Course Overview

The intersection of statistical rigour and AI is where the most impactful insights are born. R programmers who extend their skills into Artificial Intelligence gain a unique competitive advantage: they can design experiments correctly, interpret model uncertainty honestly, and communicate results with the credibility that pure software engineers often lack. CETPA Infotech's Artificial Intelligence with R Programming Training in Noida is tailored for analysts, researchers, and R practitioners who want to level up into AI without abandoning the statistical foundations that make their work trustworthy.

The course navigates the full journey from classical statistical modelling in R through modern machine learning and deep learning, using R interfaces to state-of-the-art frameworks. You will use the caret and tidymodels meta-frameworks for machine learning, the keras R package (backed by TensorFlow) for neural networks and deep learning, and the torch R package for PyTorch-style tensor operations. The curriculum also covers explainability libraries like LIME and SHAP, which are increasingly required by regulatory bodies in healthcare, finance, and insurance — sectors where R-skilled AI practitioners are in particularly high demand.

Special attention is given to biostatistical AI applications: survival analysis, mixed-effects models, clinical trial simulation, and genomic data analysis. These modules make CETPA's R-AI course uniquely valuable for professionals targeting careers in pharmaceutical companies, healthcare analytics firms, CROs (contract research organisations), and academic medical centres where R is the dominant language and AI expertise commands significant salary premiums.

Course Curriculum

• Advanced R: tidyverse, data.table, functional programming
• Statistical Modelling: GLMs, Mixed Effects, Survival Analysis
• ML with caret & tidymodels in R
• Explainability: LIME, SHAP, iml in R
• Neural Networks with keras R package
• CNN & Transfer Learning via keras/R
• LSTM for Time-Series Forecasting in R
• NLP with tidytext & text2vec
• Torch R Package: Tensors & Autograd
• Shiny Dashboard for AI Results
• Biostatistical AI: Genomics, Clinical Data
• Reproducible AI Research with R Markdown
• Capstone: Domain-Specific AI Project in R