Data Science & Machine Learning with GenAI

Transform your career with our comprehensive Data Science, Machine Learning & Generative AI program. This hands-on, project-based course covers Python fundamentals, advanced ML algorithms, Deep Learning, NLP, and cutting-edge Generative AI with RAG. Master data preprocessing, model training, hyperparameter tuning, and deployment through real-world projects that prepare you for industry challenges.

150k+ Placemenets to Date
600+ Hiring Partners
76 Lakhs Highest Annual

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Next Batch starts in November

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Flexible Learning Modes to Fit Your Schedule

Interactive Classroom Sessions
Live Virtual Instructor-Led Classes
Self-Guided Online Modules
Corporate Onsite
Training

Build an Impressive Portfolio

Expand Your Career Opportunities

Stay Ahead with Industry Trends

Master Cutting-Edge Development Tools

Data Science Careers on the Rise

Master the full spectrum from databases to Generative AI through 8 comprehensive modules covering 400+ hours of content with hands-on projects and real-world applications.

Designation

Annual Salary

Hiring Companies

₹8–15 LPA (Entry-Level), ₹15–25 LPA (Mid-Level), ₹30+ LPA (Senior-Level)

Data Scientists extract insights from structured and unstructured data using Python, R, SQL, and machine learning frameworks to drive strategic decision-making.

₹6–15 LPA (Entry-Level), ₹15–25 LPA (Mid-Level), ₹25–40+ LPA (Senior-Level)

Machine Learning Engineers develop predictive models, design algorithms, and deploy AI solutions using tools like TensorFlow, PyTorch, and Scikit-learn.

₹6–12 LPA (Entry-Level), ₹12–25 LPA (Mid-Level), ₹25+ LPA (Senior-Level)

Data Engineers build scalable data pipelines, manage databases, and optimize data flows for analysis.

₹8–20 LPA (Entry-Level), ₹20–35 LPA (Mid-Level), ₹35+ LPA (Senior-Level)

AI Specialists design and develop intelligent systems, focusing on natural language processing, computer vision, and AI-driven solutions.

₹5–10 LPA (Entry-Level), ₹10–18 LPA (Mid-Level), ₹18+ LPA (Senior-Level)

Statisticians use statistical methods and tools to analyze data, interpret results, and make recommendations for business and research purposes.

₹8–18 LPA (Entry-Level), ₹20–35+ LPA (Mid-Level)

Program Structure

Duration: 4–5 months intensive program
Mode: Online & Offline classes with hand -on coding
Format: Theory lectures, live coding, guided practice, capstone projects, and code reviews
Support: 24/7 doubt resolution and mentor guidance
Assessment: Weekly assignments and capstone projects
Learning Path: Foundations → Statistics → Data Analysis → Data Visualization → Machine Learning→ Deep Learning & NLP → Gen Ai → Deployment → Projects

Who Should Enroll

Fresh graduates aiming to begin a career in Data Science, Analytics, or AI
- Working professionals planning to shift into data-driven roles or machine learning
- Software developers looking to expand into predictive modeling and automation
- Business analysts who want deeper analytical and technical capability
- Students pursuing computer science, IT, engineering, mathematics, or related fields
- Entrepreneurs looking to build or scale AI-powered products and solutions

What You’ll Learn

Use essential tools for data science and AI practice
Manage databases (SQL/NoSQL) and Python data connectivity
Build ML & DL models, NLP pipelines, and GenAI assistants
Create and fine-tune GenAI applications using LLMs, embeddings, vector stores, and prompt engineering
Deploy to AWS, Azure, and GCP with best-practice workflows

Data Science Course Curriculum

Master Tools, Techniques, and Real-World Applications

Prerequisite: Python Programming Essentials

Python Basics: Data types, loops, conditional Statements

Functions, Modules, Exception Handling

File Handling, JSON, CSV

OOPs Concepts in Python

Module 1: Data Collection & Connectivity

Advanced SQL Concepts

2.01 Procedures
2.01 Triggers
2.01 CTE

REST API Integration

2.02 Working with public & enterprise APIs, JSON/XML response handling, authentication methods (User Agent , API Keys)

Web Scraping Techniques

2.03 BeautifulSoup

NoSQL Connectivity

2.04 MongoDB CRUD operations

Python Database Connectivity

2.05 SQLAlchemy
2.05 Database Connectivity

Mini Project

Live Weather / Stock Data Fetching via REST API
Automated Web Scraper for E-Commerce Price Tracking
SQL-Backed Reporting Dashboard with Real-Time Queries

Module 2: Statistics & Mathematics for Data Science

Descriptive & Inferential Statistics

3.01 Mean, Median, Mode , Variance, Standard Deviation, Frequency Tables, Sampling Theory

Probability & Distributions

3.02 Bayes Theorem
3.02 Normal Distribution
3.02 Binomial
3.02 Poisson

Hypothesis Testing & Statistical Validation

3.03 t-test
3.03 p-test

Correlation & Feature Relationships

3.04 Covariance,
3.04 Correlation
3.04 Coefficient
3.04 Multicollinearity
3.04 Feature Impact

Mathematics for ML

3.05 Matrix Operations
3.05 Eigen Values

Module 3: Data Engineering, Analysis & Visualization

Data Acquisition & Storage

4.01 CSV
4.01 JSON
4.01 API's
4.01 Database Fetching and Data Pipelines

Data Cleaning & Transformation

4.02 Handling missing values
4.02 Outliers Detection
4.02 Scaling
4.02 Normalization
4.02 Encoding
4.02 Feature Extraction

Exploratory Data Analysis (EDA) using Pandas

4.03 Trend discovery
4.03 Correlation mapping
4.03 Statistical insights
4.03 Pattern recognition

Feature Engineering

4.04 Binning
4.04 One-Hot-Encoding
4.04 Feature Selection
4.04 Label Encoding
4.04 Standardization

Visualization Techniques

4.05 Matplotlib & Seaborn for analytical charts
4.05 Plotly & Streamlit for interactive dashboards

Mini Project

Dashboard for Sales Trends using an Interactive Frontend
Real-Time Data Visualization from APIs
(Stock/Weather/Live Data) Cricket / Sports Analytics Dashboard with Insights and Patterns

Module 4: Machine Learning (Supervised & Unsupervised)

Core ML Foundations

5.01 Training & validation workflow
5.01 overfitting vs underfitting
5.01 data splitting
5.01 bias-variance tradeoff

Supervised Learning Algorithms

5.02 Regression Models : - Linear - Polynomial
5.02 Classification Models: - Logistic Regression, SVM, KNN, Naive Bayes, Decision Trees, Random Forest.

Unsupervised Learning Techniques

5.03 Clustering
5.03 K-means
5.03 Hierarchical
5.03 DBSCAN

Dimensionality Reduction:

5.04 PCA
5.04 Autoencoders

Model Performance & Evaluation Metrics

5.05 Accuracy Score
5.05 Precision & Recall
5.05 F1-Score
5.05 ROC-AUC
5.05 Confusion Matrix
5.05 RMSE → Root Mean Square Error
5.05 MSE → Mean Squared Error
5.05 MAE → Mean Absolute Error

Model Saving

5.06 Pickle
5.06 Joblib serialization

Mini Project

Loan/Fraud/Customer Churn Prediction Model
E-Commerce Product Recommendation System
Live Data Charting & Model Output Using Matplotlib Animation

Module 5: Natural Language Processing (NLP)

Text Preprocessing & Cleaning

6.01 Tokenization
6.01 Lemmatization
6.01 Stemming
6.01 Stopwords removal
6.01 N-Grams

Feature Extraction & Embeddings

6.02 TF-IDF
6.02 Bag of Words
6.02 Word2Vec
6.02 Sentence Embeddings (S-BERT)

Core NLP Applications

6.03 Text Classification
6.03 Spam Filtering
6.03 Topic Modeling
6.03 Named Entity Recognition (NER)
6.03 Keyword Extraction

Sentiment & Intent Analysis

6.04 Emotion classification
6.04 polarity scoring, and language understanding
6.04

End-to-End NLP Pipelines

6.05 Model building
6.05 evaluation, exporting, and integration with real-time applications
6.05

Mini Project

Twitter sentiment analysis
Resume classification system for HR filtering

Module 6: Deep Learning & Neural Networks

Neural Network Foundations

7.01 Perceptron
7.01 Activation Function
7.01 Loss Function
7.01 Gradient Descent
7.01 Backpropgation

Model Architectures & Frameworks

7.02 TensorFlow
7.02 Keras
7.02 PyTorch

Computer Vision with CNN

7.03 Convolutional Layers
7.03 Pooling
7.03 Dropout
7.03 Batch Normalization
7.03 Tensor operations

Sequence Modeling

7.04 RNN
7.04 LSTM
7.04 GRU

Transfer Learning

7.05 Pre-trained Models
7.05 VGG
7.05 ResNet
7.05 MobileNet

Mini Project

Image classification using CNN

Module 7: Generative AI & Retrieval-Augmented Generation (RAG)

Generative AI Fundamentals

8.01 LLMs
8.01 GPT-style architectures

Fine-Tuning & Customization

8.02 Hugging Face

RAG (Retrieval-Augmented Generation)

8.03 Document ingestion
8.03 Retrieval pipelines
8.03 context-based answer generation
8.03 Grounding responses to real data

Integration of ML Models in Live Applications

AI Assistants & Automation

8.05 Chatbots
8.05 content generation
8.05 summarization
8.05 Translation & report automation
8.05 Personalization systems

CI/CD Pipeline for ML Model Deployment

Mini Project

AI chatbot with Fine - Tuning
AI Text Summarizer
Personalized blog content generator using GPT

Module 8: Cloud Computing for AI

Cloud Concepts

9.01 IaaS
9.01 PaaS
9.01 SaaS

Platforms Overview

9.02 AWS
9.02 Azure
9.02 GCP

Services for ML Automation

9.03 SageMaker

Mini Project

Image classification using CNN

Learn by Doing | Real-World Projects for Data Science Mastery

Apply your learning through 2 capstone projects: create comprehensive analytical reports from real-world datasets and develop an intelligent RAG-powered chatbot, demonstrating end-to-end data science and AI implementation skills

Car Price Predictor: Informed Valuations for the Used Car Market

#01

The Car Price Predictor project is a web-based application that allows users to estimate the selling price of used cars by inputting key details, such as mileage and year of manufacture. The application leverages a linear regression model, trained on historical data, to generate price predictions. Users can interact with…

LoanPredictor: Intelligent Loan Approval Estimator

#02

The Loan Prediction project is a web-based application that leverages data science to estimate loan approval outcomes. Users enter vital financial details, such as income and credit score, into an intuitive interface built with Flask. The system employs a Random Forest model, developed using Scikit-learn, which is trained on historical…

Wine Quality Predictor: AI-Powered Wine Assessment

#03

The Wine Quality Predictor project is a machine learning-based application designed to assess wine quality based on key chemical properties. Using a linear regression model built with Scikit-learn, the system analyzes features like acidity, alcohol content, and pH level to estimate a quality score. The project evaluates the model's accuracy…

IPL Score Predictor: Smart Cricket Score Estimation

#04

The IPL Score Predictor project is a machine learning-based model designed to estimate the final score of an IPL match based on key in-game factors. Using a linear regression model built with Scikit-learn, the system analyzes inputs like current runs, wickets, and overs to predict the total score at the…

Movie Magic: AI-Powered Movie Recommendation System

#05

The Movie Magic project is a machine learning-powered recommendation system designed to suggest movies based on user preferences and past ratings. Using collaborative filtering and content-based recommendation techniques, the model analyzes user behavior, movie details, and rating patterns to uncover personalized movie suggestions. The system evaluates its recommendation accuracy by…

E-Commerce Customer Spending Predictor: Data-Driven Insights for Business Growth

#06

The E-Commerce Customer Spending Predictor is a machine learning-based project that helps businesses understand and forecast customer spending behavior. Using a linear regression model built with Scikit-learn, the system analyzes key factors such as session length, time spent on the app, and other user interactions to estimate yearly spending. This…

Diabetes Prediction: AI-Powered Health Risk Assessment

#07

The Diabetes Prediction project is a machine learning-based model designed to assess the likelihood of diabetes in individuals based on key health indicators. The dataset, sourced from Kaggle, originates from the National Institute of Diabetes and Digestive and Kidney Diseases and includes features such as Number of Pregnancies, Insulin Level,…

Arrhythmia Classification AI-Powered ECG-Based Heart Health Assessment

#08

The Arrhythmia Classification project leverages machine learning to detect and classify different types of arrhythmia using ECG data. The dataset consists of 452 samples and 16 classes, including both normal and various arrhythmia conditions. A major challenge is the high-dimensional nature of the data, with 279 features exceeding the number…

The Ultimate Toolkit for Python Data Science Professionals

Ai

Data Analytics

Data Modeling

Data Visualization

Data-Engineering

Machine Learning

Math Algorithm

MLOps

NumPy

Pandas

Pyspark

Python

Industry-Recognized Data science Certfication

Earn an industry-recognized Data Science Certification that validates your expertise in data analysis, machine learning, and data visualization. This credential highlights your proficiency in essential tools like Python, SQL, Power BI, and Tableau, giving you a competitive edge in the job market. Whether you’re starting your career or advancing in your field, this certification demonstrates your ability to solve real-world business problems and opens doors to high-paying roles at top companies. Build credibility, gain confidence, and accelerate your journey to becoming a data-driven professional.

20000+

Professionals Trained
20+

Countries & Counting
100+

Corporate Served

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Our Proven Track Record Shows that we Walk the Talk

Aditi Naruka

Cloud ops Engineer

Jaipur

Aditi Naruka has successfully completed the 4-month Devops and Cloud Computing program and secured a placement.

Raghav Bahad

Data Analyst

Jaipur

Raghav Bahad has successfully completed the 4-month Data Analyst program and secured a placement.

Suhaib Illyas

Python developer

Jaipur

Suhaib Illyas has successfully completed the 3-month PYTHON program and secured a placement.

Gourav Khatri

Data Analyst

Jaipur

Gourav Khatri has successfully completed the 4-month Data Analyst program and secured a placement.

Shamrez Khan

MIS Executive

Jaipur

Shamrez Khan has successfully completed the 4-month Data Analyst program and secured a placement.

Arbaj Khan

Graphic Designer

Jaipur

Arbaj khan has successfully completed the 4-month Ui Ux design program and secured a placement.

Why Choose Grras Solutions?

Industry-Aligned Curriculum

Master a curriculum crafted and constantly updated by industry experts to match real-world trends, ensuring every concept and project builds job-ready, future-proof skills.

Personalized Career Support

Receive one-on-one mentorship, resume reviews, mock interviews, and complete placement assistance through our 500+ hiring partners to accelerate your tech career.

Expert Mentorship

Learn directly from certified professionals with years of hands-on experience who guide you through every module, project, and career milestone personally.

Real-World Projects

Gain practical exposure by working on live, industry-grade projects that mirror real business challenges, strengthening your technical execution and problem-solving abilities.

Proven Track Record

Join thousands of successful learners who have launched rewarding tech careers through Grras. Our consistent placement results, trusted partnerships, and alumni success stories speak for the quality of our training.

From Training to Placement A Roadmap to Success

Navigate your professional journey with a comprehensive guide that transforms learning into opportunity. Discover proven strategies to build skills, gain experience, and secure your ideal position in today's competitive job market.

Building Strong Foundation

Expert Training sessions123

Focus on industry-relevant skills

Hands on projects & Assignments

Real-world projects to implement learned concepts.

Performance Tracking

Weekly tests to assess progress
Sharpening Interview Readiness

Mock Interviews

Mock sessions with real-time feedback from experts

Expert Sessions

Host industry experts for advanced technical guidance

Skill Refinement Tasks

Focus on problem-solving, critical thinking, and domain expertise
Communication & Aptitude Skill Development

Effective Communication & Presentation Skills

Through interactive classes, students enhance both verbal and non-verbal communication, while also learning to present their ideas clearly, confidently, and effectively.

Aptitude & Logical Reasoning Training

Enhances students' problem-solving, analytical thinking, and numerical ability-preparing them for competitive exams and placement tests.
Resume building masterclasses

Step by step guidance

Help students structure professional, impactful resumes
Bridging the Gap

Industry networking

* Partner with top companies for hiring pipelines
* Conduct webinars and sessions with recruiters

Placement coordination

* Connect candidates to aligned opportunities
* Organize hiring events and recruitment drives
Advance interview boot camp

Stress Management Techniques

Equip students to handle high-pressure interview situations

Scenario-Based Training

Prepare students for various interview formats, including case studies, coding rounds, and group discussions
Personalized 1:1 guidance

Individual Sessions

* Address specific weaknesses and barriers to success.
* Develop personalized improvement plans

Expert Training sessions123

Focus on industry-relevant skills

Hands on projects & Assignments

Real-world projects to implement learned concepts.

Performance Tracking

Weekly tests to assess progress

Mock Interviews

Mock sessions with real-time feedback from experts

Expert Sessions

Host industry experts for advanced technical guidance

Skill Refinement Tasks

Focus on problem-solving, critical thinking, and domain expertise

Effective Communication & Presentation Skills

Through interactive classes, students enhance both verbal and non-verbal communication, while also learning to present their ideas clearly, confidently, and effectively.