Data Analytics Course in Delhi
Master data analysis, visualization, and reporting with hands-on training and real-world projects using industry tools. Use AI-powered techniques to gain insights and make smarter, data-driven business decisions.
About Data Analytics Course
This Data Analytics course is designed to help students and professionals learn to analyze data and extract meaningful insights to support business decisions. The training focuses on practical skills using industry-relevant tools and real-world datasets, not just theoretical concepts.
What Skills You Will Gain From This Course?
Excel
Python
Power BI
SQL
Numpy
Pandas
Scipy
Course Duration & Mode
Duration
3 months
Mode
Offline & Online
Batch
Weekday & Weekend
Practical Sessions Included
Data Analytics Course Curriculum
- Introduction to Excel
Excel Workbook and Worksheet, Working with Multiple Worksheets, Grouping and Consolidating Worksheets, Sharing and Protecting Worksheets - Cells and Formatting
Cell Basics, Cell Formats, Custom Formats, Paste Special, Wrap Text, Merge Cells, Decimal Places, Hyperlinks, Check Marks - Data Handling in Excel
Skip Blanks, Transpose Data, Cell References, Relative, Absolute, Mixed, 3D and External References - Formulas and Functions
Formulas in Excel, Arithmetic, Logical, Date and Time, Text, Financial, Statistical and Lookup Functions, Formula Auditing - Text Functions
Left, Right, Mid, Concatenate, ‘&’ Operator, Find and Search, Len Function, Trim, Substitute, Clean, Exact, Replace, Lower, Upper, Proper - Conditional and Logical Functions
IF Function, Multiple IF, IF with AND, OR, NOT, IFs Function, Conditional Formatting - Lookup Functions
VLookup, HLookup, MATCH and INDEX, CHOOSE, Left Lookup, Reverse Lookup, Double Lookup, Exact and Approximate Match - Date and Time Functions
Today and Current Time, Date and Time Functions, Datedif, Age Calculation, Time Sheets, Network Days, Weekday, Weeknum, Reports - Mathematical and Statistical Functions
Arithmetic Operations, Conditional Calculations, Round, Floor, Ceiling, Square Root, Factorial, INT, ABS, Count Functions, SumIF, AverageIF - Financial Functions
PMT Function, Interest Rate Calculation, Present and Future Value, Investment and Annuity Calculations - Data Analysis
Sorting, Filtering, Conditional Formatting, Data Validation, Data Lists, Dependent Lists, Data Tables, Scenarios, Goal Seek - Named Ranges
Named Ranges, Dynamic Named Ranges, Custom Names - Data Visualization
Pivot Tables, Pivot Charts, Charts, Sorting in Charts, Chart Design, Titles and Axis Formatting - Advanced Excel Tools
Templates, User Forms, Error Messages, Object Linking, Drawing Objects - Error Handling
Excel Errors, IFERROR, ISERROR, Aggregate Function, Circular References, Formula Auditing
- Introduction to Python
Python First Step, Installing Python, Working in Python, Using Python as a Calculator, First Python Program - Variables and Data Types
Variables, Variable Assignment, Naming Rules, Numeric, Boolean, String, Sequence, Set, Mapping Data Types - Operators and Input/Output
Types of Operators, Keyboard Input, Integer and Float Input, Print Statements, sep and end in Print - Decision Making
If Statements, Indentation, Colon Usage, If-Else, If-elif-else, Nested If, AND Operator - Loops in Python
While Loop, While with Else, If-Else in While, For Loop, For with List, Range Function, Break, Continue, Pass - Lists in Python
Creating Lists, Accessing Elements, Slicing, Modifying Lists, Deleting Elements - Tuples in Python
Creating Tuples, Single Element Tuple, Accessing Elements, Slicing, Looping, Updating and Deleting, Functions - Dictionaries in Python
Creating Dictionary, Accessing Elements, Looping, Updating, Deleting Items - Sets in Python
Creating Sets, Accessing Items, Adding and Deleting Elements, Set Operations - Strings in Python
Creating Strings, Accessing and Slicing, String Operations, Format Method, Important Methods - Functions in Python
Types of Functions, Creating and Calling Functions, Arguments and Return, Recursive Functions - Modules and Packages
Modules, Types of Modules, Built-in and User-defined Modules, Importing and Aliasing, Packages - Exception Handling
Handling Exceptions, Multiple except, finally Block, Raising Exceptions, else Clause - File Handling
File Basics, Create, Open and Close Files, Read and Write Files, Append Data, File Modes, Using ‘with’ - Errors and Exceptions
Syntax Errors, Handling Exceptions, Raising Exceptions, User-defined Exceptions - Object-Oriented Programming
Classes, Class Syntax, Objects, Inheritance, Multiple Classes, Method Overriding, super() Function, Constructors - Polymorphism
Function Polymorphism, Class Polymorphism, Polymorphism with Inheritance - Database Connection
Database Basics, MySQL Connection, Software Requirements, Creating Database from Python
- Introduction to Power BI
Welcome to the Course, Course Overview, Class Resources, Power BI Basics - Power BI Setup and Tools
Power BI Desktop, Power BI Services, Power BI Pro License, Power Query Editor - Power Query Editor
Data Profiling Tools, Group By, Applied Steps, Appending vs Merging - Visuals in Power BI
Different Visuals, Charts, Types of Charts in Power BI - DAX (Data Analysis Expressions)
Introduction to DAX, Implicit Measures, DAX Formulas, Basic Functions, Date and Calendar Functions - Advanced DAX Concepts
Row vs Filter Context, IF ELSE Function, Time Intelligence Functions, X vs Non-X Functions - Tool Tips and Drill Throughs
Creating Tool Tips, Drill Through Features - Power BI Relationships
Data Relationships, Managing Relations in Power BI - KPI and Data Insights
Introduction to KPIs, Creating KPIs in Power BI - Administration in Power BI
Admin Roles, Member, Contributor, Viewer Roles - Security in Power BI
Importance of Security, Row Level Security (RLS) - Formatting and Best Practices
Formatting Options, Best Practices in Power BI - Exploratory Data Analysis (EDA)
Understanding EDA, Data Exploration Techniques - Live Project Implementation
Real-world Project Implementation in Power BI - Bonus Content
Power BI Interview Questions and Answers, Advanced Relationship Concepts
- Introduction to SQL
SQL Fundamentals, Need of SQL, Database Activities, Building Blocks and Standards - Data Types and Table Management
Data Types, Operators, Expressions, Creating Tables, ALTER TABLE, Adding Columns, DROP TABLE - Data Integrity and Constraints
Data Protection, Primary Key, Foreign Key, Check Constraints - Indexes and Performance
Creating Indexes, Guidelines for Index Creation, Performance Optimization - Data Manipulation
INSERT, UPDATE, DELETE Operations - Transaction Control
COMMIT, ROLLBACK, BEGIN TRANSACTION - SELECT Statement
Retrieving Data, Selecting Columns, ORDER BY, Working with NULL Values - Joins and Multiple Tables
INNER JOIN, OUTER JOIN, CROSS JOIN - Filtering Data
WHERE Clause, Equality Conditions, Wildcards, Handling NULL Values - Set Operations
UNION, INTERSECT, EXCEPT - SQL Functions
SUM, AVG, COUNT, MAX, MIN, GROUP BY, HAVING - Subqueries
Nested Queries, Subqueries in Conditions, Expressions, Column Lists - Advanced SQL Concepts
Complex Expressions, Query Optimization
- Introduction to NumPy
What are NumPy Arrays, Anatomy of NumPy Arrays, NumPy Arrays vs Python Lists, NumPy Data Types - Creating NumPy Arrays
Creating NumPy 1D Arrays, Creating 2-dimensional NumPy Arrays, Alternative Array Creation Methods - Working with NumPy Arrays
Accessing Elements using Indexing, Array Slicing, Joining or Concatenating Arrays, Subsets of Arrays - Operations on Arrays
Arithmetic Operations on 2D Arrays - Applications of NumPy Arrays
Covariance, Correlation, Linear Regression
- Introduction to Pandas
Descriptive Statistics with Pandas - Statistical Functions
min() and max(), mode(), mean(), median(), count(), sum(), quantile(), var() - DataFrame Operations
Applying Functions on Subset of DataFrame, Advanced Operations, Pivoting, Sorting, Aggregation - Data Visualization
Creating Histogram - Function Application
pipe() Function, apply() and applymap() Functions - Grouping and Transformation
groupby() Function, transform() Function - Data Handling
Reindexing and Altering Labels
- Introduction to SciPy
What is SciPy, Why Use SciPy, Language Used in SciPy, SciPy Codebase - Constants in SciPy
Constant Units, Unit Categories - SciPy Optimizers
Optimizing Functions, Roots of an Equation, Minimizing Functions, Finding Minima - SciPy Sparse Data
What is Sparse Data, Working with Sparse Data, CSR Matrix, Sparse Matrix Methods - SciPy Graphs
Adjacency Matrix, Connected Components, Dijkstra, Floyd Warshall, Bellman Ford, Depth First Order, Breadth First Order - SciPy Spatial Data
Triangulation, Convex Hull, KDTrees, Distance Matrix, Euclidean Distance, Cosine Distance, Hamming Distance - SciPy Matlab Arrays
Exporting Data in Matlab Format, Importing Data from Matlab Format - SciPy Interpolation
Spline Interpolation, Radial Basis Function Interpolation
Project Based Practical Training
At VSIT, students gain hands-on experience by working on real-world Data Analytics projects. Our practical training in Delhi helps learners analyze data, generate insights, and become job-ready for analytics and business intelligence roles.
- Data Cleaning & Preparation – Learn how to organize, clean, and transform raw data for analysis.
- Data Visualization Skills – Develop dashboards and reports to present insights clearly and effectively.
- Problem Solving Approach – Analyze data to identify trends, patterns, and business solutions.
- Tool-Based Learning – Gain hands-on experience with industry tools used in data analytics.
- Career Ready Training – Prepare confidently for roles in data analytics, business intelligence, and reporting in Delhi.
Why Learn Data Analytics?
Data Analytics is a powerful skill in today’s data-driven world, helping businesses make informed decisions and improve performance. At VSIT, students gain practical knowledge, work on real datasets, and develop job-ready skills required for successful careers in data analytics in Delhi and beyond.
- Growing Career Demand – Data analytics professionals are in high demand as companies rely on data to drive growth and efficiency.
- In-Demand Tools & Technologies – Learn tools like Excel, Python, SQL, and Power BI used widely in the analytics industry.
- Versatile Career Paths – Explore opportunities in domains like marketing analytics, financial analysis, and business intelligence.
- Hands-On Practical Learning – Work on real datasets to understand data cleaning, visualization, and interpretation techniques.
- Freelance & Remote Work Options – Get opportunities to work independently or remotely with global clients.
Who Should Join This Course?
This course is suitable for individuals aiming to build strong data analytics and reporting skills for professional growth.
What Are The Career Opportunities After Data Analytics Course?
After completing Data Analytics course, students gain skills in analyzing data, identifying trends, and making data-driven decisions, making them highly valuable in today’s digital economy. At VSIT, the focus on practical training and real-world projects helps learners become job-ready for various analytics roles in Delhi and across India.
Data Analyst
Business Analyst
Data Scientist
Data Engineer
Financial Analyst
Marketing Analyst
Why Choose VSIT?
Learn from experienced mentors who provide practical guidance and industry insights.
Get personalized attention and better understanding through small group training sessions.
Build real skills with hands-on training focused on industry requirements effectively.
Prepare confidently for interviews with guidance, practice, and expert tips
Learn at your own pace with classes available on weekdays and weekends.
Earn industry-recognized certification that validates your skills and enhances your resume.
Frequently Asked Questions
Students, graduates, working professionals, and beginners from any background can join.
You will learn Excel, SQL, Python, Power BI/Tableau, data visualization, and real-world analytics projects.
Basic coding like SQL and Python is taught from beginner level, so no prior coding experience is required.
The course duration typically ranges from 3 to 6 months depending on the program structure.
Yes, students receive an industry-recognized certification after successfully completing the course.