Data Science Course with Placement Support
Instructor-led cohorts • Hands-on projects • Interview prep
Program fee
₹55,000
₹65,000
Save ₹10,000
One-time payment
Limited-time discount: course fee ₹65,000 minus ₹10,000; you pay ₹55,000.
Payment options
- Flat ₹10,000 OFF — Pay ₹55,000 all-inclusive. No hidden charges.
- EMI options available
Why Learners Choose Our Data Science Course — Placement Support Included
Mentor-led learning, portfolio projects, and dedicated career support.
Top Skills You’ll Gain in Our Data Science Course
Python Programming for Data Science & AI Advanced SQL for Analytics & ETL Statistics, Probability & Hypothesis Testing Exploratory Data Analysis (EDA) with Pandas Machine Learning (Scikit-learn, Regression to XGBoost) Power BI & Excel for Business Dashboards Real-World Data Cleaning & Feature Engineering ML Model Deployment using FastAPI & Streamlit Git & GitHub for Version Control & Collaboration End-to-End Project Execution for Job Readiness Data Storytelling & Business Problem Solving Capstone Projects with Resume-Focused Outcomes Cloud Basics (AWS/GCP) for Model Hosting Interview Preparation & Resume Review Support
Python
Core Programming Language
Learn to analyze, manipulate, and visualize data using Python—a must-have skill in every data analyst’s toolkit.
Pandas
Data Analysis & Manipulation
Work with structured data effortlessly using Pandas for filtering, aggregation, time-series, and preprocessing.
NumPy
Numerical Computation Library
Speed up data operations with NumPy arrays, broadcasting, and mathematical functions used in analytics workflows.
SQL
Querying Databases
Master SQL to extract, join, and manipulate data from real-world databases like MySQL, PostgreSQL, and SQLite.
MS Excel
Spreadsheet-Based Analytics
Build dashboards, use pivot tables, apply formulas, and perform analysis using the most widely-used spreadsheet tool.
Tableau / Power BI
Data Visualization Tools
Create interactive dashboards and business visualizations to communicate insights effectively using Tableau or Power BI.
Scikit-learn
Machine Learning Library
Train ML models like linear regression, decision trees, and clustering with Scikit-learn’s easy-to-use API.
Matplotlib & Seaborn
Data Plotting Libraries
Visualize trends, distributions, and patterns using beautiful charts built with Matplotlib and Seaborn.
Google Sheets
Online Spreadsheet Collaboration
Use cloud-based spreadsheets for real-time data entry, analytics, and integrations with data pipelines.
Jupyter Notebooks
Interactive Python Coding
Document and run data workflows in real time with Jupyter—a standard environment for every data analyst.
Python
Core Programming Language
Learn to analyze, manipulate, and visualize data using Python—a must-have skill in every data analyst’s toolkit.
Pandas
Data Analysis & Manipulation
Work with structured data effortlessly using Pandas for filtering, aggregation, time-series, and preprocessing.
NumPy
Numerical Computation Library
Speed up data operations with NumPy arrays, broadcasting, and mathematical functions used in analytics workflows.
SQL
Querying Databases
Master SQL to extract, join, and manipulate data from real-world databases like MySQL, PostgreSQL, and SQLite.
MS Excel
Spreadsheet-Based Analytics
Build dashboards, use pivot tables, apply formulas, and perform analysis using the most widely-used spreadsheet tool.
Tableau / Power BI
Data Visualization Tools
Create interactive dashboards and business visualizations to communicate insights effectively using Tableau or Power BI.
Scikit-learn
Machine Learning Library
Train ML models like linear regression, decision trees, and clustering with Scikit-learn’s easy-to-use API.
Matplotlib & Seaborn
Data Plotting Libraries
Visualize trends, distributions, and patterns using beautiful charts built with Matplotlib and Seaborn.
Course Curriculum
Python Basics
Module 1: Python for Data Science
- Syntax and data structures
- Functions and modules
- Jupyter workflows
Module 2: NumPy and Pandas
- Arrays and broadcasting
- Data wrangling
- EDA with Pandas
Module 7: Time and Space Complexity
- Understanding Algorithm Efficiency
- Time Complexity
- Space Complexity
Python Advanced
Module 8: Statistics and EDA
- Probability and hypothesis testing
- Feature engineering
- Visualization with Matplotlib and Seaborn
Module 9: Core Machine Learning
- Regression to XGBoost
- Model evaluation
- Scikit-learn pipelines
Module 10: Deep learning and NLP
- Neural network foundations
- NLP essentials
- LLM and RAG foundations
Introduction to Excel
Module 11: Spreadsheets and BI
- MS Excel dashboards
- Power BI / Tableau
- SQL for analytics
Frequently asked questions
Why Learners Choose Our Data Science Course — Placement Support Included
Mentor-led learning, portfolio projects, and dedicated career support.
Ready to start?
Talk to an advisor about this program — 15 minutes, no sales pitch.