Attribute

Detail

Format

Online (e-LMS)

Level

Advanced

Duration

4 weeks

Certification

e-Certification + e-Marksheet

Tools

R, RStudio

About the R Language For Ai Course

R Language – Use in AI is a structured 8-week program that introduces R programming to M.Tech, M.Sc, and MCA students, as well as professionals in various tech industries.

It covers the integration of R in data science, machine learning, deep learning, and natural language processing, providing practical skills and deep insights into R's use in AI-driven projects.

Program Highlights

• Comprehensive coverage of R Language for AI from fundamentals to advanced applications

• Hands-on projects and real-world case studies in Science & Technology

• Expert-curated curriculum aligned with current industry standards

• Access to recorded lectures and e-LMS platform for flexible, self-paced learning

• e-Certification and e-Marksheet upon successful completion

• Dedicated mentor support and interactive doubt-clearing sessions

• Exposure to industry-standard tools and platforms used in Science & Technology

• Career-oriented training for academic and professional growth in Science & Technology

Course Curriculum

Module 1: Introduction to R and AI Fundamentals Section 1.1: Getting Started with R

Subsection 1.1.1: Installing R and RStudio Overview of R language and the RStudio IDE.
Setting up R for AI development.

Module 2: Data Preprocessing and Feature Engineering Section 2.1: Data Collection and Cleaning in R

Subsection 2.1.1: Importing and Exploring Data Importing datasets from CSV, Excel, databases, and web sources.
Summary statistics and basic exploration using summary() , str() , head() .

Module 3: Building AI Models in R Section 3.1: Supervised Learning in R

Subsection 3.1.1: Regression Models Building and evaluating Linear Regression, Ridge, and Lasso models.
Implementing Polynomial Regression for non-linear relationships.

Module 4: Deep Learning with R Section 4.1: Introduction to Deep Learning

Subsection 4.1.1: Overview of Neural Networks Structure of neural networks: Layers, neurons, activation functions.
How deep learning differs from traditional machine learning.

Module 5: Model Deployment and Optimization Section 5.1: Model Deployment in R

Subsection 5.1.1: Saving and Exporting Models Saving models using saveRDS() , caret ’s train() , and keras models.
Loading models for prediction and inference.

Tools, Techniques, or Platforms Covered

R
RStudio

Real-World Applications

Apply R Language for AI skills directly to academic research, thesis work, and publications
Build a professional portfolio showcasing practical Science & Technology competencies
Solve industry-relevant problems using R Language for AI methodologies and tools
Contribute to open-source projects and collaborative research in Science & Technology
Prepare for competitive examinations, interviews, and professional certifications in Science & Technology

Who Should Attend & Prerequisites

Students pursuing degrees in Science & Technology, science, engineering, or related disciplines
Working professionals seeking to upskill or transition into Science & Technology roles
Researchers and academicians looking to adopt modern techniques in Science & Technology
Entrepreneurs, freelancers, and self-learners interested in practical Science & Technology knowledge

Prerequisites: Prior experience with Science & Technology fundamentals or a related discipline is recommended. Basic programming knowledge may be helpful depending on the course modules.

Frequently Asked Questions

1. What is the format of this R Language for AI course?

This is an Online (e-LMS) course delivered via our e-LMS platform. You will have access to pre-recorded video lectures, reading materials, assignments, quizzes, and hands-on projects that you can complete at your own pace.

2. Will I receive a certificate after completing this course?

Yes! Upon successful completion of all modules, assignments, and assessments, you will receive an e-Certification along with an e-Marksheet from NanoSchool (NSTC) that you can showcase on your CV and LinkedIn profile.

3. What are the prerequisites for this course?

Learners should have a foundational understanding of Science & Technology concepts. Familiarity with basic tools and programming is recommended.

4. How long will I have access to the course materials?

You will have access to all course materials for the duration of 4 weeks. The self-paced format allows you to learn according to your own schedule through our online learning management system.

5. Is mentor support available during the course?

Yes, dedicated mentor support is available throughout the course. You can reach out for doubt-clearing sessions, project guidance, and career advice related to Science & Technology. Our mentors are industry experts and experienced professionals.

Enroll in R Language for AI today and take the next step in your professional journey. With expert-curated content, practical projects, and industry-recognized certification, this course is your gateway to mastering Science & Technology skills that matter.

Brand	NSTC
Format	Online (e-LMS)
Duration	4 weeks
Level	Advanced
Domain
Hands-On	Yes – Practical projects with industrial datasets
Tools Used

Achieve Excellence & Enter the Hall of Fame!

Elevate your research to the next level! Get your groundbreaking work considered for publication in prestigious Open Access Journal (worth USD 1,000) and Opportunity to join esteemed Centre of Excellence. Network with industry leaders, access ongoing learning opportunities, and potentially earn a place in our coveted

Hall of Fame.

Achieve excellence and solidify your reputation among the elite!