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Data Analytics Mentorship Program

Become a job-ready Data Analyst in 14 weeks plus gain real industry exposure with a 4-week internship. Master Data Analytics from scratch with Top Data Analysts from Microsoft, KPMG, Amazon, and Rapido.
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  • job-guarantee-icon
    1.5 Lakh+
    Aspirants Mentored
  • job-guarantee-icon
    350+
    Hiring
    Partners
  • job-guarantee-icon
    7+
    Industry
    Mentors
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AI-Infused Project-Driven Curriculum
AI-Infused Project-Driven Curriculum
Curriculum

AI-Infused Project-Driven Curriculum

Master how AI enhances data cleaning, visualization, and predictive modeling in modern analytics.

  • Industry projects on finance, e-commerce, martech
  • Strong portfolio of dashboards, reports, and models
  • Master AI tools that automate repetitive analysis tasks
Guided by Data Experts from Top Companies
Guided by Data Experts from Top Companies
Mentorship

Guided by Data Experts from Top Companies

Learn directly from data leaders from Google, Amazon, Microsoft, Rapido & KPMG.

  • Master real data workflows with insider insights
  • Learn applied analytics with hands-on problem-solving
  • Get guided feedback on every milestone and project
Learn & Build Together in Jam Sessions
Learn & Build Together in Jam Sessions
Learn By Doing

Learn & Build Together in Jam Sessions

Live interactive sessions where you analyze data, build dashboards, discuss, and extract insights together in real time.

  • Work in teams on real data analytics use cases
  • Present insights to an industry mentors
  • Build projects live with mentors in real time
Work as a Data Analytics Intern at WsCube Tech
Work as a Data Analytics Intern at WsCube Tech
Internship

Work as a Data Analytics Intern at WsCube Tech

Gain real industry exposure by working as a Data Analytics Intern with a 4-week online internship.

  • Solve business problems using real datasets
  • Apply tools & concepts in industry-driven scenarios
  • Build practical experience for your resume & portfolio
Placements Support for 1 Year
Placements Support for 1 Year
Placements

Placements Support for 1 Year

Get dedicated help into your hiring journey end-to-end with real recruiter expectations.

  • Guided preparation for every stage of placements
  • Learn how to crack analytics jobs & interviews
  • Referrals to 350+ partner companies
AI-Infused Project-Driven Curriculum

Success Stories of Our Alumni

Our alumni are now excelling in high-impact data roles across leading tech, consulting & product companies with career-defining salary jumps and global opportunities.

Under WsCube’s Mentorship
Transformed
Milestone 1 - Duration: 3 weeks

Kickstart your Data Analytics journey with Excel!  From pivot tables to essential functions and from charts to dashboards learn every essential to become a Data Analyst. Excel isn't just a tool, it's your new superpower!

Week 1

Introduction to Data Analytics & Excel - Ⅰ

  • Introduction to Data Analytics
  • Basic Features in Excel
  • Formatting in Excel
  • Dealing with Raw Data
  • Functions in Excel
  • AI Prompting for Excel formulas
  • AI-assisted data cleaning
Week 2

Deep Dive with Excel - ⅠⅠ

  • Data Connectors in Excel
  • Cleaning in Power Query Editor
  • Adding Conditional Columns using Power Query Editor
  • Data Modelling and its Importance
  • Cardinality and Filter Direction in Power Pivot
  • ChatGPT/Gemini → Generate Power
  • Query M scripts
Week 3

Master Advanced Excel - ⅠⅠⅠ

  • Pivot Tables in Excel
  • Charts in Excel
  • Slicers in Excel
  • Measures in Excel
  • Creating a Dashboard in Excel
  • AI Visual Recommendation
  • Dashboard Summary Insight
  • Narration with AI
  • Invideo/Descript using AI

Project:

Tata Power – EV Charging Network Expansion Analysis

As a Data Analyst at Tata Power, you have been tasked with using Excel to build a comprehensive EV Infrastructure Planning Dashboard. Analyze electric vehicle density, mobility patterns, charging demand, corridor coverage, installation costs, and revenue potential to identify underserved regions, estimate ROI per location, and recommend data-driven priorities for scalable charging network expansion.

Case Study

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Analysis of Myntra Apparel

You are working at Myntra, a leading online fashion retailer. The management has asked you to analyse a dataset of various apparel items to gain insights into pricing, discounts, ratings, and available sizes.

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Audible Data Cleaning

As a data cleaning analyst at Audible, you've been assigned the task of cleansing a dataset sourced from audible's app. Ensure meticulous attention to detail to guarantee the accuracy and reliability of our data for subsequent analyses.

Excel Interview Prep with Industry Expert

In this session, you'll master Excel for data analytics interviews. Learn insider tips on using Excel effectively, tackling real-world scenarios, and impressing interviewers with your data manipulation skills.

Milestone 2 - Duration: 3 weeks

Want to retrieve, clean, manipulate and analyse the data?? Do it efficiently by using SQL queries!! This milestone covers everything from basic queries to complex joins, empowering you to extract valuable insights from large datasets with ease.

Week 4

Welcome to MySQL

  • Introduction to MySQL
  • Basic MySQL Syntax
  • Clauses in MySQL
  • Operators in MySQL
  • Dealing with Null Values in MySQL
  • AI for SQL query generation
  • AI debugging SQL errors
  • AI auto-documentation of queries
Week 5

Advanced SQL Queries and Functions in MySQL

  • Functions in MySQL
  • Case Operator in MySQL
  • Group By in MySQL
  • Having Clause in MySQL
  • Joins in MySQL
  • Query Optimization using AI
Week 6

Advanced SQL Concepts and Techniques in MySQL

  • Subqueries in MySQL
  • Union, Intersect, Except in MySQL
  • Stored Procedures in MySQL
  • Common Table Expressions(CTE)
  • Window Functions in MySQL
  • Stored procedure templates using AI
  • Debug window functions with AI

Project:

Amazon - Sales Data Analysis Using SQL

As a Data Analyst at Amazon, you have been tasked with using SQL to analyze sales transactions, customer orders, product performance, regional trends, and revenue metrics. Perform complex queries, joins, aggregations, and subqueries to uncover sales patterns, identify top-performing products, evaluate customer behavior, and support data-driven business decisions.

Case Study

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Swiggy Analysis Using SQL

Swiggy seeks insights from its SQL dataset. Implement sophisticated SQL queries with intricate joins for in-depth analysis and strategic decision-making.

SQL Interview Prep with Industry Expert

SQL is the backbone of data analysis. Get ready to deep dive into complex queries, optimize your understanding of database management, and leave with pro tips to stand out in SQL-based interview questions.

Milestone 3 - Duration: 3 weeks

Transform raw data into powerful insights with Data Visualization! Learn to create interactive dashboards, compelling charts, and dynamic reports using tools like Power BI and Tableau. Master the art of storytelling with data and make informed decisions with ease!

Week 7

Data Visualisation with Power BI

  • Introduction to Power BI
  • Data Connectors
  • Power Query Editor and Tools
  • Append Queries and Merge Queries
  • Pivoting and Unpivoting of data
  • Exploring datasets with AI
Week 8

Advanced-Data Modeling and DAX in Power BI

  • Data Modelling and Cardinality
  • Cross Filter Direction
  • Measures vs Calculated Columns
  • Functions in DAX
  • Cumulative Sales and Moving
  • Average Using DAX
  • AI natural language to DAX
  • AI anomaly detection for trends
  • DAX optimization using AI
  • AI quick YoY, MoM, rolling avg
Week 9

Visualisations and Dashboard Creation in Power BI

  • ChatGPT for Measures
  • Column Charts and Slicers
  • Matrix vs Tables
  • Cards, KPI and Gauge Chart
  • Formatting a Dashboard
  • AI-generated DAX & explanations
  • Smart Narratives for auto-insights

Project:

Olympic Games - Athlete Performance & Medal Analysis

As a Data Analyst for the Olympic Games, you have been tasked with using Power BI to build a comprehensive Sports Performance Dashboard. Analyze athlete profiles, country-wise participation, medal distribution, event categories, and historical trends to identify top-performing nations, emerging sports, gender participation patterns, and factors influencing medal success for strategic sports development and funding decisions.

Case Study

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Financial Performance Analysis Using Power BI & DAX

As a Data Analyst, you have been tasked with using Power BI and DAX (Data Analysis Expressions) to build an interactive Financial Intelligence Dashboard. Develop complex measures including running totals, moving averages, Year-to-Date (YTD), Month-to-Date (MTD), Year-over-Year (YoY) growth, and variance analysis to monitor revenue and cash flow trends, enabling data-driven financial planning and strategic decision-making.

Data Storytelling Fest

Transform raw data into compelling stories using Power BI/Tableau and compete to present the best insights.

Milestone 4 - Duration: 5 weeks

Master Python for Data Analytics! From data manipulation with Pandas to visualization with Matplotlib & Seaborn, and numerical computing with NumPy, this milestone will equip you with essential coding skills to analyze, transform, and visualize data efficiently.

Week 10

Python Basics

  • Introduction to Python for Data Analytics
  • Datatypes and Variables
  • Operators in Python
  • Control Flow in Python
  • Data Structures in Python
  • AI regex for data cleaning
  • AI variations & debugging
Week 11

Python Advance

  • Functions in Python
  • In-built Modules
  • Pickle Library
  • Introduction to Numpy
  • Statistical Functions in Arrays
  • AI-assisted file handling automation
  • AI real-world dataset examples
Week 12

Python Libraries - Pandas, Matplotlib and Seaborn

  • Introduction to Pandas
  • Cleaning Data with Pandas
  • Merge, concatenate and join Pandas
  • Introduction to Matplotlib
  • Charts in Matplotlib
  • AI imputation strategies
Week 13

Python Libraries - Webscraping and Text Analysis

  • What is WebScraping
  • BeautifulSoup and Requests
  • Library in Python
  • Extracting Data from Tables
  • Extracting Data from Multi-Page Websites
  • Text Analysis using Python
  • AI-assisted debugging for parsing errors
  • AI comparison with pre-trained models
Week 14

AI Automation and Workflow

  • How LLMs Actually Work
  • The Art of Prompt Engineering
  • RAGs, Fine Tuning & Model Optimization
  • AI-Powered Workflow Automation
  • Set up smart checks and alerts
  • Generate insights with AI-driven flows

Project:

Apollo - Appointment No-Show & Patient Engagement Analysis

As a Data Analyst at Apollo, you have been tasked with using Python to do a comprehensive Healthcare Utilization Analysis. Analyze patient booking patterns, no-show rates, time-slot performance, reminder effectiveness, consultation pricing, and visit history to identify key predictors of missed appointments, evaluate intervention strategies, and improve doctor utilization, patient outcomes, and platform trust.

Unilever Multi-Layer Workflow Automation

You are a data analyst at Unilever tasked with developing a multi-layer workflow automation system. The goal is to create a simple yet efficient automated pipeline that handles raw data, performs basic preprocessing, generates insightful visual dashboards, and shares the final reports without any manual intervention.

Case Study

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Amazon Prime Video - Content Performance & Viewer Retention Analysis

As a Data Analyst at Amazon Prime Video, you have been tasked with using Python to analyze viewing completion rates, genre preferences, release timing, audience engagement, and marketing spend to identify success patterns, and support data-driven decisions for future content investments.

Python Hackathon

Compete to solve coding challenges in the shortest and most efficient way possible while learning best practices.

Milestone 5 - Duration: 4 weeks

A 4-week immersive internship where you work as a Data Analyst Intern at WsCube Tech on real business challenges. Gain hands-on experience in data analysis, visualization, and reporting across multiple departments. Experience the real workflows of modern data teams while contributing to decision-driving projects.

Week 15

Data Organization & Foundation

  • Work with real business data from day one
  • Organize and structure data for business use
  • Build solutions that improve team efficiency
  • Understand how data flows within an organization
Week 16

Data Discovery & Reporting

  • Extract meaningful information from company data sources
  • Identify trends, patterns, and inconsistencies
  • Perform structured analysis on business datasets
  • Prepare concise reports for team leads and stakeholders
Week 17

Visualization & Dashboarding

  • Build interactive dashboards for real business teams
  • Transform findings into clear visual outputs
  • Design for non-technical audiences
  • Ensure accuracy, clarity, and business relevance
Week 18

Insights & Stakeholder Presentation

  • Consolidate work from all previous weeks
  • Craft a data-driven business narrative
  • Present findings to WS Cube Tech stakeholders
  • Demonstrate analytical thinking and communication skills
Bonus

Learn the latest tools and trends shaping the future of data roles.

Maths & Applied Statistics

  • Introduction to Statistics
  • Descriptive Statistics
  • Hypothesis Testing
  • AB Testing
  • Fundamentals of Probability
  • AI sample test scenarios
  • AI-driven simulations for visualization

Machine Learning

  • What is ML?
  • Applications of Machine Learning
  • Linear Regression
  • Decision Trees
  • Random Forests and Ensemble Methods
  • AI auto-generated regression datasets
  • AI-assisted debugging & result interpretation

Microsoft Fabric

  • Unified analytics with Microsoft Fabric ecosystem.
  • Integrate Power BI, Lakehouse, and Data Factory seamlessly.
  • Master modern Fabric architecture and Dataflow Gen2.
  • Build and manage Lakehouse with Delta Tables.
  • Execute a real-world Fabric project end to end.
  • Migrate legacy dashboards to Fabric effortlessly.
  • Automate pipelines and data refresh workflows.
  • Enable real-time insights with Power BI + Fabric.

Database Design & Architecture (MySQL)

  • Introduction to Database Design
  • Understanding Data Models (Conceptual, Logical, Physical)
  • Entity-Relationship (ER) Diagrams Basics
  • Normalization & Denormalization Concepts
  • Primary Keys, Foreign Keys & Relationships
  • Designing a Simple Database Schema in MySQL

Google Analytics 4 (GA4) for Data Analysts

  • Introduction to Google Analytics 4
  • Setting Up GA4 Property and Data Streams
  • Understanding Events, Parameters, and User Data
  • Exploring Reports and Key Metrics (Engagement, Retention, Traffic)
  • Connecting GA4 with BigQuery and Power BI
  • Building Dashboards and Interpreting Insights

Last Mile 3-Stage Exclusive Preparation

Your final sprint to a high-performing marketing career.

Last Mile 3-Stage Exclusive Preparation

Your final sprint to a high-performing marketing career.

01

Gear Up

Build a strong online presence with to get noticed by recruiters.

02

Pitch Perfect

Present ideas, tell stories, and ace interviews.

03

Tech Skill Setup

Master the practical side of digital marketing hiring.

01

Gear Up

Build a strong online presence with to get noticed by recruiters.

Gear Up
Gear Up

Resume Building

Craft impactful, job-ready resumes.

Portfolio

Showcase your projects and data stories effectively.

GitHub

Present real work with structured repositories.

LinkedIn

Optimize your profile for recruiter visibility.

02

Pitch Perfect

Present ideas, tell stories, and ace interviews.

Pitch Perfect
Pitch Perfect

Storytelling

Present your data projects with clarity, context, and impact.

Recruiter Insights

Learn how to align your pitch with what top recruiters look for.

Interview Tactics

Build authentic and structured responses for behavioral rounds.

Communication Mastery

Develop speaking and body language skills for interviews.

03

Tech Skill Setup

Master the practical side of digital marketing hiring.

Tech Skill Setup
Tech Skill Setup

Technical Round Prep

Problem-solving with SQL, Python, and BI-based questions.

Assessments

Tackle assignments and case study–specific data problems.

Whiteboarding Challenges

Practice structured thinking and data storytelling on the spot.

Guesstimates Practice

Crack analytical estimation and business reasoning confidently.

01

Gear Up

Build a strong online presence with to get noticed by recruiters.

Gear Up
Gear Up

Resume Building

Craft impactful, job-ready resumes.

Portfolio

Showcase your projects and data stories effectively.

GitHub

Present real work with structured repositories.

LinkedIn

Optimize your profile for recruiter visibility.

02

Pitch Perfect

Present ideas, tell stories, and ace interviews.

Pitch Perfect
Pitch Perfect

Storytelling

Present your data projects with clarity, context, and impact.

Recruiter Insights

Learn how to align your pitch with what top recruiters look for.

Interview Tactics

Build authentic and structured responses for behavioral rounds.

Communication Mastery

Develop speaking and body language skills for interviews.

03

Tech Skill Setup

Master the practical side of digital marketing hiring.

Tech Skill Setup
Tech Skill Setup

Technical Round Prep

Problem-solving with SQL, Python, and BI-based questions.

Assessments

Tackle assignments and case study–specific data problems.

Whiteboarding Challenges

Practice structured thinking and data storytelling on the spot.

Guesstimates Practice

Crack analytical estimation and business reasoning confidently.

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Industry-Recognized Certificate

A badge trusted by top companies.

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Stand Out in the Job Market

Turn your profile into a recruiter magnet.

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Your Passport to Career Growth

Step into better roles and higher salaries.

certificat-icon

Industry-Recognized Certificate

A badge trusted by top companies.

certificat-icon

Stand Out in the Job Market

Turn your profile into a recruiter magnet.

certificat-icon

Your Passport to Career Growth

Step into better roles and higher salaries.

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Live Data Arenas

Case Studies + Assignments from Top Companies

Learn real industry use cases and instantly apply every concept with short, focused assignments inside the live class, guided step-by-step by expert mentors.

8+

Case Studies

12+

Assignments

Turn every concept into execution, just like in real data teams.

Hackathon event
Proof of Work

Build Your AI Portfolio - Guided Milestone Projects

Every milestone ends with a complete, portfolio-ready Data Science or AI project that proves your practical expertise.

4+

Portfolio Projects

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Public Portfolio

You won’t need to say you’re a Data Analyst, your WORK will prove it.

Portfolio creation session
Data + AI Stack

Train on the Exact Tools Used by Top Data & AI Teams

Get hands-on with tools used for data cleaning, analysis, modeling, pipelines, deployment, and LLM workflows used by Data Scientists and ML Engineers to build real systems.

40+

Data & AI Tools

100%

Job-Relevant Stack

Hands-on training on tools used by McDonald's, KFC, PayPal & more.

Students using real tools
Project-Based Learning

Showcase Mega Capstone Project on Demo Day

Build a full-scale Data Analytics with GenAI system and present it live in an online Demo Day to mentors & peers.

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Because the best Data Analysts are made by doing, not just learning.

Group discussion with mentors
Doubt Solving & Community Support

Learn with Discord Community & Mentor Network

Never get stuck, connect instantly with mentors and like-minded Data Analytics learners. Build accountability circles, share project feedback, work together, and grow as a team.

1.5 Lakh+

WsCube Learners Community

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Live Mentor Access

You’re never learning alone; you’re growing in a tribe.

Mock interview happening
Mock Interviews

Perfect Your Skills with 1:1 Mock Interviews

Face 1:1 mock interviews, problem-solving rounds, and project simulations designed exactly like real hiring at top tech, fintech, and data companies. Get actionable feedback from experts who’ve actually hired Data Analysts.

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HR Round

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Strategy + Campaign-Based Round

Walk into interviews with clarity, strategy, and confidence.

Upskilled students with certificates
Graduation Ceremony

Grand Celebration of Your Journey & Certification

Graduate with pride in an virtual ceremony, present your campaigns, receive your certification, and network with recruiters and mentors.

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Top Performer Showcase

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WsCube Tech Certification

You don’t just complete the program; you get celebrated and noticed.

Upskilled students with certificates
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    Total Program Fee:

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    35,000/-

    Flat ₹18,400 OFF
    • Live instruction from Industry Veterans
    • Vibrant community just like a College Campus
    • Hand-on curriculum with Real-Life Projects

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WsCube Tech Alumni Stories, You can't afford to miss.

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Data Analyst | Skilled in Excel, Power BI, SQL & Python | Passionate About Business & Market Analytics | #OpenToWork

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MD SALMAN AHMAD

B.Tech (CSE) | Data Analyst (Microsoft Excel, SQL, Python, Power BI)

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Yes, freshers can certainly learn data analytics. It is a field that is constantly evolving, and it is not uncommon for individuals to enter the field without any prior experience or knowledge. In fact, our online data analytics courses in India are well-suited for beginners. We cover everything from the basics of data analytics.
No, our course is designed to be accessible to learners of all levels, and no prior knowledge or experience is required.
Yes, you will receive data analytics certification after successfully finishing the training.
Yes, data analytics is a great career choice for those interested in data, statistics, and technology. Data analysts are in high demand across a variety of industries, as businesses and organisations increasingly rely on data to drive decision-making and improve performance. Data analytics offers a promising career path with opportunities for growth, career advancement, and high earning potential.
Yes, data analysts are in high demand in today's digital economy. With the explosion of data and the increasing need for businesses to use data to drive decision-making, data analysts play a critical role in helping organisations gain insights and stay competitive. As a result, there is a significant demand for skilled data analysts across a variety of industries, including healthcare, finance, e-commerce, and technology, to name a few.

There are a wide range of career opportunities after the course on data analytics, including:

  • Data Analyst
  • Business Analyst
  • Data Scientist
  • Data Engineer
  • Business Intelligence Analyst
  • Market Research Analyst
  • Quantitative Analyst
  • Database Administrator
  • Data and Analytics Manager
  • Big Data Analyst
  • Predictive Modeller
  • Financial Analyst
  • Fraud Analyst
  • Healthcare Data Analyst
  • Marketing Analyst
  • Customer Insights Analyst
  • Risk Analyst
  •  

These are just a few examples of the many career paths available in data analytics. With the right skills and knowledge, there are plenty of opportunities to build a successful and rewarding career in this field.

The average data analyst salary in India is around INR 6,00,000 to INR 8,00,000 per annum. However, this can vary based on location, company size, industry, skills, education, and job responsibilities.

 

In the United States, the average salary for a data analyst is around $62,453 to $96,000 per year. In the United Kingdom, the average salary for a data analyst is around £28,000 to £50,000 per year.

Yes. It is an online data analyst course with placement. We help our learners to find suitable employment opportunities.

A data analyst is a professional who analyses and interprets large volumes of data to identify patterns, trends, and insights that can be used to inform business decisions, improve performance, and drive growth.

Some common tasks of a data analyst include:

  • Collecting and processing data from various sources
  • Cleaning and preparing data for analysis
  • Analysing data using statistical and analytical tools like SQL, Python, Power BI, Excel, etc.
  • Creating visualisations, charts, and reports to communicate findings
  • Identifying patterns, trends, and insights in the data to inform business decisions
  • Making data-driven recommendations for improvements or optimisations
  • Developing and maintaining databases and data systems
  • Collaborating with other teams and stakeholders to drive business outcomes

Data analytics can be a valuable skill set for a wide range of professionals, including:

  • learners
    learners who are interested in a career in data analytics.
  • Business professionals
    Executives, managers, and other business professionals who need to make data-driven decisions.
  • IT professionals
    Developers, database administrators, and other IT professionals who need to work with data.
  • Marketing professionals
    Marketing analysts, digital marketers, and other marketing professionals who need to measure the effectiveness of their campaigns.
  • Financial professionals
    Financial analysts, accountants, and other financial professionals who need to analyse financial data.
  • Engineers
    Engineers who work with sensor data, machine data, or other types of data.
  • Anyone who is interested in working with data
    Anyone interested in data and who wants to learn how to analyse it can benefit from learning data analytics.

Many companies across a wide range of industries are hiring for data analyst roles. Some of the top companies include:

  • Amazon
  • Microsoft
  • Facebook
  • Google
  • Apple
  • IBM
  • Accenture
  • Deloitte
  • KPMG
  • McKinsey & Company

In addition to these large tech and consulting firms, many smaller companies and startups are also hiring data analysts as they recognise the value of data-driven decision-making.

Industries such as finance, healthcare, retail, and manufacturing are all using data analytics to improve their operations and products, and as a result, they are hiring for data analyst roles.

There are also many online job boards and staffing agencies that specialise in placing data analysts in various industries and job functions. So if you are interested in this career, there are many opportunities available across a wide range of industries and company sizes. Join our best online data analytics course in India now to get started!

The data analyst course is a training program designed to equip learners with the essential skills and knowledge needed to analyse and interpret data in the digital economy.
This online data analyst course will equip you with the necessary skills and knowledge needed to succeed in the industry, making you an attractive candidate to potential employers.
Our course is taught by industry experts with extensive experience in the data analysis field.
The course includes hands-on 20+ projects that will allow you to apply the skills and knowledge you've learned in a practical setting.
The course duration is 2 months.
There are no prerequisites or fixed requirements for this training. Anyone interested in learning data analytics can join our course.
Yes, our course is available to learners all over the country, as long as they have access to a stable internet connection.
You can enrol in our online data analyst course by booking the demo class. Our team will be in touch with you for further assistance.

The subjects covered in our data analytics course in India include:

  • Python Programming
  • Data science libraries
  • Data analysis
  • Data visualisation
  • Microsoft Power BI
  • Data modelling
  • AI visuals
  • SQL (basic to advanced)
  • Advanced MS Excel

Power BI is a powerful business intelligence and data visualisation tool developed by Microsoft. It allows users to connect to a wide range of data sources, transform and model the data, and create interactive reports, dashboards, and visualisations.

With Power BI, users can easily analyse and understand data to gain insights and make informed decisions. It is widely used by businesses, data analysts, and data scientists to collect, analyse, and present data in an effective and visually appealing way. Power BI also provides a variety of features for collaboration, sharing, and data security.

SQL (Structured Query Language) is a fundamental tool in data analytics. It is a programming language that is used to communicate with relational databases, such as MySQL, Oracle, and SQL Server. SQL is used to extract, manipulate, and analyse data stored in databases.

In data analytics, SQL is used to perform various tasks, including:

  • Data Retrieval
  • Data Transformation
  • Data Analysis
  • Data Management
Data visualisation is the graphical representation of data and information in a way that is easy to understand and interpret. It is the process of turning data into visual elements such as charts, graphs, maps, and other visual representations that allow viewers to quickly and easily comprehend complex information. The primary goal of data visualisation is to communicate information clearly and effectively, so that viewers can gain insights and make informed decisions. It helps to reveal patterns, trends, and relationships in data that might not be immediately obvious in text or table format.