⚡ Short answer
A complete 2026 data analytics syllabus should cover analytics foundations, Python, Excel, SQL, Power BI and Tableau, statistics, real case studies, capstone projects and placement preparation. Our course delivers this in 16 modules over 3 months, with a lab or project in almost every module.
Syllabus overview
The 2026 syllabus at a glance
The order is deliberate: foundations first, then the tools employers test, then real-world application.
Course snapshot
What the full program includes
Duration
3 months
Modules
16
Core tools
6
Classroom and live online batches follow the same syllabus, projects and placement preparation.
This is the syllabus of our data analytics course in Hyderabad. Fees are ₹30,000 classroom or ₹27,000 online; see the full fee breakdown.
All 16 modules
Data analytics course syllabus: module by module
Every module ends with a lab, a tool skill or a clear outcome you can show an employer.
Module
What you learn
Outcome / lab
01 Introduction to Data Analytics
Descriptive, diagnostic, predictive and prescriptive analytics; business applications
Explain the four analytics types
02 Data Handling and Preprocessing
Data types, collection, missing data, cleaning and transformation
Clean a messy real dataset
03 Python Programming Fundamentals
Setup, Jupyter, variables, loops, functions and files
First analysis script from scratch
04 Python for Data Analytics
NumPy, Pandas DataFrames, regular expressions, manipulation
Hands-on with Pandas and NumPy
05 Excel for Data Analysis
Formulas, sorting, filtering, pivot tables, charts
Day-one job skills
06 Advanced Excel Analytics
Goal Seek, Solver, What-If analysis, large datasets, Flash Fill
Scenario model on a large dataset
07 SQL Fundamentals
Databases, SELECT, filtering, sorting, joins and grouping
Practice on MySQL and PostgreSQL
08 Advanced SQL for Analytics
Window functions, ranking, CTEs, transactions
Interview-level SQL
09 Tableau and Power BI Fundamentals
Connecting data, core charts, heat maps, dashboard basics
First interactive dashboard
10 Advanced Tableau and Power BI
Data blending, relationships, DAX, calculated fields, LOD
Multi-source executive dashboard
11 Alteryx for Data Automation
Alteryx Designer, input/output, filter, formula, workflows
Automated, repeatable workflow
12 Statistics for Data Analytics
Central tendency, variance, probability, hypothesis testing
Draw sound conclusions from data
13 Data Wrangling and Preprocessing
Merge, join, groupby, aggregation, feature preparation
Combine four raw sources into one table
14 Real-Time Case Studies
E-commerce, healthcare, finance, customer segmentation
Domain experience for interviews
15 Capstone Projects
Problem framing, analysis, dashboard delivery, presentation
Portfolio you present in interviews
16 Career Support and Placement Prep
Resume, LinkedIn, GitHub, SQL and Python interview practice
Mock interviews on real questions
💡 The syllabus is reviewed regularly so tools and examples stay current with what Hyderabad employers ask for.
Want to see how a module is taught before you join? Attend a free demo class with a trainer.
Book a free demoTools covered
The tools you will use hands-on
Every tool here appears regularly in data analyst job descriptions in Hyderabad.
Modules 05–06
Microsoft Excel
Formulas, pivots, What-If analysis and reporting: the tool you will use on day one.
Modules 07–08
SQL (MySQL, PostgreSQL)
From basic queries to window functions and CTEs. The most-tested interview skill.
Modules 03–04, 13
Python (Pandas, NumPy)
Cleaning, wrangling and analysing data at scale in Jupyter Notebook.
Modules 09–10
Power BI
Data models, DAX and interactive business dashboards.
Modules 09–10
Tableau
Visual analytics, calculated fields and LOD expressions.
Module 11
Alteryx
No-code workflow automation, a differentiator few fresher resumes have.
Month-by-month split
How the 3 months are organised
An indicative split. Exact pacing depends on the batch and is shared at enrolment.
M1
Month 1: Foundations, Python and Excel
Modules 01–06: analytics basics, data preprocessing, Python fundamentals, Pandas and NumPy, and Excel from basics to advanced.
M2
Month 2: SQL, BI tools and statistics
Modules 07–12: SQL to advanced level, Power BI and Tableau dashboards, Alteryx automation and statistics.
M3
Month 3: Real-world work and placement
Modules 13–16: data wrangling, case studies, capstone projects, resume, portfolio and mock interviews.
💡 Studying on your own instead? Follow the same order in our data analyst roadmap for 2026.
How to judge a syllabus
A checklist for comparing any course syllabus
Use this whether you choose us or another institute.
✓ Covers Excel, SQL, a BI tool and Python, not just one tool
✓ Includes advanced SQL such as window functions and CTEs
✓ Teaches statistics, not just software clicks
✓ Has real case studies and at least one capstone project
✓ Ends with resume, portfolio and mock interview preparation
✓ Is updated for the current year's tools and job market
Syllabus red flags
✕ A long list of buzzwords (AI, ML, big data) with no time allotted to each.
✕ No mention of projects or labs.
✕ SQL treated as a one-week topic.
FAQs
Syllabus questions, answered
How long is the data analytics course?
3 months for the full 16-module program, in both classroom and live online formats.
Does the syllabus include Python?
Yes. Python fundamentals, Pandas and NumPy are covered from scratch; no prior coding is needed.
Are both Power BI and Tableau included?
Yes. Modules 09 and 10 cover both tools from fundamentals to advanced features like DAX and LOD expressions.
Is machine learning part of the syllabus?
The focus is data analytics: Excel, SQL, BI, Python and statistics, which are what analyst jobs test. Machine learning is a separate data science path.
Is a certificate included?
Ask our team about certification for your batch. Employers care far more about your projects and skills, so that is where the course focuses.
Can I see the detailed syllabus before enrolling?
Yes. Book a free demo or message us on WhatsApp and we will share the detailed module plan.