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DSTC-A35 Online (e-LMS) Advanced Postgrad

Introduction to R Programming

by - DSTC

Master Introduction to R Programming in 4 weeks through hands-on, project-based online training with DSTC.

★★★★★ Be the first to review • 4 Weeks · 40 hrs • e-Certificate Included
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From ₹200 + GST

Programme Parameters

Educational Level:
Advanced Postgrad
Duration & Workload:
4 Weeks (40 Hrs)
Delivery Mode:
Online (e-LMS)
Prerequisites:
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.

About This Course

The Introduction to R Programming course is a free, beginner-friendly self-paced program designed to help learners understand the basics of R, a widely used programming language for data analysis, statistics, and research. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.

🎯 Program Aim

The Introduction to R Programming course is a free, beginner-friendly self-paced program designed to help learners understand the basics of R, a widely used programming language for data analysis, statistics, and research.

📋 Course Objectives

1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Assemble a documented case study that evidences your applied capability.

👥 Who Should Enroll?

• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence

🚀 Key Learning Outcomes

• A demonstrable Artificial Intelligence project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.

💎 What You'll Gain

🎥

Live & Recorded Sessions

Lifetime access to class recordings
🎓

e-Certificate on Completion

Cryptographically verified credential
💬

Post-Programme Support

Direct access to mentors & council
💻

Hands-On Experience

Notebooks, real-world code & datasets

Curriculum Outline

Module 1 Outline

Introduction to R Programming

What is R Programming? • Why R is Used in Data Science and Research • Installing and Setting Up R • Overview of R Environment

Module 2 Outline

Basics of R

Variables and Data Types • Vectors, Lists, and Data Structures • Basic Operators and Expressions • Writing Simple Commands

Module 3 Outline

Working with Data in R

Importing and Understanding Datasets • Basic Data Cleaning Concepts • Exploring Data in R • Simple Data Analysis

Module 4 Outline

Data Visualization in R

Introduction to Plots and Graphs • Basic Chart Types • Visualizing Data Patterns • Presenting Results Clearly

Module 5 Outline

Applications and Next Steps

R in Data Science and Research • Using R for Statistical Analysis • Career Opportunities in Data and Analytics • Mini Learning Activity / Concept-Based Practice

Technical Specifications

ParameterRequirement
Covered Tool / PlatformR Programming
Covered Tool / PlatformData Analysis
Covered Tool / PlatformData Visualization
Covered Tool / PlatformBasic Statistics
Covered Tool / PlatformDatasets

Frequently Asked Questions

Yes. This is a free online self-paced course designed for beginners.

No. The course starts from basics and is suitable for non-programmers.

You will learn R basics, data handling, simple analysis, and visualization concepts.

Students, beginners, and professionals from any background can join.

Yes. Learners receive an e-Certification after completing the course.

Yes. R is widely used for data analysis, statistics, research, visualization, and data science learning.

Yes. This course is designed for beginners and explains R programming concepts step by step.

The Introduction to R Programming course is designed as a 2–3 week online self-paced course.

Yes. The course introduces basic plots, graphs, chart types, and ways to present data patterns clearly.

The course starts with R basics, explains variables, data types, simple commands, datasets, analysis, and visualization in simple language without requiring prior programming experience. The Introduction to R Programming course provides a simple and structured foundation in programming for data analysis and research. It is an ideal starting point for learners who want to explore data science, statistics, and analytics using R.

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