Best Full Stack Data Science & AI Course Training Institute

Full Stack Data Science & AI

Full Stack Data Science & AI is a comprehensive program designed to equip learners with the skills required to analyze data, build machine learning models, create AI-powered applications, and deploy intelligent solutions. This course combines Data Science, Machine Learning, Deep Learning, Generative AI, Python programming, data visualization, and cloud technologies to prepare students for high-demand careers in Artificial Intelligence.

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Commercial

Industry Standard

Every 2 Weeks

New Batch Starts

Classroom / Remote

Training Modes

model

fit(X, y)

accuracy

99.4%

predict()

success

🤖

import

torch

Full Stack Data Science & AI

REST APIs

SQL & Databases

Docker

AWS Cloud

Git & GitHub

Production Deployment

Full Stack Data Science & AI

REST APIs

SQL & Databases

Docker

AWS Cloud

Git & GitHub

Production Deployment

Program Overview

Full Stack Data Science & AI Includes

Python Programming

Learn Python programming from scratch, including data structures, functions, object-oriented programming, and libraries used in Data Science.

Statistics & Mathematics

Understand probability, statistics, linear algebra, calculus basics, and mathematical concepts essential for building AI and Machine Learning models.

Data Analysis

Learn how to clean, process, transform, and analyze structured and unstructured data using industry-standard tools.

Data Visualization

Create interactive dashboards and meaningful visualizations using Matplotlib, Seaborn, Plotly, and Power BI to communicate insights effectively.

SQL & Databases

Master SQL queries, database design, MySQL, and MongoDB for efficient data storage, retrieval, and management.

Machine Learning

Develop predictive models using supervised and unsupervised learning techniques with Scikit-learn.

Deep Learning

Build Artificial Neural Networks, CNNs, RNNs, and LSTM models using TensorFlow and PyTorch.

Generative AI

Learn Prompt Engineering, Large Language Models (LLMs), OpenAI APIs, Gemini APIs, LangChain, Hugging Face, and Retrieval-Augmented Generation (RAG).

AI Agents & Automation

Build intelligent AI agents, automate workflows, integrate APIs, and develop AI-powered business applications.

Cloud Deployment

Deploy Machine Learning models and AI applications using cloud platforms, Docker, FastAPI, and CI/CD pipelines.

Prerequisites & Eligibility

Skills & Qualifications

Anyone passionate about Data Science and Artificial Intelligence can join this course. Recommended qualifications include: Basic Computer Knowledge Basic Mathematics Logical Thinking

Note: Designed for students, freshers, and IT working professionals aiming to master Full Stack Data Science & AI with commercial project experience and 100% placement support.

Key Competencies Covered

Python NumPy Pandas Scikit-learn TensorFlow PyTorch OpenAI API Google Gemini Hugging Face LangChain FastAPI Power BI

Curriculum Breakdown

Full Stack Data Science & AI Syllabus

Comprehensive hands-on modules extracted directly from our official training document.

Module 1 – Python Programming

Module 1 Topic Coverage (Theory + Live Coding)

Python Fundamentals

Data Structures

Functions

OOP

Exception Handling

File Handling

Includes Hands-On Labs Real-World Practice

Module 2 – Mathematics for AI

Module 2 Topic Coverage (Theory + Live Coding)

Probability

Statistics

Linear Algebra

Calculus Basics

Includes Hands-On Labs Real-World Practice

Module 3 – Data Analysis

Module 3 Topic Coverage (Theory + Live Coding)

NumPy

Pandas

Data Cleaning

Feature Engineering

Exploratory Data Analysis (EDA)

Includes Hands-On Labs Real-World Practice

Module 4 – Data Visualization

Module 4 Topic Coverage (Theory + Live Coding)

Matplotlib

Seaborn

Plotly

Power BI

Includes Hands-On Labs Real-World Practice

Module 5 – SQL & Databases

Module 5 Topic Coverage (Theory + Live Coding)

SQL

MySQL

MongoDB

Database Design

Includes Hands-On Labs Real-World Practice

Module 6 – Machine Learning

Module 6 Topic Coverage (Theory + Live Coding)

Regression

Classification

Clustering

Recommendation Systems

Model Evaluation

Includes Hands-On Labs Real-World Practice

Module 7 – Deep Learning

Module 7 Topic Coverage (Theory + Live Coding)

Artificial Neural Networks

CNN

RNN

LSTM

TensorFlow

PyTorch

Includes Hands-On Labs Real-World Practice

Module 8 – Generative AI

Module 8 Topic Coverage (Theory + Live Coding)

Prompt Engineering

OpenAI API

Gemini API

Hugging Face

LangChain

Vector Databases

RAG

AI Chatbots

Includes Hands-On Labs Real-World Practice

Module 9 – AI Agents & Automation

Module 9 Topic Coverage (Theory + Live Coding)

AI Agents

Workflow Automation

AI APIs

FastAPI

Intelligent Applications

Includes Hands-On Labs Real-World Practice

Module 10 – Deployment

Module 10 Topic Coverage (Theory + Live Coding)

Docker

Cloud Deployment

CI/CD

Model Deployment

API Deployment

Includes Hands-On Labs Real-World Practice

Practical Labs

Projects You'll Build

Build commercial portfolio-grade applications during your training.

Customer Churn Prediction

Predict customer retention using Machine Learning classification algorithms and feature engineering.

AI Resume Screening System

Automatically analyze resumes and recommend suitable candidates using NLP and machine learning.

Sales Forecasting Dashboard

Build a time-series forecasting model that predicts future sales using historical transaction data.

Medical Diagnosis Prediction

Develop predictive healthcare diagnosis models using supervised learning algorithms.

AI Chatbot with LangChain & LLMs

Create an intelligent chatbot using OpenAI or Gemini APIs with LangChain and vector embeddings.

Movie & Product Recommendation System

Build a personalized recommendation engine using collaborative filtering and matrix factorization.

Image Classification with CNNs

Develop a Deep Learning model to classify images using Convolutional Neural Networks in PyTorch/TensorFlow.

Sentiment Analysis Engine

Analyze customer reviews and social media feedback using Natural Language Processing.

AI Document Q&A System with RAG

Build an application that summarizes documents and answers user queries using Retrieval-Augmented Generation.

Financial Fraud Detection System

Develop an anomaly detection Machine Learning model to identify fraudulent financial transactions.

Got Questions?

We are here to help.

Everything you need to know before enrolling in the Full Stack Data Science & AI program.

01 What is Full Stack Data Science & AI?

It is a complete program covering Python, Data Analysis, Machine Learning, Deep Learning, Generative AI, AI Agents, and deployment to build end-to-end AI solutions.

02 Who can join this course?

Students, graduates, working professionals, engineers, software developers, and anyone interested in Data Science and AI can join.

03 Do I need programming experience?

No. The course begins with Python basics and gradually advances to AI and Deep Learning concepts.

04 Does the course include Machine Learning and Deep Learning?

Yes. You'll learn supervised learning, unsupervised learning, neural networks, CNNs, RNNs, TensorFlow, and PyTorch.

05 Will I learn Generative AI?

Yes. The curriculum includes Prompt Engineering, ChatGPT integration, OpenAI API, Gemini API, LangChain, Hugging Face, Vector Databases, and RAG.

06 What projects will I build?

You'll build AI chatbots, recommendation systems, fraud detection models, resume screening systems, document analyzers, image classifiers, and predictive analytics applications.

07 Will I receive placement assistance?

Yes. We provide resume preparation, mock interviews, real-time projects, internship opportunities, career guidance, and placement assistance.

08 Will I receive a certificate?

Yes. Students who successfully complete the course and project work will receive a Course Completion Certificate. Internship certificates may also be provided based on eligibility.

09 What AI tools are covered?

Python NumPy Pandas Scikit-learn TensorFlow PyTorch OpenAI API Google Gemini Hugging Face LangChain FastAPI Power BI Docker ChromaDB Pinecone Git & GitHub

10 What career opportunities are available after completing this course?

Graduates can pursue roles such as: Data Scientist AI Engineer Machine Learning Engineer Deep Learning Engineer Generative AI Developer Data Analyst Business Intelligence Developer AI Application Developer NLP Engineer Computer Vision Engineer AI Solutions Architect Data Engineer MLOps Engineer AI Research Associate Prompt Engineer

Still have questions about this course?

Speak directly with our senior course advisors to customize your learning path.

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