Data Science

Beginner to Mastery

Mastering Data Science with R

Cutting-edge Data Science Tools.

Comprehensive curriculum covering R, statistics, machine learning, and deep learning..

Strong emphasis on practical application through hands-on projects.

Flexible program design to accommodate learners from diverse backgrounds.

Group Enrollment with Friends or Colleagues

Mastering Data Science with R

Course Duration

240 Hours

Next Batch

14 September 2025

Course Material

Live. Online. Interactive.

Cutting-edge focus on deep learning for AI proficiency.

Equip graduates with in-demand skills for successful careers in data science.

Industry-relevant case studies to bridge the gap between theory and real-world problem-solving.

Work on real-world projects and case studies to apply concepts practically and build a strong portfolio.

Highlight Mastering Data Science with R

KEY HIGHLIGHTS OF MASTERING DATA SCIENCE WITH R PROGRAM

  • Weekly sessions with industry professionals
  • Dedicated Learning Management Team
  • 240 hours of hands-on learning experience
  • 75+ Live Sessions Across 4 months
  • 105 Hours of Self-Paced Learning
  • Learn from Industry Experts.
  • More than 25+ industry-related projects and case studies
  • One-on-One with Industry Mentors
  • 24*7 Support
  • Dedicated Learning Management Team
  • 1:1 Mock Interview
  • No-Cost EMI Option
  • Designed for both working professionals and fresh graduates
  • High Demand and Career Opportunities
  • Competitive Edge and Innovation
  • Problem-Solving and Critical Thinking

WHY JOIN MASTERING DATA SCIENCE WITH R PROGRAM?

Hands-On Learning

Gain practical experience with advanced tools like GPT, DALL-E 2, and Hugging Face Transformers.

Comprehensive Skill Set

Master everything from Python programming to cutting-edge AI techniques.

Stay Ahead

Learn the latest AI and generative technologies shaping the future.

Career Advancement

Boost your qualifications and open doors to advanced AI roles.

UPCOMING BATCH:

14 September 2025

SkillzRevo

SkillzRevo Solutions

30 MINUTE MEETING

Web conferencing details provided upon confirmation.

Corporate Training, Enterprise training for teams

Batch schedule

BatchBatch Type
Online Live Instructor Led SessionFull-Time
Online Live Instructor Led SessionPart-Time

Regional Timings

BatchBatch Type
IST (India Standard Time)09:00 PM–12:00 AM
Bahrain, Qatar, Kuwait, Saudi Arabia06:30 PM–09:30 PM
UAE / Oman07:30 PM–09:00 PM

Mastering Data Science with R OVERVIEW

This Program offers a deep dive into fundamental AI technologies, Python programming language and essential libraries for machine learning image processing etc. Participants will learn cutting-edge tools such as Hugging Face Transformers, GPT, DALL-E 2.0, MidJourney, GANs, RAG, LanguageChain. The curriculum integrates theoretical understanding with real-world use-cases to develop a skills-rich ecosystem capable of utilizing AI and generative technologies at an advanced level.

ENROLL NOW & BOOK YOUR SEAT AT FLAT 50% WAIVER ON FEE

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Mastering Data Science with R Objectives

The course aims to provide participants a thorough understanding of AI technologies with its more high-level programming side. After completing this, the student will be proficient in python programming and have experience working with Hugging Face Transformers, GPT, DALL-E 2, MidJourney. Then they can integrate those levels of solutions into their AI application. And will be equipped with hands-on experience on GANs, RAG and LangChain to face the complex challenges and innovations in the AI community.

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Why Learn Mastering Data Science with R ?

Master R & Data Analysis

Gain proficiency in R, statistical analysis, and data visualization to effectively explore and understand data.

Build Predictive Models

Learn machine learning and deep learning techniques to create intelligent systems for accurate predictions.

Unlock Data Potential

Discover hidden patterns and insights within your data through data analysis and feature engineering, driving informed decision-making.

Enhance Communication

Innovative ways of communicating detailed understanding and findings with data visualisation techniques.

Advance Your Career

Gain skills that can lead you to top jobs in data science, machine learning, and deep learning.

Hands-On Projects

Apply your knowledge through real-world case studies and projects, building practical experience and a strong portfolio.

Industry-Relevant Skills

Equip yourself with R packages and frameworks widely used in data science and analytics, ensuring you stay aligned with industry needs.

Drive Innovation

Develop cutting-edge technologies and solutions with deep understanding of these tools.

Program Advantages

Covers R, statistical analysis, machine learning, and deep learning for a broad data science foundation.

Focuses on current tools and practices to ensure up-to-date training.

Combines theory with projects for hands-on problem-solving skills.

Taught by knowledgeable educators with a focus on individual student attention.

Prepares students for roles like Data Analysts, Machine Learning Engineers, and AI Specialists.

Teaches state-of-the-art libraries and frameworks such as TensorFlow and Keras.

Develops problem-solving abilities and data-driven decision-making.

Encourages teamwork, idea sharing, and networking among students.

Helps students build a professional portfolio for job searches and promotions.

Provides a solid foundation for continuous learning in evolving data science technologies.

Description

Mastering Data Science with R program Certifications

NASSCOM

NASSCOM

Course Completion

Course Completion

Project Completion

Project Completion

Mastering Data Science with R Curriculum

Lecture 01: Introduction to R, Installing R and RStudio, Basics of RStudio IDE, Writing and executing R scripts, Variables and Data Type in R, Operators
Lecture 02: Creating vectors, Vector indexing and slicing, Vectorized operations, Creating matrices, Matrix operations, Matrix indexing, Creating lists, Creating data frames, Indexing and manipulating lists and data frames
Lecture 03: Conditional statements, Loops, Applying functions, Flow Control, Functions in R, Object-Oriented Programming in R, S3 and S4 classes, Methods and inheritance, Creating and using objects
Lecture 04: Data Structures - List, Tuple, and List Comprehensions
Lecture 05: Creating and using factors, Working with dates and times, Reading and writing (CSV files and Excel files), Introduction to the readr and readxl packages
Lecture 06: Introduction to dplyr, Selecting, filtering, and arranging data, Grouping data, Summarizing data with summarize and mutate
Lecture 07: Data Manipulation in R - dplyr, Data Manipulation & Data Visualization in R - tidyr
Lecture 08: Introduction to Text Mining, Text Preprocessing, Document-Term Matrix (DTM) and TF-IDF, Exploratory Text Analysis, Sentiment Analysis
Lecture 09: Install Necessary Packages, Create a New Package, Package Structure, Writing Functions, Documenting Functions, Testing Your Package, Building and Checking and Sharing Your Package
Lecture 10: Introduction to APIs, Using the 'httr' Package, GET & POST Request, and Authentication, Introduction to Web Scraping, Using the 'rvest' Package, Handling Dynamic Content, Handling Sessions and Cookies
Lecture 11: Connecting to Databases in R, Packages Installation, Connect to Database, Execute Queries, Write Data, Disconnect and Error Handling
Lecture 12: Introduction to Statistics, Descriptive Statistics, Sample, Population, Major of Central Tendency, Standard Deviation,
Lecture 13: Variance, Range, IQR, Outliers, Correlation, Covariance Skewness, Kurtosis, Probability
Lecture 14: Probability, Probability distributions, Central Limit Theorem, Binomial and Poisson Distribution
Lecture 15: Normal Distribution, Type I & Type II Error
Lecture 16: T-test, Z-test, Hypothesis Testing
Interview Questions
Lecture 17: Introduction to ML, Types of variables, Encoding, Normalization, Standardization, Types of ML, Linear Regression
Lecture 18: Linear Regression, Logistic Regression, SVM, KNN, Naïve Bayes, Decision Tree, Random Forest
Lecture 19: Mean Absolute Error, Mean and Root Mean Square Error, Confusion Matrix, R2 Score, Adjusted R2 Score,F1 Score
Lecture 20: Classification Report, AUC ROC, Accuracy, Ensemble Techniques, Random Forest, Xgboost
Lecture 21: Unsupervised Machine Learning, PCA, Clustering, k-Means Clustering and Hierarchical clustering
Lecture 22: Introduction to Neural Network, Foreward Propagation, Activation Function
Lecture 23: Activation Function(Linear, Sigmoid, Relu, Leaky Relu), Optimizers, Gradient Descent, Stochastics Gradient Descent
Lecture 24: Mini batch Gradient Descent, Adagrad, Padding, Pooling, Convolution, Checkpoints and Neural Networks Implementation
Lecture 25: Introduction to Time Series Analysis, Various components of the TSA, Decomposition Method (Additive Method and Multiplicative)
Lecture 26: ARMA and ARIMA
Lecture 27: Project Session

Mastering Data Science with R Skills Covered

Data Analysis
Data Manipulation
Statistical Analysis
Machine Learning
Model Evaluation
Feature Engineering
Neural networks
Transfer learning
Deep Learning
Image Processing
Text Processing
Sentiment Analysis
Language Modelling
Deep Learning
Data Visualization

Mastering Data Science with R Tools Covered

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Mastering Data Science with R Program Benefits

Mastering Data Science with R Program Benefits Illustration

CAREER OPPORTUNITIES AFTER THIS COURSE

Machine Learning Engineer Salary Range

Min

$90,000

Average

$120,000

Max

$150,000

Projects

MASTER GANS, TRANSFORMERS & DEEP LEARNING WITH REAL PROJECTS

Practice Essential Tools

Designed By Industry Experts

Get Real-world Experience

Machine Learning
NO. OF PROJECTS: 10
Deep Learning
NO. OF PROJECTS: 10

Capstone Projects of this Program

Multimodal Text-to-Image Generator

A system that creates high-quality, realistic images from descriptive text inputs, blending multiple data types for creative visual output.

AI Music Composer with Genre Adaptation

An AI tool that generates original musical compositions while adapting to specific genre styles, tempo, and mood preferences.

Realistic Deepfake Video Synthesizer

A tool that realistically manipulates and synthesizes video content to create authentic-looking deepfake footage for various applications.

Personality-Driven Conversational AI Assistant

A chatbot designed to interact with a distinct and consistent personality, providing a more natural and engaging user experience.

Artistic Style Transfer Engine for Videos

A program that applies the artistic style of a source image to every frame of a video, creating a new, stylized visual experience.

Context-Aware Text Summarization System

An advanced system that generates concise summaries of long texts by understanding the document's broader context and key information.

Voice Cloning and Speech Style Transfer Tool

A tool that replicates a speaker's voice and transfers a specific speech style or emotion to new synthesized audio content.

Interactive AI Storyteller with Image Generation

An AI that collaboratively creates stories with users, dynamically generating scenes and characters based on a developing narrative.

2D Sketch to 3D Object Generation Pipeline

A seamless workflow that converts simple two-dimensional sketches into detailed, three-dimensional models for creative and design purposes.

Synthetic Data Generator for Model Training

A system that produces large and diverse datasets for machine learning models, overcoming data scarcity for effective training.

AI-Powered Video Subtitle Generator and Translator

An automated solution that transcribes spoken language in videos and translates it into accurate subtitles for global accessibility.

Generative Design Tool for Product Prototyping

An AI application that rapidly generates numerous product design prototypes based on a set of constraints and functional requirements.

RAG-based Research Assistant (Retrieval-Augmented Generation)

An intelligent assistant that answers complex queries by retrieving relevant information from large documents and generating coherent responses.

Multilingual Chatbot with Memory and Personality

A conversational agent that can communicate in multiple languages while maintaining a consistent personality and recalling past interactions.

AI-Powered Comic Strip Generator from Text Prompts

A tool that creates unique comic strips by converting user text prompts into sequential images with a consistent artistic style.

Explainable AI Engine for Text Classification

An AI system that classifies text and provides clear, understandable reasons for its decisions, ensuring transparency and trust.

Autonomous Slide Generator from Research Papers

An AI that automatically extracts key findings and data from research papers to create well-structured, presentable slide decks.

AI Assistant for Code Generation and Explanation

A helpful tool that writes code snippets and explains complex programming logic in simple terms, assisting developers with their tasks.

AI-Driven Marketing Content Generator Across Formats (text, image, video)

A unified platform that produces marketing materials in various formats, including text, images, and videos, from a single campaign brief.

Real-Time Emotion Detection and Response AI System

A system that identifies human emotions from facial expressions or speech and generates appropriate, empathetic responses in real time.

Job Obligation After This Course

WE CAN APPLY FOR JOBS IN

Preparing the Data for acquisition

cleaning, transformation, exploration and analysis.

Building, training, and evaluating statistical and machine learning models for predictive and prescriptive analytics.

Applying deep learning, natural language processing, and computer vision techniques for complex problem-solving.

Creating compelling visualizations and communicating insights effectively to technical and non-technical audiences.

Stay updated with the latest advancements in AI and apply them to improve existing solutions.

Applying data-driven solutions to address business challenges and identify new opportunities.

Troubleshoot and resolve issues related to AI models and systems.

Working effectively with cross-functional teams to achieve project objectives.

Companies Hiring for this Course

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Admission Process

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

Course Fees & Financing

Course Fees

Enroll Now & Save Up To

60%

In USD

$1,049

In INR

84,999

Inclusive of All Taxes

Enroll Now →
Payment Partners

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs.

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UPCOMING BATCHES/PROGRAM COHORTS

BatchDateTime (IST)Batch Type
Online Live Instructor Led Session30 August 20259 PM to 12 AMBatch 1
Online Live Instructor Led Session14th Sept 20259 PM to 12 AMBatch 2

COMPARISON WITH OTHERS

FeatureOur CourseCOMPETITOR ACOMPETITOR B
Curriculum ScopeComprehensive: Python, ML, DL, NLP, CV, Generative AIBasic ML and DL focusGeneral AI with less focus on Generative AI
Hands-On ExperienceExtensive practical projects with tools like GPT, DALL-E 2Limited practical projectsHands-on projects mainly in traditional AI
Advanced ToolsGPT, DALL-E 2, Midjourney, Hugging Face, Transformers, GANs, RAG, LangChainFocus on traditional ML frameworksEmphasis on standard ML and AI tools
Instructor ExpertiseExperienced professionals with industry and research backgroundMix of industry and academic instructorsPrimarily academic-focused instructors
Real-World ApplicationsEmphasis on real-world problem-solving and innovationMostly theoretical applicationsGeneral applications with less focus on innovation
Career SupportStrong focus on career advancement and networkingBasic career servicesLimited career support and networking opportunities
Networking OpportunitiesConnect with peers and industry leadersLimited networking eventsFew networking opportunities
Certification ValueRecognized certification for advanced AI rolesStandard certificationGeneral certification with less industry recognition

Frequently Asked Questions