Logo
Students
100% Job Interview Guarantee

Data Analytics Course
Powered By Gen AI

Become a Job Ready Data Analyst within 6 Months with our Best Data Analytics Course. Master SQL, Python, Power BI, Excel, and reporting skills recruiters notice fast.

Our Programs are Backed by

NSDCMinistry of Skill Development and EntrepreneurshipSkill India
Student 1Student 2Student 3Student 4

4.9/5 by 2,000+ Students

Claim Your Free Roadmap

Talk to our career experts and get a personalized learning path to your dream job.

+91

Your privacy is our priority. No spam ever.

The NexaLearn Data Analytics Program That Helped

30k+ students

We don't just teach we help you get hired at top-tier product companies.

Samsung
Accenture
Deloitte
GitHub
TCS
American Express
Google
Siemens
Vercel
Amazon
ICICI Bank
Tech Mahindra
Infosys
Nvidia
Samsung
Accenture
Deloitte
GitHub
TCS
American Express
Google
Siemens
Vercel
Amazon
ICICI Bank
Tech Mahindra
Infosys
Nvidia
Microsoft
Flipkart
Myntra
Zepto
Cred
Blinkit
Zomato
Swiggy
EY
PwC
boAt
Microsoft
Flipkart
Myntra
Zepto
Cred
Blinkit
Zomato
Swiggy
EY
PwC
boAt

Curated Job Boards

500+ Active Openings

Skip random job hunting. Get direct access to 500+ active openings shared for learners.

Learn more

Average Hike

85%

Google

Data Analyst

Google • Bangalore

Estimated CTC

35 LPA
HOT

Build a Solid Portfolio

Show dashboards, reports, and project work that prove you can handle real tasks. We help to build a Standout Portfolio.

Average Hike

85%

Arjun Sharma

Arjun Sharma

Business Analyst

Optimized
Portfolio Live

Resume Score

92/100

Mock Interview Preparation

Get trained with interview-style questions and be more prepared under real pressure. Get one-on-one mentorship for interview preparation.

Average Hike

85%

Interview Rating

CommunicationEXCELLENT
Technical DepthSTRONG
Problem SolvingTOP 1%

Feedback from Senior Data Analyst at Meta

Meta

Become A Certified

Data Analyst

Become a certified data analyst with the best data analytics training courses at The NexaLearn. Complete the program, finish projects, and earn credentials you can proudly share during interviews.

12.6 LPA
HIGHEST SALARY
500 +
PARTNER COMPANIES
100%
JOB ASSISTANCE
5.7 LPA
AVERAGE SALARY
NexaLearn
Standard Courses
Industry Readiness

6–10 month job-focused curriculum.

Long programs with less practical exposure.

Personalised Placement Support

500+ hiring partners with placement support.

Limited support and generic job portals.

Classroom Learning

300+ hours of live online & offline sessions.

Mostly self-paced with fewer live classes.

Data Analytics Studio

Studio projects, hackathons, and masterclasses.

Limited real-world project exposure.

Personalised Mentorship

1:1 mentorship from industry experts.

Limited personalised career guidance.

Ready to redefine your future?

Ready to become Certified Analyst? Get a call with our expert counselor to get personalized guidance for your next career path.

Job-Guarantee Data Analytics Curriculum

This course follows a career-first structure and stands strong among data analytics courses in India.

Module 01

Business Analytics Foundations

Teach learners how data analytics is used to solve real business problems, not just how to operate tools.

Key Topics

What is data analytics?
Types of analytics

Descriptive analytics

Diagnostic analytics

Predictive analytics

Prescriptive analytics

Difference between data, metrics, KPIs, and insights
Business questions vs data questions
Understanding stakeholders and requirement gathering
Defining success metrics
Common business metrics

Revenue

Profit margin

Conversion rate

Retention rate

Churn rate

Customer lifetime value

Average order value

Return on ad spend

Basics of data storytelling and communicating insights to non-technical stakeholders
Practical Capstone Project

Business Problem Framing Project

Convert a vague problem such as “Sales are declining. Find out why.” into business questions, required data, KPIs, an analysis plan, and an expected dashboard/report structure.

Module 01

Business Analytics Foundations

Teach learners how data analytics is used to solve real business problems, not just how to operate tools.

Key Topics

What is data analytics?

Types of analytics

Descriptive analytics

Diagnostic analytics

Predictive analytics

Prescriptive analytics

Difference between data, metrics, KPIs, and insights

Business questions vs data questions

Understanding stakeholders and requirement gathering

Defining success metrics

Common business metrics

Revenue

Profit margin

Conversion rate

Retention rate

Churn rate

Customer lifetime value

Average order value

Return on ad spend

Basics of data storytelling and communicating insights to non-technical stakeholders

Practical Capstone Project

Business Problem Framing Project

Convert a vague problem such as “Sales are declining. Find out why.” into business questions, required data, KPIs, an analysis plan, and an expected dashboard/report structure.

Module 02

Modern Excel for Business Analytics

Teach Excel as a practical business analytics tool, including modern functions, Power Query, reporting, and dashboarding.

Key Topics

Excel basics

Interface, cell formatting, data types, sorting, filtering, data validation, named ranges, and conditional formatting

Modern Excel functions

SUM, COUNT, MIN, MAX, AVERAGE, COUNTA, COUNTBLANK

IF, AND, OR, NOT

SUMIF, SUMIFS, COUNTIF, COUNTIFS

XLOOKUP, INDEX, MATCH

FILTER, SORT, UNIQUE

LEFT, RIGHT, MID, FIND, LEN, TRIM, SUBSTITUTE, UPPER, LOWER, PROPER

TODAY, NOW, MONTH, YEAR, DAY, WEEKDAY, NETWORKDAYS, WEEKNUM

Data cleaning in Excel

Removing duplicates, handling blanks, standardizing text, splitting and combining columns, cleaning dates, and preparing sales/customer data

Pivot tables and reporting

Grouping, binning, calculated fields, slicers, timelines, summary reports, and cross-tab reports

Power Query

Importing from Excel/CSV/folders, removing and renaming columns, changing data types, merging, appending, and creating reusable cleaning workflows

Excel dashboards (Optional)

Dashboard design, KPI cards, trend charts, bar charts, waterfall charts, dynamic dashboards, and executive layouts

Practical Capstone Project

Retail Sales Excel Dashboard

Clean raw sales data and build a dashboard showing total sales, monthly trend, top products, top regions, profit margin, customer segments, and salesperson performance.

Module 03

SQL for Real-World Analytics

Teach SQL as the core skill for analysis, reporting, segmentation, cohorting, and business decision-making.

Key Topics

SQL foundations

Relational databases, tables, primary keys, foreign keys, data types, SELECT, WHERE, ORDER BY, GROUP BY, HAVING, DISTINCT, and NULL handling

Joins and data merging

INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL OUTER JOIN, UNION, UNION ALL, INTERSECT, and EXCEPT

Business SQL

CASE WHEN, date functions, text functions, conditional aggregations, deduplication, rollups, and revenue calculations

Intermediate SQL

Subqueries, CTEs, temporary tables, window functions, ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD, running totals, and moving averages

Advanced analytics SQL

Cohort analysis, funnel analysis, retention analysis, segmentation, churn-risk identification, RFM analysis, booking window analysis, attribution basics, data quality checks, and query optimization basics

Cloud SQL exposure (Optional)

Google BigQuery, Snowflake, Microsoft Fabric Warehouse, Amazon Redshift, or Databricks SQL

Practical Capstone Project

Customer Retention SQL Project

Calculate first purchase date, last purchase date, total orders, total revenue, average order value, repeat customer flag, churn-risk flag, monthly retention, and cohort performance.

Module 04

Data Modeling and Analytics Engineering (Optional)

Teach learners how trusted analytics datasets are designed before dashboards are built.

Key Topics

Data modeling basics

Transactional vs analytical data, OLTP vs OLAP, fact tables, dimension tables, star schema, snowflake schema, table grain, primary keys, and foreign keys

Analytics engineering workflow

Raw layer, staging layer, intermediate layer, mart layer, metric layer, documentation, testing, and data lineage

Practical data models

Customer dimension, product dimension, date dimension, sales fact table, marketing campaign fact table, web events fact table, and aggregated reporting tables

Data quality

Null checks, duplicate checks, referential integrity, freshness checks, volume checks, outlier checks, and metric reconciliation

Version control basics

Why Git matters, GitHub basics, project folder structure, SQL file organization, and README documentation

Practical Capstone Project

Build an Analytics Data Mart

Convert raw orders, customers, and products into staging tables, intermediate models, and business marts such as mart_customer_revenue and mart_monthly_sales.

Module 05

Power BI for Enterprise Analytics

Teach Power BI as an enterprise BI and decision-support platform, not just a desktop visualization tool.

Key Topics

Power BI foundations

Power BI Desktop, Power BI Service, import mode, DirectQuery, data view, model view, and report view

Power Query

Cleaning data, merging, appending, conditional columns, type changes, date transformations, text transformations, and parameterized queries

Data modeling in Power BI

Star schema, fact/dimension tables, relationships, cardinality, filter direction, date tables, role-playing dimensions, and measure tables

DAX

Calculated columns vs measures, SUM, COUNT, DISTINCTCOUNT, CALCULATE, FILTER, ALL, DIVIDE, time intelligence, YTD, MTD, QTD, rolling averages, ranking, contribution percentage, row context, and filter context

Dashboard and report design

KPI cards, trend charts, bar charts, matrix visuals, drill-through pages, tooltips, bookmarks, field parameters, slicers, filters, and executive summary pages

Enterprise Power BI

Publishing, workspaces, scheduled refresh, gateway basics, row-level security, app sharing, deployment pipelines, Performance Analyzer, and dataset optimization

AI-ready Power BI

Clean semantic model design, business-friendly field names, measure descriptions, and consistent metric definitions

Practical Capstone Project

Executive Sales Performance Dashboard

Build and publish a dashboard showing revenue, profit, monthly growth, region performance, product category performance, salesperson ranking, customer segments, and drill-through details.

Module 06

Tableau for Data Storytelling

Teach Tableau as a visual storytelling and exploratory dashboarding tool.

Key Topics

Tableau foundations

Interface, data connections, dimensions and measures, discrete vs continuous fields, marks card, shelves, filters, and parameters

Tableau calculations

Calculated fields, logical calculations, string calculations, date calculations, table calculations, percent of total, running total, rank, and Level of Detail expressions

Visual analytics

Bar charts, line charts, scatter plots, heatmaps, maps, dual-axis charts, combo charts, reference lines, trend lines, and forecasting basics

Dashboard design

Layouts, containers, actions, filters, parameters, story points, executive storytelling, and avoiding dashboard clutter

Practical Capstone Project

Customer Segmentation Dashboard

Build a dashboard showing customer segments, revenue by segment, retention by segment, region-wise distribution, high-value customers, and churn-risk customers.

Module 07

Python for Data Analytics

Teach Python as a practical tool for data cleaning, analysis, automation, and machine learning.

Key Topics

Python foundations

Installation, Jupyter Notebook, VS Code, variables, data types, strings, lists, tuples, dictionaries, sets, conditionals, loops, functions, lambda functions, comprehensions, error handling, files, modules, and packages

Python for data work

Virtual environments, package installation, project folder structure, reading CSV/Excel/JSON files, connecting to APIs, and writing reusable scripts

NumPy

Arrays, indexing, slicing, reshaping, combining arrays, math operations, and basic statistics

pandas

Series, DataFrames, reading data, inspecting data, filtering rows, selecting columns, renaming, dropping, missing values, duplicates, type conversion, dates, grouping, merging, appending, pivots, and derived columns

Exploratory data analysis

Summary statistics, frequency tables, univariate analysis, bivariate analysis, correlation, outliers, missing values, and business interpretation

Data visualization

Matplotlib, Seaborn, line charts, bar charts, histograms, box plots, scatter plots, heatmaps, regression plots, and geospatial basics with Folium

Python automation

Automating repeated reports, cleaning multiple files from a folder, exporting clean datasets, creating automated Excel outputs, and report automation concepts

Practical Capstone Project

Marketing Campaign Analysis with Python

Clean campaign data and calculate impressions, clicks, CTR, spend, CPC, conversions, CPA, revenue, ROAS, best-performing campaign, and worst-performing campaign.

Module 08

Statistics for Data Analysts

Teach statistical thinking required for reliable business decision-making.

Key Topics

Foundations

Population vs sample, mean, median, mode, variance, standard deviation, percentiles, distributions, skewness, and outliers

Probability basics

Probability concepts, conditional probability, expected value, normal distribution, and binomial distribution

Inferential statistics

Sampling, sampling bias, confidence intervals, hypothesis testing, p-values, statistical significance, and practical significance

Business testing

A/B testing, control vs treatment, conversion rate testing, t-test, chi-square test, ANOVA basics, sample size intuition, experiment design, and common testing mistakes

Regression interpretation

Simple linear regression, multiple linear regression, coefficients, R-squared, residuals, and correlation vs causation

Practical Capstone Project

A/B Testing Project

Analyze two versions of a landing page and decide which performed better, whether the difference is statistically meaningful, and whether the business should roll out the new version.

Module 09

Applied Machine Learning for Analysts (Data Science)

Teach machine learning as a practical business analytics skill, not as abstract theory.

Key Topics

ML foundations

Supervised learning, unsupervised learning, regression, classification, clustering, train/test split, features, and target variables

Regression models

Linear regression, decision tree regression, random forest regression, RMSE, MSE, MAE, and business interpretation of errors

Classification models

Logistic regression, decision tree classifier, random forest classifier, KNN, accuracy, precision, recall, F1-score, confusion matrix, and ROC-AUC basics

Model improvement

Feature engineering, categorical variables, scaling, cross-validation, grid search, overfitting, and underfitting

Unsupervised learning

K-means clustering, PCA, customer segmentation, and cluster interpretation

Deployment basics

Saving models with pickle, simple Streamlit apps, model documentation, and business recommendations from model outputs

Responsible ML

Bias in data, explainability, model limitations, human review, and monitoring model performance

Practical Capstone Project

Customer Churn Prediction

Build a model to predict customers likely to churn, compare models, evaluate performance, explain model limitations, and recommend business actions.

Module 10

Generative AI for Data Analytics

Teach learners how to use GenAI responsibly and practically in analytics workflows.

Key Topics

GenAI foundations

LLMs, GPT-style models, tokens, context windows, prompt engineering, system prompts, user prompts, few-shot prompting, hallucination risk, and bias risk

AI-assisted analytics

Using AI to understand business problems, generate SQL drafts, debug SQL, explain SQL, write Python, debug Python, summarize EDA, design dashboards, and generate stakeholder summaries

OpenAI API and LLM workflows

API basics, API keys conceptually, request/response structure, temperature, max tokens, cost awareness, prompt templates, and structured outputs

Embeddings and vector search

Embeddings, semantic search, FAISS, vector databases, similarity search, and analytics use cases

RAG for analytics

Retrieval-Augmented Generation, chunking, metadata, retrieval quality, grounded answers, source citations, RAG evaluation, and preventing unsupported answers

AI agents for analytics

Tool use, planning, SQL agents, dashboard assistants, documentation assistants, data quality assistants, risks of agentic workflows, and human-in-the-loop review

Responsible AI

Data privacy, sensitive data handling, hallucination checks, governance, explainability, and when not to use AI

Practical Capstone Project

AI Analytics Assistant

Build a simple assistant that answers questions from business documents, data dictionaries, dashboard documentation, and sample datasets while retrieving relevant context and refusing unsupported answers.

Module 11

Cloud Data Platforms and Modern Data Stack (Optional)

Expose learners to how analytics is delivered in modern companies using cloud platforms.

Key Topics

Modern platform concepts

Data warehouse, data lake, lakehouse, data mart, batch processing, streaming basics, ELT vs ETL, and bronze/silver/gold layers

Cloud warehouse exposure

Google BigQuery, Snowflake, Microsoft Fabric, Databricks, or Amazon Redshift

Data ingestion

Loading CSV files, Excel files, API data, scheduled refresh, and data pipeline basics

Data transformation

SQL transformations, Python transformations, Power Query transformations, and dbt-style transformation logic

Governance and cost awareness

Access control, data privacy, query cost, storage cost, refresh frequency, documentation, and lineage

Practical Capstone Project

Cloud Analytics Pipeline

Build a mini pipeline from raw CSV/API data to a cloud warehouse table, cleaned SQL model, business data mart, and Power BI dashboard.

Module 12

Business Domain Analytics

Teach learners how analytics changes across business functions and how metrics differ by domain.

Key Topics

Marketing analytics

Campaign performance, CTR, CPC, CPA, ROAS, funnel conversion, attribution basics, and lead scoring

Sales analytics

Revenue, pipeline analysis, win rate, sales cycle, salesperson performance, and forecasting basics

Customer analytics

Segmentation, RFM, customer lifetime value, churn, retention, and repeat purchase rate

Product analytics

DAU, MAU, activation, feature adoption, retention curves, funnel drop-off, and North Star metric

Finance analytics

Revenue, cost, gross margin, EBITDA basics, budget vs actual, and forecasting

Operations analytics

Turnaround time, SLA, defect rate, inventory, process bottlenecks, and productivity metrics

Practical Capstone Project

Business Function Analytics Case Study

Choose one domain, define the business problem, identify KPIs, clean data, analyze trends, build a dashboard, and present recommendations.

Module 13

Data Storytelling and Stakeholder Communication

Teach learners how to communicate insights clearly, professionally, and actionably.

Key Topics

Insight vs observation

Executive summary writing

Structuring analysis

Pyramid principle

Before/after comparison

Root cause explanation

Recommendation writing

Dashboard narration

Presenting uncertainty

Handling stakeholder questions

Making analysis actionable

Practical Capstone Project

Executive Insight Memo

Write a one-page memo explaining what happened, why it happened, why it matters, what the business should do next, and what the limitations are.

Module 14

Capstone Portfolio

Ensure every learner completes job-ready portfolio projects that demonstrate practical analytics ability.

Key Topics

Required portfolio projects

SQL business analysis

Power BI executive dashboard

Python EDA project

Statistics or A/B testing project

Machine learning project

GenAI analytics project

Final presentation

Problem statement, dataset used, methodology, tools used, key findings, business recommendations, limitations, and next steps

Practical Capstone Project

Final Capstone Presentation

Present the complete analytics portfolio to demonstrate business understanding, technical execution, communication quality, and practical decision support.

Technical Stack

20+ Gen AI Tools You Will Learn

Use 20+ modern tools that help with writing reports, creating drafts, organizing work, speeding up research, and saving time on daily tasks.

Excel
Excel
MYSQL
MYSQL
Tableau
Tableau
Python
Python
Power BI
Power BI
Pandas
Pandas
NumPy
NumPy
Scikit Learn
Scikit Learn
Jupyter
Jupyter
GitHub
GitHub

Get the Complete Tools List

Download all the tool lists that you will master throughout our NEXGEN Data Analytics Training

Industry-Relevant

Projects You Will Learn

E-Commerce Sales Performance
ExcelPivot TablesVLOOKUP

E-Commerce Sales Performance

Analyze retail data using Excel Pivot Tables, VLOOKUP, and professional data cleaning techniques to identify growth opportunities.

Our Alumni

See how our graduates are changing the world.

Success Story

Akreeti Sharma

Previous RoleStudent
Current RoleOperations Analyst
atFoxit
Placed ✓
Akreeti Sharma

Akreeti Sharma

• 3rd+

Operations Analyst at Foxit Software

12h

I'm excited to share that I'm starting a new position as a Operations Analyst at Foxit Software! I'm extremely grateful to my mentors at The NexaLearn, friends, and family for their endless support throughout this journey. #DataAnalytics #FoxitSoftware #CareerGrowth #NewBeginnings #Grateful

Starting a new position
👏
34
6 comments

Why Choose The NexaLearn

Study with the only boot camp that provides end-to-end support for your career.

Learn

Learn the Advanced Gen AI Course

Master modern tools for dashboards, reports, and faster tasks. Save your time, improve output, and stay ahead of average applicants by choosing the best data analytics courses.

4.7/5

Average Rating

Get Mentored

Get Mentored by Industry Experts

Learn from top industry mentors who handle reports, deadlines, dashboards, reviews, and hiring expectations in real corporate environments.

4.9/5

Average Rating

Build

Learn 20+ Gen AI Tools

Learn 20+ Gen AI tools for report creation, cleaner data workflows, presentation drafting, and faster day-to-day work.

20+

Gen AI Tools

SQL

SQL

Live in Project

Python

Python

Tableau

Tableau

Excel

Excel

Placement

Get Our Placement Service

Enroll in the best data analytics courses with a 100% job interview guarantee. Placement services include resume upgrades, interview preparation, hiring alerts, and career support.

100%

Interview Guarantee

Get Hired

Get Hired with 200+ Companies

Get access to The NexaLearn’s 200+ active hiring partners, including startups, agencies, service firms, and product companies hiring skilled analysts.

200+

Hiring Partners

GoogleAmazonMicrosoftMetaNetflixAdobeUberAirbnbSpotifySamsungOracleIBMGoogleAmazonMicrosoftMetaNetflixAdobeUberAirbnbSpotifySamsungOracleIBM
IBMOracleSamsungSpotifyAirbnbUberAdobeNetflixMetaMicrosoftAmazonGoogleIBMOracleSamsungSpotifyAirbnbUberAdobeNetflixMetaMicrosoftAmazonGoogle
GoogleAmazonMicrosoftMetaNetflixAdobeUberAirbnbSpotifySamsungOracleIBMGoogleAmazonMicrosoftMetaNetflixAdobeUberAirbnbSpotifySamsungOracleIBM
Data Analytics Certification

Globally Accepted
Data Analytics Certification

Receive a certification of our AI data analytics course that will make your resume stand out from other candidates.

Course Completion

Comprehensive mastery of Data Analytics and AI.

Microsoft Certification

Microsoft Certified Data Analyst Associate.

Google Certification

Google Data Analytics Professional Certificate.

Virtual Experience Programs

Accenture, Infosys, KPMG, and Quantium Virtual Experience Programs.

Internship Completion

Successful completion of the Data Analytics Internship.

Instant Verification

Every certificate is cryptographically signed and shareable to portfolios with a single click.

Course Completion
Full Session Review

Ankit Sharma

Senior Data Analyst

Tata Consultancy Services
Tata Consultancy Services
Expert Insights

Learn from Industry Experts

Master real-world data practices directly from top-tier leaders who engineer live production systems at global enterprises.

Tata Consultancy Services

Ankit Sharma

Senior Data Analyst

Tata Consultancy Services

Session Highlights

TCS Live Data Pipelines: Step-by-step walkthrough of enterprise preprocessing pipelines.

Advanced Python & SQL Workflows: Expert methods for dealing with missing values, deduplication, and anomaly detection.

Upcoming Cohorts

Flexible Batches

Busy with work or college? Pick flexible batches. Limited seats available per cohort.

Scholarships Available

Classroom Program - Data Analytics

Comprehensive training on Python, Power BI, SQL, and Advance Excel with real-world projects.

Weekday

19th May '26

Mon - Fri (7 PM - 9 PM)

Filling Fast
Weekend

23rd May '26

Sat - Sun (10 AM - 2 PM)

Open

Batch Strength

Limited to 25 Students / Batch

Free Career Guidance

Confused about the
right batch?

Talk to our academic counselors for a free 1-on-1 counseling session to evaluate your career goals.

Counselor
Counselor
Counselor

Counselors Online

Available to assist

Admissions Open

How To Join TheNexaLearn
Data Analytics Course?

We employ a simple, 3-step system to identify aspiring talent for careers in data. Take the first step today.

Application
Counseling
Confirm Enrollment
01

Submit Online Application

Complete the application form with your educational information, work experience, and learning interests.

15 Mins
1-on-1 Session
02

Career Counselling Session

Talk with our admissions counsellors about your objectives, clarify expectations, and ensure the program is a good fit for your career path.

03

Secure Your Seat

Fill out the required documentation and confirm your seat in the upcoming batch.

Fast-Track Entry

Next cohort starts in 12 days

Start Your Application

+91

By clicking proceed, you agree to our terms and conditions regarding the admission policy.

Investment Roadmap

Master AI with Transparent Fees.

One flagship program. Everything you need to launch your data career.

Flagship Program

Data Analytics
Gen AI

Advanced Industry Readiness

₹39,900 + GST/one-time

EMI options available • No hidden charges

  • Complete Gen AI Framework
  • Live Interaction Sessions
  • Industry Tools Mastery
  • Placement Preparation
  • NexaLearn Certification
  • 1-on-1 Mentorship
Secure Payments via
RazorpayMastercardUPIVisa

Invest in Skills, Not Financial Stress

Worried that the data analytics course fee may delay your plans? Our flexible payment options can help.

Monthly Installment

₹3,565/mo
0% Interest Plan
₹15,000
Min: ₹5,000Max: ₹24,000
9 Months

Who Should Do the Data Analytics with GenAI?

Career Starters

Graduates & College Students
  • Graduates from any stream who want to enter the analytics field

  • College students who want job-ready skills before graduation

Career Switchers

Professionals & Job Seekers
  • Working professionals planning a career switch into analytics

  • Sales, finance, operations, or marketing executives want better growth

Leaders & Creators

Business Owners & Freelancers
  • Freelancers wanting to offer analytics and reporting services

  • Business owners wanting to use data for smarter decisions

Upskilling First

In short, there is no such strict requirement to enrol in our Data Analytics Programme, as TheNexaLearn believes in upskilling.

Course Overview

Everything you need to know about the NexaLearn Data Analytics Program

About the Program

Recognised as one of the data analytics courses in India, the NexaLearn Data Analytics Course Powered by Gen AI creates analytical professionals who understand today’s tedious business workflows, automation tools, and data-driven thinking.

6Months

Program Duration

10+

Capstone Projects

500+

Hiring Partners

2K+

Students Placed

85%

Avg. Salary Hike

Experienced by our graduates within 3 months of placement.

4.9

/5

By 2,000+ Students

Ready to Start Your Journey?

Next batch starts Oct 24th. Limited seats available.

Frequently Asked Questions

Let's answer some questions

A data analytics course teaches you how to collect, clean, study, and present data for business decisions. You learn Excel, SQL, Python, dashboards, and reporting skills that companies value across many industries.

Yes, The NexaLearn offers best data analytics course that covers each and every 20+ Gen AI tools for reporting, research, workflow improvement, and business tasks, along with core skills like Excel, SQL, Python, and dashboards.

No, both fields are different. Data analytics focuses on reports, dashboards, trends, and business decisions. Data science covers advanced modelling, automation, coding, and predictive systems using larger datasets.

Yes, the course includes GenAI tools used for reports, summaries, dashboards, faster work tasks, and office productivity support.

To choose the right data analytics course, one must ensure that they provide live projects, updated tools, mentor support, placement help, flexible timing, and strong reviews. Pick programs that teach Excel, SQL, Python, Power BI, and AI skills. The NexaLearn offers all these facilities with 100% Job Interview Guarantee.

Still have questions? We are here to help you guide your path.