Our Data Analytics with Python program is designed as per current industry requirements, ensuring you learn the most in-demand analytical and programming skills used by real-world data professionals.
You don’t just learn theory — you work on live projects, real datasets, and business case studies using Python, so you gain complete job-ready practical experience.
Learn directly from experienced data analytics professionals who bring real corporate projects and industry knowledge into the classroom.
1) This program is built to make you job-ready, focusing on:
A. Interview preparation
b. Resume building
c. Practical projects
d. Real-world problem solving
e. Dedicated placement assistance
f. Career mentoring
The Data Science Mastery Program is designed to help learners build strong, industry-ready skills in data analysis, programming, and machine learning. This course blends theory with practical, hands-on projects using real-world datasets so you can confidently apply data-driven techniques in business, technology, finance, and other domains. Whether you are a beginner or transitioning from a different field, this program guides you step-by-step from basic concepts to advanced data science techniques used by top companies worldwide.
Advanced formulas: VLOOKUP, XLOOKUP, INDEX-MATCH
Data cleaning & transformation techniques
PivotTables, PivotCharts & slicers
Conditional formatting for data visualization
Data validation & structured referencing
Advanced charting and dashboards
Excel functions for analytics (TEXT, DATE, LOGICAL, IFs, SUMIFS, COUNTIFS, etc.)
Working with Power Query
Automating tasks with Macros (basic)
Practical business case studies
Introduction to relational databases
Writing SQL queries from basic to advanced
Filtering, sorting, grouping & aggregations
Joins (Inner, Left, Right, Full)
Subqueries & CTEs
Views, stored procedures & functions
Data manipulation (INSERT, UPDATE, DELETE)
Database design & normalization
Real-world SQL problem-solving exercises
Getting started with Power BI interface
Importing, cleaning & transforming data
Data modeling using relationships
DAX functions (basic to intermediate)
Building interactive dashboards & reports
Introducing Power Query tools
Publishing reports to Power BI Service
Sharing dashboards & real-time collaboration
Real business reporting use cases
Understanding Tableau workspace
Connecting to data sources
Dimensions, measures & data types
Building charts: bar, line, pie, maps, scatter, heat maps, etc.
Dashboard & story creation
Filters, actions & parameters
Data blending vs data joins
Publishing dashboards to Tableau Public/Server
Industry-based dashboard projects
Python basics & programming concepts
Working with variables, loops, functions & libraries
NumPy for numerical computing
Pandas for data wrangling & analysis
Matplotlib & Seaborn for data visualization
Exploratory data analysis (EDA) techniques
Reading/writing CSV, Excel & JSON files
Handling missing, inconsistent & unstructured data
Mini projects & practice problems














According to the Fortune Business Insights report, the global data analytics market was valued at USD 64.99 billion in 2024, and is projected to grow to USD 402.70 billion by 2032 — a compound annual growth rate (CAGR) of about 25.5%
As per the U.S. Bureau of Labor Statistics (BLS), employment of “data scientists” — a role heavily overlapping with data analytics — is projected to grow 34% from 2024 to 2034, which is much faster than the average for all occupations.
New job opportunities expected in Data Science & Analytics worldwide
Consistent year-on-year job growth projected for the next decade
Average annual salary range for skilled data science professionals in India






Data Analytics is the process of collecting, cleaning, and analyzing data to make better business decisions. It helps companies improve performance, reduce costs, and increase profits.
No. You can learn Data Analytics even if you come from a non-IT background like mar-keting, sales, finance, or operations. Basic computer knowledge is enough to get started.
Key skills include Excel, SQL, Python, Data Visualization (Power BI/Tableau), and basic statistics, along with problem-solving and analytical thinking.
You can apply for roles such as:
Freshers can earn ₹4–8 LPA, while experienced professionals can earn ₹10–25 LPA or more, depending on skills and company.
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