★★★★★ 4.8 / 5  ·  1,200+ reviews

Data Analytics
with Python

From spreadsheets to Python pipelines — master the full analytics stack in 6 months and step into a Data Analyst role with confidence.

⏱ 6 Months 🖥 Online & Offline 🎓 Certificate Included 💼 100% Placement Assistance
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Data Analytics with Python Course
Why The XL Academy

What Makes This Program Different

3,000+ learners have chosen The XL Academy over self-paced online platforms. Here's why.

🎯

Industry-Aligned Curriculum

Regularly updated with the latest tools, technologies, market demands and industry hiring requirements.

🛠️

Hands-On Learning from Day One

Learn by doing with live projects, real datasets, and practical assignments & become Master in industry tools through practical training.

👨‍🏫

Industry Expert Trainers

Get trained by experienced professionals with 10+ years of industry expertise, who bring real-world insights, practical knowledge, and interview-focused guidance to every session.

💼

100% Placement Support

Get job-ready with Resume Building, LinkedIn Optimization, Mock Interviews, Career Mentoring & Placement Assistance.

Where You'll Land

Roles You Can Target After This Course

Our graduates work at top companies across e-commerce, finance, consulting, and tech.

📊 Data Analyst
₹4 – 9 LPA
TCS, Wipro, Infosys, Accenture, Deloitte, Genpact, HCL
📣 Marketing Analyst
₹5 – 10 LPA
Amazon, Flipkart, Meesho, Urban Company, Zomato, Swiggy
📦 Product Analyst
₹6 – 12 LPA
Paytm, PhonePe, Ola, Razorpay, CRED, Zepto
📋 Business Analyst
₹5 – 11 LPA
KPMG, EY, PwC, Mu Sigma, Tiger Analytics, Fractal
📈 BI Developer
₹5 – 10 LPA
Cognizant, Capgemini, Tech Mahindra, Mphasis, Hexaware
🔍 Operations Analyst
₹4 – 8 LPA
Hitachi, DHL, Mahindra, Max Life, ICICI, HDFC Bank
Detailed Curriculum

Data Analytics with Python Course Syllabus

Comprehensive 6-Month Training — Module-by-Module & Day-by-Day Breakdown

Advance Excel
▼
  • Day 1Excel Components (Tabs, Ribbons, Workbook, Sheet, Row, Columns, Cells), Cell Address, Data Entry, Selections & Data Formatting
  • Day 2Using 'Go To' (Blanks, Comments, Formulas), Copy/PasteSpecial, Data Sorting & Filtering, Data Validations, Remove Duplicates, Text To Columns, Find & Replace
  • Day 3Subtotals, Group & Ungroup, Data Protection (Cells, Sheet, Workbook), Conditional Formatting, What-If Analysis (Goal Seek, Tables & Scenario Manager)
  • Day 4Excel Operations, Formulas & Basic Functions (Sum, Count, Average, Left, Right, Mid, Len, Find, Search, Replace, Today, Now), Error Checking & Formula Evaluation
  • Day 5Excel Charts, Chart Modifications & Advanced Charting Techniques
  • Day 6If & Nested If Functions with AND/OR, Logical Functions, Text Functions, Date & Time Functions
  • Day 7Lookup & Reference Functions: VLOOKUP, XLOOKUP, MATCH, INDEX, ADDRESS, INDIRECT & combinations
  • Day 8Mathematical Functions & Database Functions
  • Day 9Understanding Pivot Tables, Pivot Charts, Formatting, Custom Formulas in Pivot Tables & Slicers
  • Day 10Power Pivot Fundamentals: Data Relationships, Visualizing Power Pivot Data, Power Pivot Reports, DAX Calculations, KPIs & Date/Time Functions
  • ProjectsBuilding Real-world Executive Trend & Product Performance Dashboards
Python + Statistics + Pyspark
▼
  • Day 1-3Python Overview, Installation (Anaconda, Colab), IDEs, Objects, Data Types, Mutability, Operators, Magic Commands (%Run, %Load), Strings, Formatting & Indexing
  • Day 4-6Lists, Tuples, Dictionaries, Sets, Control Flow (If-Else), Loops (For, While, Break, Continue, Nested Loops), List & Tuple Comprehensions
  • Day 7-9Dictionary & String Methods, Regular Expressions (Regex), Functions, Lambda, Map, Filter, Reduce, Zip, Accumulate, Decorators, Modules & Generators
  • Day 10-11Statistics for Data Science: Population vs Sample, Sampling Techniques, Central Tendency, Dispersion, Normalization vs Standardization (Z-Score), Probability & Math/NumPy Practical
  • Day 12-14OOPs Concepts (Class, Objects, Init, Inheritance, Polymorphism, Encapsulation), File Handling (Modes, Reading/Writing with 'with'), Exception Handling, Logging & SQL Server Connection
  • Day 15-17Data Analytics Libraries: NumPy Multi-dimensional Arrays, Pandas DataFrames, Data Cleaning & Visualizations (Matplotlib, Seaborn, Plotly)
  • Day 18-20Python Analytics Project Discussion, Big Data Architecture, Apache Spark, PySpark Queries, Git & GitHub Version Control & APIs
SQL Server
▼
  • Unit 1-2SQL Overview & RDBMS Concepts, T-SQL Foundation Statements, SELECT, INSERT, SQL Commands (DDL, DML, DCL, DQL), Data Types, Create, Alter, Drop, Delete, Update
  • Unit 3-4SQL Operators (Arithmetic, Comparison, Logical), Database Normalization (1NF, 2NF, 3NF), JOINS (INNER, LEFT, RIGHT, FULL, SELF, CARTESIAN) & SQL Constraints
  • Unit 5-6SQL Clauses (WHERE, ORDER BY, GROUP BY, HAVING, TOP, LIKE, UNION), Sub-Queries (Nested, Correlated, EXISTS Operator), System Functions (AVG, COUNT, MAX, MIN, SUM, SQRT, CONCAT, SUBSTRING, DATEDIFF, FORMAT)
  • Unit 7-8User Defined Functions (Scalar & Table-valued UDFs), Database Indexes (CREATE INDEX), Views, Stored Procedures, Transactions (Commit, Rollback, Savepoint), Identity Sequences & Triggers
Power BI
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  • Class 1-3Introduction to Power BI, Cloud Architecture, Data Source Library, Report Designer, Visuals, Fields, Auto Filters, GET DATA, Direct Query & Real-Time Data Access
  • Class 4-5Chart & Map Reports (Stacked/Clustered Bar/Column, Waterfall, Scatter, Pie, Maps), Hierarchies & Drilldown Reports, Drill-thru Options, Parameters
  • Class 6-7Power Query & M Language (Part 1 & 2): Query Editor, Data Transformations, Merge Join, Anti-Join, Union, Custom Columns & Applied Steps
  • Class 8-9DAX Expressions Level 1 & 2: Row/Filter Context, Calculated Columns, Measures, YTD/QTD/MTD Calculations, Time Intelligence, RANKX, STDEV, TOPN
  • Class 10-11Power BI Cloud Deployment, Workspaces, Dashboards, Real-Time Pins, Personal/Enterprise Gateways, Data Refresh Architecture & Subscriptions
  • Class 12-13Improving Reports: Templates (.pbit), Gateway Settings, Natural Language Q&A (Cortana) & Quick Insights
Tableau
▼
  • FundamentalsTableau Fundamentals (24 Hrs/8 Days): Overview Dashboard, Sheets & Menu Items, Combined/Dual Axis Charts, Reference Lines, Sets, Histograms, Groups & Hierarchies, Custom Dates, Data Filters, Filled Maps, Heat Maps, Highlight Tables, String/Date Conversions & Motion Charts
  • AdvancedTableau Advanced: Data Blending, Dashboard Actions & Navigation, Box & Whisker Plots, Bullet Graphs, Calculated Fields & Joins, Data Extracts, Dual Axis Maps, Dynamic Measure Selection, Pareto Charts, Forecast Trend Lines, Small Multiples & Window Averages
Enroll Today

Fee, Batches & Centres

Transparent pricing. EMI options available. Seats are limited per batch — reserve yours early.

₹35,000 + Tax
* All study materials, projects & certificate included
Duration6 Months
ModeOnline & Offline
Batch SizeMax 20 Students
CertificateThe XL Academy
  • 100+ hours live instructor-led sessions
  • 80+ Notes + Assignments
  • 6+ Live projects
  • Doubt-clearing after every module
  • Resume & LinkedIn profile review
  • Mock interviews + placement drives
Talk to a Counsellor
💳 EMI starts from ₹3,999/month  ·  Education loan available

Upcoming Batches

Weekday BatchMon to Fri — 10:00 AM to 6:00 PM
Starting Soon
Weekend BatchSat & Sun — 10:00 AM to 6:00 PM
Few Seats Left
Online BatchFlexible — recorded backups included
Open

Available Centres

📍 New Delhi (HQ) 📍 Gurugram 📍 Noida 📍 Bangalore 📍 Pune 📍 Mumbai 🌐 Online
Market Opportunity

Data Analytics Is One of India's Most In-Demand Skills

Every industry — from banking and e-commerce to healthcare and consulting — is hiring analysts who can turn data into decisions. Demand keeps outpacing the supply of skilled talent.

₹5 – ₹14 LPA
Typical salary range for Data Analyst roles — 1 to 4 years experience
25%
Projected growth in analyst roles over the next 5 years
1.4M+
Analytics & data job openings expected in India by 2027
$16B
India's analytics & AI market projection by 2026
40K+
Open Data Analyst roles in India on LinkedIn at any time
Common Questions

Data Analytics with Python — FAQs

Do I need prior coding experience to join this course?
No. This course is designed to take you from zero to a job-ready level. We start with Excel and introduce Python gradually — by the time you reach the Python modules you'll already have strong data foundations.
What is the difference between this course and the Data Science course?
Data Analytics with Python focuses on analysis, dashboards, and business reporting (Python, SQL, Power BI, Tableau). Data Science goes deeper into Machine Learning, Statistics, and model building — it's better suited for those targeting ML Engineer or Data Scientist roles.
How are the classes delivered?
Both Online (Live Session) and Offline Classes (Delhi, Gurgaon, Noida, Mumbai, Pune, Bangalore) options are available. The curriculum, projects, and placement support are identical across both modes.
What kind of projects will I build?
Two industry-grade capstone projects: an e-commerce analytics dashboard (end-to-end with Python + Power BI) and a financial performance report (SQL + Tableau). Both are portfolio-ready and interviewable.
Is placement guaranteed?
We provide 100% placement assistance — resume building, mock interviews, access to placement drives, and direct referrals. Final placement depends on student performance and effort during prep.
Is EMI available?
Yes — EMI starts at just ₹3,999/- only. Education loan options through partner NBFCs are also available. Call +91 73036 09096 for a personalised fee plan.

Ready to Start Your Data Analytics Career?

Book a free demo class and see how we teach — no commitment, no pressure. New batch starting soon.

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