Best Data Science Course in Surat
Data Science & Predictive Modeling Course
Our data science course in Surat turns you into a job-ready data scientist: Python, statistics, data visualisation, machine learning, deep learning, NLP and AI applications, learned through more than ten real projects. Classes run at our City Light campus and online, with practical work in every module.
Why choose data science
Every business now collects data, and the people who can clean it, find patterns and build predictive models help companies decide what to sell, whom to target and where to cut risk. Data science skills are valued in IT, finance, e-commerce, manufacturing and textiles, including many businesses in Surat.
Who this data science training is for
- Students after 12th, BCA, B.Sc IT, B.Com, B.Sc and engineering students who like numbers and problem solving.
- Data analysts who want to move into machine learning.
- Developers who want to work with data and AI.
- Beginners: the course starts with Python, NumPy and Pandas from the basics.
What you will learn
- Python for data: Python basics, Jupyter, Colab and VS Code, NumPy arrays and Pandas data handling and cleaning.
- Maths and statistics: linear algebra basics, gradient descent, descriptive statistics, probability, distributions and correlation.
- Visualisation and EDA: Matplotlib and Seaborn, exploratory data analysis, feature engineering and preprocessing.
- Machine learning: regression and classification models, evaluation, cross-validation, hyperparameter tuning and ML pipelines.
- Advanced models: clustering, PCA, anomaly detection, Random Forest, Gradient Boosting, XGBoost, LightGBM and explainable AI.
- Deep learning: neural networks in PyTorch and TensorFlow/Keras, CNNs for images, transfer learning and time series forecasting.
- NLP and AI apps: text classification, Transformers and Hugging Face, embeddings, vector databases, RAG, Streamlit, Gradio and FastAPI.
- MLOps: experiment tracking, model versioning, Docker and deployment to Render or Hugging Face Spaces.
Projects you will build
Projects follow the syllabus: house price, salary, customer churn and loan approval prediction, customer segmentation with RFM and K-Means, fraud detection and credit risk models, image classification and sales forecasting, an AI-powered document search engine, chat with PDF and an AI document assistant, ending with an end-to-end capstone deployed online.
Data science course fees
The fee for the Data Science and Predictive Modeling course is ₹50,000. Call +91 95109 90292 for the current batch duration and timings, or book a free demo class at our City Light campus. Online batches are available across Surat.
Career after data science training
Graduates apply for roles such as Data Scientist, Machine Learning Engineer, Data Analyst and AI Developer. Our placement assistance covers your project portfolio, resume and interview preparation.
Data science or data analytics?
Choose data science to build predictive models and AI applications. Choose our data analytics course if you want SQL, Excel, Power BI and business reporting. For LLMs and AI agents, see the AI and machine learning course.
Duration: 12 Months · Fees: ₹50,000
Course Curriculum
Module 1: Python, NumPy & Pandas for AI/ML
- Python Programming Foundations
Python basics, data structures, functions, file handling, and OOP basics. - AI/ML Development Environment
Jupyter Notebook, Google Colab, Anaconda, and VS Code setup. - NumPy for Numerical Computing
Arrays, indexing, slicing, matrix operations, and numerical calculations. - Pandas for Data Handling
DataFrame, Series, reading datasets, filtering, grouping, merging, and aggregation. - Data Cleaning
Handling missing values, duplicate values, incorrect data types, and messy datasets.
Module 2: Mathematics & Statistics for Machine Learning
- Mathematics for ML
Linear algebra basics, vectors, matrices, and gradient descent introduction. - Descriptive Statistics
Mean, median, mode, variance, standard deviation, and data distribution. - Probability & Data Relationships
Probability basics, normal distribution, correlation, and outlier understanding.
Module 3: Data Visualization, EDA & Feature Engineering
- Data Visualization
Matplotlib, Seaborn, charts, graphs, and visual storytelling. - Exploratory Data Analysis (EDA)
Data distribution, patterns, trends, outliers, and business insights. - Feature Engineering
Feature selection, feature creation, categorical encoding, scaling, and normalization. - Data Preprocessing
Train-test split, data leakage prevention, and preprocessing workflow.
Module 4: Supervised Machine Learning
- Regression Models
Linear Regression, Multiple Linear Regression, Ridge Regression, and Lasso Regression. - Classification Models
Logistic Regression, KNN, SVM, Naive Bayes, and Decision Trees. - Model Performance Metrics
Regression and classification evaluation metrics. - Projects
- House Price Prediction
- Salary Prediction
- Customer Churn Prediction
- Loan Approval Prediction
Module 5: Model Evaluation & Hyperparameter Tuning
- Model Evaluation
Training, testing, validation, cross-validation, and model comparison. - Hyperparameter Tuning
GridSearchCV, RandomizedSearchCV, and parameter optimization. - Model Saving & Reuse
Pickle, Joblib, and reusable model files. - ML Workflow
Building complete machine learning pipelines.
Module 6: Unsupervised Learning & Clustering
- Clustering Techniques
K-Means Clustering, Elbow Method, and Silhouette Score. - Dimensionality Reduction
Principal Component Analysis (PCA). - Anomaly Detection
Basic anomaly detection concepts. - Project
- Customer Segmentation using RFM and K-Means.
Module 7: Advanced Machine Learning & Ensemble Models
- Tree-Based Models
Decision Trees and advanced tree-based concepts. - Ensemble Learning
Bagging, Boosting, and model combination techniques. - Advanced ML Models
Random Forest, Gradient Boosting, XGBoost, and LightGBM. - Model Interpretation
Feature importance and explainable AI concepts. - Projects
- Fraud Detection
- Credit Risk Prediction
- Business Forecasting Problems
Module 8: Deep Learning, Computer Vision & Time Series
- Neural Network Foundations
Neural networks, activation functions, loss functions, and backpropagation. - Deep Learning Frameworks
PyTorch and TensorFlow/Keras. - Computer Vision
Image data, CNNs, image classification, and transfer learning. - Time Series Forecasting
Trend, seasonality, and forecasting models. - Projects
- Image Classification
- Sales Forecasting
Module 9: NLP, Embeddings & Semantic Search
- Natural Language Processing
Text cleaning, tokenization, TF-IDF, sentiment analysis, and text classification. - Transformer Models
Introduction to Transformers and Hugging Face. - Embeddings
Word embeddings, sentence embeddings, and semantic similarity. - Vector Databases
ChromaDB, FAISS, Pinecone overview, and vector search. - Project
- AI-Powered Document Search Engine.
Module 10: AI App Development, FastAPI & RAG
- AI App Development
Streamlit applications and Gradio demos. - API Development
FastAPI for ML and AI applications. - Retrieval-Augmented Generation (RAG)
Document loading, chunking, embeddings, vector databases, retrieval, and PDF Q&A.
Why LLMs need external data.
RAG architecture and workflow. - LLM Application Development
Prompt engineering, structured outputs, API integration, and chatbot workflows. - Projects
- Chat with PDF
- AI Chatbot
- AI Document Assistant
Module 11: MLOps, LLMOps & AI System Design
- MLOps & LLMOps
Experiment tracking, model versioning, and AI workflow management. - Deployment
Docker, Render, and Hugging Face Spaces. - Production Architecture
API architecture, vector databases, cost optimization, latency, and security. - Monitoring & Maintenance
Logging, monitoring, and production readiness checklist. - Capstone Project
- End-to-end AI application development and deployment.
Why Choose Extrabits for Data Science & Predictive Modeling Course Training?
At Extrabits Academy, we provide the best Data Science Course in Surat, offering more than just theory - we provide an opportunity to enhance your career with practical knowledge and live project experience.
Gain insights from professionals with years of real-world experience.
Work on live projects and build a portfolio that stands out.
Choose from weekend or weekday batches to suit your schedule.
Master core concepts and advanced techniques in modern technology.
Apply your skills to solve real business problems through case studies.
Earn a recognized certificate to boost your career opportunities.
Student Reviews
Rated 4.9/5 ★ from 109 Google reviews
Google review · Jul 2026
★★★★★
"ExtraBits Academy is an excellent place to learn computer programming. The instructors explain concepts clearly and make even difficult programming languages easy to understand. The curriculum is well-structured, with a good balance of theory and hands-on practice. The supportive learning environment and practical projects helped me improve my coding skills and confidence. I highly recommend..."
Google review · Oct 2025
★★★★★
"I had a great experience at ExtraBits. The teacher is extremely supportive, friendly, helpful, and always encourages students to ask questions. Their way of explaining concepts is simple and easy to understand. They’re also very patient and make sure that every student is comfortable with the topic before moving on. Overall, it’s a very positive and motivating environment for learning.🫶🏻"
Google review · Oct 2024
★★★★★
"In my time at extrabits , I witnessed a remarkable improvement in my IT skills and a boost in my confidence. The results speak for themselves, with many students excelling in exams and securing rewarding positions"
FAQs about the Data Science Course in Surat
What is the fee for the data science course in Surat?
The Data Science and Predictive Modeling course at ExtraBits Academy costs ₹50,000. Call +91 95109 90292 for the current batch duration, timings and payment options.
Do I need a maths or coding background for data science?
No. The course starts with Python and teaches the statistics and mathematics you need for machine learning step by step.
What projects are included in the data science course?
House price, salary, churn and loan approval prediction, customer segmentation, fraud detection, credit risk, image classification, sales forecasting, a document search engine and chat with PDF, plus a deployed capstone.
Does the course include machine learning and deep learning?
Yes. You learn regression, classification, clustering and ensemble models with Scikit-Learn, XGBoost and LightGBM, then deep learning with PyTorch and TensorFlow/Keras.
What is the difference between data science and data analytics?
Data science focuses on predictive models, machine learning and AI applications. Data analytics focuses on SQL, Excel, Power BI and business reporting. Our counsellors can help you choose.
Is placement assistance included?
Yes. We help you build a project portfolio, prepare your resume and practise data science interviews.
Where are the data science classes in Surat held?
At our campus on the 3rd floor of Agrasen Shopping Point, City Light Road, Athwa, Surat 395007. Online batches are also available across Surat.
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