Data Science & Machine Learning with GenAI in Bhopal

Transform your career with our comprehensive Data Science, Machine Learning & Generative AI program designed for aspiring data scientists in Bhopal and Madhya Pradesh. This hands-on, project-based course covers Python fundamentals, advanced ML algorithms, Deep Learning, NLP, and cutting-edge Generative AI with RAG.

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    150k+ Placemenets to Date

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    600+ Hiring Partners

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    76 Lakhs Highest Annual

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Calendar

Next Batch starts in December

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Flexible Learning Modes to Fit Your Schedule

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

Leading tech giants and innovative startups are actively hiring data scientists and ML engineers proficient in these technologies. Graduates from Bhopal will be job-ready for top companies nationwide and globally.

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)

 NLP Engineers work on language-based AI systems, such as chatbots, sentiment analysis tools, and speech-to-text systems, using Python and NLP libraries.

Data Science Careers on the Rise in Bhopal

Leading tech giants and innovative startups are actively hiring data scientists and ML engineers proficient in these technologies. Graduates from Bhopal will be job-ready for top companies nationwide and globally.

Annual Salary

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

Hiring Companies

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

Annual Salary

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

Hiring Companies

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

Annual Salary

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

Hiring Companies

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

Annual Salary

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

Hiring Companies

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

Annual Salary

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

Hiring Companies

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

Annual Salary

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

Hiring Companies

 NLP Engineers work on language-based AI systems, such as chatbots, sentiment analysis tools, and speech-to-text systems, using Python and NLP libraries.

Course Snapshot

This comprehensive Data Science & AI program covers the complete journey from databases to Generative AI
through 8 structured modules and 400+ hours of learning. The course emphasizes
hands-on projects and real-world applications, ensuring learners in Bhopal gain industry-ready,
practical skills aligned with current market demands.

Course Details

  • Duration: 6–8 months intensive training program
  • Mode: Live online classes with recorded sessions available at the Bhopal center
  • Schedule: Weekend batches and weekday evening options
  • Support: 24/7 doubt resolution with continuous mentor guidance
  • Assessment: Weekly assignments and real-world capstone projects

Batch Options

  • Weekday Evening Batch: Monday–Friday (7:00 PM – 9:00 PM)
  • Weekend Batch: Saturday–Sunday (10:00 AM – 5:00 PM)
  • Self-Paced Online: Flexible learning with live mentor sessions

Who Should Enroll

  • Fresh graduates from IIT Indore, MANIT Bhopal, RGPV, and Barkatullah University entering Data Science & AI
  • Working professionals in Bhopal, Indore, and Madhya Pradesh transitioning into ML and AI roles
  • Software developers aiming to upskill in data science and advanced analytics
  • Business analysts seeking stronger technical and data-driven decision-making skills
  • Students pursuing computer science or related disciplines
  • Entrepreneurs planning to build AI-powered products and solutions

Course Outcomes – Skills You’ll Master

  • Database Management: Work with SQL, NoSQL, and Python database connectivity
  • Statistical Analysis: Apply descriptive and inferential statistics for actionable insights
  • Machine Learning: Build and deploy supervised and unsupervised learning models
  • Deep Learning: Implement neural networks, CNNs, and RNNs using TensorFlow
  • NLP Proficiency: Develop text processing, classification, and sentiment analysis solutions
  • Generative AI: Create RAG-based chatbots and intelligent AI assistants
  • Cloud Deployment: Deploy ML models on AWS, Azure, and GCP platforms

Data Science Course Curriculum in Bhopal

Master Tools, Techniques, and Real-World Applications

Our industry-aligned curriculum spans 8 comprehensive modules, from database fundamentals to advanced Generative AI. Each module combines theoretical concepts with practical implementation, ensuring you master both the science and art of data-driven decision making through hands-on projects and real-world applications.

Understanding Database & Connectivity

  • Introduction to Databases
  • Types of Databases (SQL and NoSQL)
  • Basics of SQL Databases
    • Types of Keys
    • Constraints
    • Schema Design
  • CRUD Operations
    • Create
    • Read
    • Update
    • Delete
  • Types of JOINS
    • Inner Join
    • Left Join
    • Right Join
    • Outer Join
  • Aggregate Functions
    • MIN
    • MAX
    • SUM
    • COUNT
    • AVG
  • Advanced SQL
    • Triggers
    • Stored Procedures
    • Control Statements Implementation
    • WITH Clause (CTE)
  • SQL Databases
    •  MySQL
    • PostgreSQL
    • SQLite
  • NoSQL Database
    • MongoDB
  • Python Database Connectivity
    • SQLite Connectivity
    • MySQL Connectivity
    • Libraries Used
      • SQLAlchemy
      • PyMySQL

Statistics & Mathematics

  • Descriptive Statistics
    • Measures of Central Tendency
      •  Mean
      • Median
      • Mode
    • Measures of Spread
      • Deviation
      • Standard Deviation
      • Variance
    • Frequency Distribution
    • Quartile Deviation
    • Data Distribution Visualization
      • Normal Distribution
      • Skewed Distribution
      • Kurtosis
  • Inferential Statistics
    • Hypothesis Testing
      • p-value
      • Confidence Intervals
      • Chi-Square Test
    • Probability Theory
      • Bayes’ Theorem
      • Probability Distributions
  • Linear Algebra for Machine Learning
    • Matrices and Vectors
      •  Transpose
      • Inverse
      • Determinants
    • Eigenvalues and Eigenvectors
      • Application in PCA and Dimensionality Reduction

Data Science (Data Engineering, Analysis & Visualization)

  • Data Engineering & Preprocessing
    • Data Extraction
      • APIs
        • Understanding API concepts
        • HTTP protocols and API methods (GET, POST, PUT, DELETE)
        • Working with APIs such as Google API, Weather API, Stock Market APIs
      • Databases
      • Web Scraping
      • Cloud Data Sources
      • Online Resources
        • Kaggle
        • Google Dataset Search
    • Data Cleaning & Transformation (using Pandas and NumPy)
      • Handling Outliers
      • Data Skewness Treatment
      • Handling Missing, None, or Empty Values
      • Data Transformation Techniques
  • Exploratory Data Analysis (EDA)
    • Data Analysis using Pandas
      • Working with 1D and 2D Data
      • Aggregate Functions
      • Data Filtering Techniques
      • Indexing and Slicing in DataFrames
      • Merging and Joining Multiple Datasets
      • GroupBy Operations
      • Sorting Data by Index and Values
      • Applying Multiple Mathematical Operations
    • Feature Engineering
      • Converting Text Data to Numerical Format
        • One-Hot Encoding
        • Label Encoding
      • Data Scaling Techniques
  • Data Visualization
    • Data Visualization Libraries
      • Pandas
      • Matplotlib
      • Seaborn
      • Plotly
    • Building Live Graphs using Real-Time Data Animation
    • Creating Interactive Dashboards using Streamlit

Machine Learning

  • Introduction to Machine Learning
    • What is an Algorithm?
    • Core Machine Learning Concepts
    • Difference between Traditional Programming and Machine Learning
    • Types of Machine Learning Algorithms
    • Online Learning vs Offline Learning
    • Understanding Training and Testing Data
  • Supervised Learning
    • Regression Models
      • Simple Linear Regression
      • Multiple Linear Regression
      • Polynomial Regression
    • Classification Models
      • Decision Trees
      • Random Forest
      • Support Vector Machine (SVM)
      • Naïve Bayes
      • K-Nearest Neighbors (KNN)
      • Logistic Regression
    • Model Evaluation Metrics
      • Confusion Matrix
      • ROC–AUC Curve
      • Precision
      • Recall
      • F1 Score
      • Classification Report
      • Accuracy Score
      • R² Score
  • Unsupervised Learning
    • Clustering Algorithms
      • K-Means Clustering
      • Hierarchical Clustering
    • Dimensionality Reduction Techniques
      • Principal Component Analysis (PCA)
      • Linear Discriminant Analysis (LDA)
      • Autoencoders
  • Model Optimization & Deployment
    • Hyperparameter Tuning
      • Grid Search
      • K-Fold Cross Validation
    • Model Deployment
      • Flask
      • Pickle
      • Joblib
    • Gradient Descent Algorithm

Natural Language Processing (NLP)

  • Text Preprocessing & Feature Engineering
    • NLP Techniques using NLTK
      • Tokenization
      • Stemming
      • Lemmatization
    • Word Embedding Concepts
      • One-Hot Encoding
      • TF-IDF (Term Frequency–Inverse Document Frequency)
      • Word2Vec
Mini Project
  • Sentiment Analysis
  • Document Classification
  • Named Entity Recognition (NER)

Deep Learning & Neural Networks

  • Neural Network Fundamentals
    • Stochastic Gradient Descent (SGD) Algorithm
    • Activation Functions
      •  ReLU
      • Sigmoid
      • Softmax
    • Backpropagation Algorithm
    • Neurons
    • Weights
    • Bias and Variance
    • Hidden Layers
  • Building & Training Neural Networks
    • Building and Training Models using TensorFlow and Keras
    • Loss Functions
    • Optimization Techniques
  • Convolutional Neural Networks (CNNs)
    • Creating CNN Models with Multiple Layers
    • Image Classification Models
    • Transfer Learning Concepts
      • ResNet
      • VGG
      • MobileNet
  • Recurrent Neural Networks (RNNs) & Transformers
    • Embedding Concepts
    • Building RNN Models with Multiple Layers
    • Transformer Architecture
      • Encoders
      • Decoders
    • BERT and GPT for NLP Applications

Generative AI (Including Retrieval-Augmented Generation – RAG)

  • Introduction to Generative AI
    • Importance of Generative AI
    • Architecture of Generative AI Systems
    • Encoder-Based Concepts
      • Generative Adversarial Networks (GANs)
      • Variational Autoencoders (VAEs)
    • Understanding Large Language Models (LLMs) and Their Working
    • Implementing Various LLMs using Open-Source APIs
  • Fine-Tuning Large Language Models
    • Adapting GPT and BERT for Custom Applications
    • Fine-Tuning Models using Hugging Face
  • Retrieval-Augmented Generation (RAG)
    • Enhancing LLMs with Real-Time Data Retrieval
    • Document Chunking and Text Splitting Techniques
    • Embedding Generation
    • Vector Databases and Vector Search
      • FAISS
      • Pinecone
      • ChromaDB
Mini Project
  • Real-World AI Chatbots and Applications

Cloud Computing

  • Introduction to Cloud Computing
    • What is Cloud Computing and Its Benefits
    • Cloud Service Models
      • Infrastructure as a Service (IaaS)
      • Platform as a Service (PaaS)
      • Software as a Service (SaaS)
  • Popular Cloud Platforms
    • Overview of Major Cloud Platforms
      • Amazon Web Services (AWS)
      • Microsoft Azure
      • Google Cloud Platform (GCP)
    • ML and Data Services Offered by Each Platform
  • Storage and Compute Services
    • Object Storage Services
      • Amazon S3
      • Azure Blob Storage
    • Virtual Machines and Scalable Compute Engines
  • Cloud Databases
    • SQL Databases
    • NoSQL Databases
  • Machine Learning Services
    • Cloud ML Platforms
      • Azure ML Studio
      • AWS SageMaker
      • Google Vertex AI
    • Drag-and-Drop ML Workspaces to
      • Build Models
      • Train Models
      • Optimize Performance
      • Deploy Models
Mini Project
  • Integrating Python Scripts and Prebuilt Modules
  • Model Versioning and Experiment Tracking
  • Model Performance Monitoring and Analysis
  • Support for Real-Time and Batch Inference

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

Apply your learning through two 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. Work on data science projects relevant to businesses in Bhopal and create portfolio pieces that showcase your skills to employers across India and globally.

The Ultimate Toolkit for Python Data Science Professionals

Industry-Recognized Data science Certification in Bhopal

Earn an industry-recognized Data Science Certification in Bhopal that validates your expertise in data analysis, machine learning, and data visualization. This certification highlights your proficiency in essential tools like Python, SQL, Power BI, and Tableau, giving you a strong competitive edge in Bhopal’s growing tech and analytics job market.

Whether you’re starting your career or advancing in your field, this credential proves 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 toward becoming a highly skilled, data-driven professional in Bhopal and beyond.

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    Professionals Trained

  • 20+

    Countries & Counting

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    Corporate Served

Our Proven Track Record Shows that we Walk the Talk

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.

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.

Aptitude & Logical Reasoning Training

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

Step by step guidance

Help students structure professional, impactful resumes

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

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

Individual Sessions

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

Our mission revolves around our learners

Promising 100% #CareerSuccess!

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Frequently Asked Questions

Yes, you’ll learn directly from experienced AI professionals with 1-on-1 guidance.

Yes, live Q&A sessions, discussion forums, and mentor support are available.

Yes, join hackathons, webinars, and group discussions to grow your network.

Yes, course materials and updates remain accessible for continued learning.

Thousands of learners have successfully completed AI & Data Science programs with Grras Solutions.

You’ll get an industry-recognized AI & Data Science certification from Grras Solutions.

Yes, it’s globally recognized and strengthens your resume internationally.

You can become a Data Scientist, AI Engineer, ML Engineer, Generative AI Specialist, or NLP Engineer.

Yes, resume building, mock interviews, LinkedIn/GitHub optimization, and placement training.

 

Placement assistance is provided through our dedicated job portal & network, with a high success rate.

Projects like Generative AI Chatbot, Sentiment Dashboard, Anime Face Generator, and Business Reporting Tools.

Yes, all projects simulate real-world scenarios to strengthen your portfolio.

Yes, from data preprocessing to model deployment.

A decent system is enough; cloud-based solutions like AWS SageMaker are also used.

Yes, they are designed to be shared on GitHub and LinkedIn.

Both options are available – online live classes and offline sessions at Jaipur.

Yes, flexible timings are designed for students, working professionals, and career changers.

Yes, learners can choose formats as per their convenience.

Recorded sessions and backup classes are available.

Yes, sessions and assignments are structured for flexible, self-paced learning.

Primarily Python, along with libraries like NumPy, Pandas, and Matplotlib.

You’ll learn TensorFlow, PyTorch, Hugging Face, LangChain, and AWS SageMaker.

Yes, Natural Language Processing (NLP) with transformers, LLMs, and RAG is a key module.

Yes, including chatbots, GANs, and image-to-image conversion models.

Yes, you’ll deploy models using AWS SageMaker and similar tools.

This course covers Data Science, Machine Learning, Deep Learning, and Generative AI with practical industry projects.

Aspiring AI engineers, data analysts, Python developers, students, working professionals, entrepreneurs, and freelancers.

Basic Python helps, but it’s not compulsory. We teach fundamentals before moving to advanced AI.

It is a 180-hour program, designed for in-depth learning and project-based training.

It blends theory, real-world projects, expert mentorship, and placement support, making you industry-ready.

Yes, you’ll learn directly from experienced AI professionals with 1-on-1 guidance.

Yes, live Q&A sessions, discussion forums, and mentor support are available.

Yes, join hackathons, webinars, and group discussions to grow your network.

Yes, course materials and updates remain accessible for continued learning.

Thousands of learners have successfully completed AI & Data Science programs with Grras Solutions.

You’ll get an industry-recognized AI & Data Science certification from Grras Solutions.

Yes, it’s globally recognized and strengthens your resume internationally.

You can become a Data Scientist, AI Engineer, ML Engineer, Generative AI Specialist, or NLP Engineer.

Yes, resume building, mock interviews, LinkedIn/GitHub optimization, and placement training.

 

Placement assistance is provided through our dedicated job portal & network, with a high success rate.

Projects like Generative AI Chatbot, Sentiment Dashboard, Anime Face Generator, and Business Reporting Tools.

Yes, all projects simulate real-world scenarios to strengthen your portfolio.

Yes, from data preprocessing to model deployment.

A decent system is enough; cloud-based solutions like AWS SageMaker are also used.

Yes, they are designed to be shared on GitHub and LinkedIn.

Both options are available – online live classes and offline sessions at Jaipur.

Yes, flexible timings are designed for students, working professionals, and career changers.

Yes, learners can choose formats as per their convenience.

Recorded sessions and backup classes are available.

Yes, sessions and assignments are structured for flexible, self-paced learning.

Primarily Python, along with libraries like NumPy, Pandas, and Matplotlib.

You’ll learn TensorFlow, PyTorch, Hugging Face, LangChain, and AWS SageMaker.

Yes, Natural Language Processing (NLP) with transformers, LLMs, and RAG is a key module.

Yes, including chatbots, GANs, and image-to-image conversion models.

Yes, you’ll deploy models using AWS SageMaker and similar tools.

This course covers Data Science, Machine Learning, Deep Learning, and Generative AI with practical industry projects.

Aspiring AI engineers, data analysts, Python developers, students, working professionals, entrepreneurs, and freelancers.

Basic Python helps, but it’s not compulsory. We teach fundamentals before moving to advanced AI.

It is a 180-hour program, designed for in-depth learning and project-based training.

It blends theory, real-world projects, expert mentorship, and placement support, making you industry-ready.

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