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Industry-Driven Program with Placement Assistance Data Science Course

Data science drives decision-making in every serious organization today. Companies do not operate on assumptions anymore. They operate on data. This Data Science Course is built to transform you into a job-ready data professional with structured technical depth, real project exposure, and placement assurance backed by 26+ years of training legacy. This is an execution-focused industry training program.

Join 10,000+ professionals who transformed their careers through Envision job-oriented Data Science Course. Learn from expert trainers with real-time projects and guaranteed placement support.

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Duration

9 - 12 Months

Mode

Classroom & Online

Placement

After Completion

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Talk to ECTI’s expert team teaching since 1997 and get your doubts cleared.

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Students Taught

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Our Students Works In

Why This Data Science Course Leads the Industry

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1. 26+ Years of Legacy

Established in 1997, we have trained thousands of students who now work across IT, analytics, and engineering domains. The methodology is refined, structured, and proven.

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2. Structured Framework

Every module is designed in progression:

Fundamentals → Tools → Modeling → Deployment → Capstone → Interview

No random topics. No scattered teaching.

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3. Placement Guarantee

You are guided until placement through:

Resume engineering
Technical mock interviews
HR round simulations
Portfolio building
Hiring pipeline integration

What Is Data Science?

Data science combines Statistics, Programming, Machine Learning, and Business Intelligence.

Organizations use data science to:

Predict behavior Detect fraud Optimize operations Forecast sales Automate decisions

Every product company, fintech firm, healthcare organization, and logistics platform relies on data science. Learning data science means positioning yourself in one of the most stable and scalable career domains.

What You Will Learn

You will not just “learn tools.” You will learn how to solve business problems using data.

Data cleaning and feature engineering
SQL-based data extraction
Statistical analysis
Python-based modeling
Machine learning model building
Dashboard and visualization design
Performance evaluation and optimization
Real-world deployment thinking

By the end of the program, you will understand how data flows from raw format to business decision.

Tools & Technologies You Will Master

Python

SQL Database

Microsoft Excel

Power BI

Tableau

NumPy

Pandas

Machine Learning

Real-World Skills You Will Master

Clean and structure raw datasets

Write optimized SQL queries

Perform statistical hypothesis testing

Build regression and classification models

Create interactive dashboards

Interpret model performance metrics

Present insights to business stakeholders

Solve domain-based analytics problems

These are job skills, not academic concepts.

Comprehensive Data Science Course Syllabus

Industry-Aligned Curriculum for Data Science Course

Explore each topic in-depth through interactive live classroom sessions, real-world use cases, and tool-based learning. You’ll not only understand the theory but also build practical skills that matter in actual roles.

Fundamentals of Analytics

Understanding the fundamentals of analytics is crucial for building a strong foundation in Data Science. This module introduces the core concepts of Data Science and Analytics, emphasizing its applications in various industries. Students will learn descriptive and inferential statistics, data structures, and feature engineering techniques essential for real-world data handling.

Introduction to Data Science and its applications
Importance of data-driven decision-making
Descriptive & inferential statistics
Data wrangling and feature engineering

Excel for Data Analytics

Excel is a powerful tool for data analytics, widely used in business intelligence and decision-making. This module covers advanced Excel functions, data cleaning, and visualization techniques, helping students master Pivot Tables, Power Query, and dashboards for analytical reporting.

Advanced formulas & functions
Data cleaning & visualization
Pivot Tables, Power Query & Dashboard creation

SQL for Data Science

SQL is a fundamental skill for data analysts and data scientists. This module teaches students how to interact with relational databases, perform complex queries, joins, and optimizations, and retrieve meaningful insights from large datasets.

SQL queries, joins & database management
Data retrieval & optimization
Hands-on project using SQL for Data Analysis

Python for Data Science

Python is one of the most widely used programming languages in Data Science. This module focuses on Python fundamentals, data manipulation, and visualization techniques using popular libraries like NumPy, Pandas, and Matplotlib.

Python fundamentals & libraries (NumPy, Pandas, Matplotlib)
Data manipulation & visualization
Exploratory Data Analysis (EDA)

Machine Learning & AI

Machine Learning is at the core of Data Science, enabling predictive analytics and AI applications. This module covers Supervised and Unsupervised Learning, regression, classification, and model evaluation, helping students build real-world machine learning models.

Supervised & Unsupervised Learning
Regression & Classification models
Model evaluation & hyperparameter tuning
Real-world Data Science Capstone Project

Outcome from Syllabus

Complete Industry Curriculum that builds depth.

Module 1 Fundamentals

Fundamentals of Analytics

Introduction to Data Science
Importance of data-driven decision making
Descriptive & Inferential statistics
Data wrangling & Feature engineering

You learn how to interpret data before modeling it.

Module 2 Excel

Excel for Data Analytics

Advanced formulas & functions
Data cleaning & Pivot tables
Power Query
Dashboard creation

You will build real analytical reports used in industry settings.

Module 3 SQL

SQL for Data Science

SQL queries
Joins & aggregations
Database optimization
Hands-on SQL data project

You will extract insights directly from structured databases.

Module 4 Python

Python for Data Science

Python fundamentals
NumPy & Pandas
Matplotlib & Visualization
Exploratory Data Analysis (EDA)

You will manipulate, transform, and analyze large datasets.

Module 5 ML & AI

Machine Learning & AI

Supervised & Unsupervised learning
Regression & Classification models
Model evaluation metrics
Hyperparameter tuning

You will build real predictive models.

Module 6 Capstone

Real-World Capstone Project

Problem definition & Data cleaning
Feature engineering & Model building
Evaluation & Business presentation

This project becomes your portfolio asset.

Building Your Technical Portfolio

In this course, we don't just teach code; we teach you how to build products. You will work on applications that simulate real-world business challenges—from inventory management to secure payment processing gateways. By the end, you will have a GitHub portfolio that proves your ability to write production-ready code.