computing and data analysis.
  • Fundamental Concepts: Cover essential topics such as data types, variables, and basic syntax in R programming.
  • Data Manipulation and Transformation: Explore R's extensive libraries for data manipulation and transformation to derive meaningful insights.
  • Data Visualization Techniques: Learn effective data visualization techniques in R for presenting and interpreting data.
  • Programming Structures: Master programming structures like loops and conditional statements to automate tasks and make data-driven decisions.
  • Statistical Analysis and Hypothesis Testing: Implement statistical analysis and hypothesis testing using R to extract actionable insights from data.

Course Outcomes

  • Master foundational R programming skills, including data types, variables, and basic syntax.
  • Gain proficiency in manipulating and transforming data using R's extensive libraries.
  • Learn effective data visualization techniques in R for clear presentation and interpretation.
  • Develop skills in programming structures like loops and conditional statements for automation in data analysis.
  • Apply statistical analysis and hypothesis testing techniques using R to derive meaningful insights.
  • Gain hands-on experience with real-world datasets, collaborative coding exercises, and integration of R with other tools for comprehensive data analysis.

Rules & Regulations

  •  Attendance and Participation: Maintain a minimum of 75% attendance. Regular assessments and attendance contribute to performance evaluation.
  •  Discipline: Maintain punctuality and respect in live classes. Engage actively and interact respectfully with instructors and peers.
  • Course Fee Payment: Pay course fees on time to avoid suspension or cancellation of access.
  • Assignments: Complete assignments sincerely and submit them on time.
  • Feedback and Communication: Maintain open communication with instructors and provide constructive feedback.
  • Certification: A certificate will be awarded upon course completion.

Course Curriculum DOWNLOAD BROCHURE

1 Getting Ready with R -introduction and installation
1 Hour

2 Data Types, Variables, and Basic R Operations
1 Hour

3 Algebraic and Logical Operations in R
1 Hour

4 Function-buit-in and User defined
1 Hour

5 Conditional statements
1 Hour

6 Package installation from CRAN repository and Bioconductor
1 Hour

7 Data manipulation with dplyr for biological datasets
1 Hour

8 Importing and handling biological data formats
1 Hour

9 Data Wrangling and Cleaning
1 Hour

1 Working with Sequence using Bioconductor
1 Hour

2 Sequence Analysis with seqinr and biostring
1 Hour

3 Sequence Statistical
1 Hour

4 Handling Sequence Database
1 Hour

5 Sequence Alignment
1 Hour

1 Statistical Test-t-test ,z-test and ANOVA
1 Hour

2 Visualization using ggplot2
1 Hour

3 Heatmap and Volcano plot
1 Hour

4 Network analysis and visualization
1 Hour

5 Phylogenetic tree structure
1 Hour

6 Machine learning applications in genomics
1 Hour

Instructor

Dr.Omics

0 Rating
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213 Students
44 Courses

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This course includes:

  • Live classes

  • For full fee and payment plan details, please contact us at 9310870544

  • Duration 1 Month

  • Skill Level Advanced

  • Lectures 20 lessons

  • Full lifetime access

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