Is the demo class really free?

Yes. The demo is a free live session with our faculty. You see how classes run, get the course roadmap, batch timings and fees, and ask your questions. There is no obligation to join.

I have no IT background. Can I join?

Yes. Manual Testing, API Testing, Database – SQL and Data Analytics start from the basics. In the demo we suggest the right starting course for your background.

Are classes live or recorded?

Both. You can join live online classes or learn self-paced. Self-paced learners get monthly live doubt-clearing sessions with faculty.

How much do the courses cost?

Fees start at ₹5,500 (API Testing and Database – SQL). Each course's fee is listed on the courses page; for the rest we share it at the free demo.

Do you help with interviews?

Yes. Every course includes interview preparation with real questions, live scenarios and hands-on practice.

What happens after I book?

A counsellor calls or WhatsApps you within 24 hours to fix a demo time. You then receive the meeting link for the live demo by email and WhatsApp.

Software Testing Courses Online from ₹5,500 – Free Demo Class

Course Curriculum

Everything You'll Learn

Industry-aligned syllabi crafted by QA professionals. Click a course below to explore the full curriculum.

Manual Testing

The foundation of every QA career — from SDLC to UAT with real-project simulations and interview prep.

⏱️Duration: 1.5 Months (Mon–Thu, 4 sessions/week)

🎯Level: Beginner → Mid

📅21 Days structured learning

🛠️Tools: JIRA, Bugzilla, MantisBT

💰Fee: ₹7,500

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

Career Guidance & Mock Interview

Book Free Demo →

Day 1 – What is Software Testing? QA vs QC vs Testing, SDLC vs STLC, Roles & responsibilities, Overview of testing process
Day 2 – SDLC Models: Waterfall, V-Model, Agile, Spiral — pros, cons & how testing fits in each. Agile ceremonies & tester role
Day 3 – STLC Phases: Requirement analysis → Test Planning → Design → Execution → Defect Reporting → Closure. Entry & Exit Criteria
Day 4 – Types of Testing: Functional vs Non-functional, Manual vs Automation, Static vs Dynamic, Levels (Unit, Integration, System, UAT)
Day 5 – Test Scenarios, Test Cases, Test Data. How to write effective test cases. Industry-standard template. Practical: Login page test cases

Day 6 – Test Case Review, Traceability Matrix (RTM), Test Case Prioritization. Practical: Create RTM for a sample app
Day 7 – Black Box Techniques: Equivalence Class Partitioning (ECP), Boundary Value Analysis (BVA), Decision Table, State Transition, Use Case Testing
Day 8 – White Box Testing: Statement, Branch, Path Coverage. Black Box vs White Box comparison with practical examples
Day 9 – Defect Life Cycle: Severity vs Priority, Defect states (New → Open → Fixed → Retest → Closed), Bug report template
Day 10 – Defect Tracking Tools (JIRA, Bugzilla, MantisBT). Practical: Raise and track a defect in JIRA. Best practices for reporting

Day 11 – Static Testing & Reviews: Peer, Walkthrough, Inspection. Static vs Dynamic analysis. Practical: Team test case review
Day 12 – Functional Testing in Depth: Smoke vs Sanity, Regression, Re-testing, Ad-hoc & Exploratory Testing
Day 13 – Non-Functional Testing Overview: Performance, Security, Usability, Compatibility, Localization. Tools overview (JMeter basics)
Day 14 – Test Environment & Test Data Management: Environment setup, data creation, masking, management. Test Lab vs Production
Day 15 – Practical Session: End-to-end testing of sample web app. Create Test Scenarios, Test Cases, Execute, Log Defects, Test Summary Report

Day 16 – UAT and Alpha/Beta Testing: UAT process, real scenarios, checklist and sign-off
Day 17 – Testing Deliverables & Metrics: Test Plan, Test Strategy, Test Summary Report (TSR), Defect Density, Test Coverage
Day 18 – Risk & Quality Management: Risk-Based Testing, risk identification & mitigation, quality assurance processes
Day 19 – Real Project Simulation: Mini e-commerce project — RTM, Test Plan, Test Cases, Defects, walkthrough presentation
Day 20 – Interview Preparation: Top 50 manual testing Q&A, real-time project discussion, resume tips for QA roles, Mock Interview
Day 21 – Career Growth: Role guidance for 2–8 years experience, 50+ interview questions, profile setup on job portals, email automation for job replies

API Testing

Master REST APIs and Postman from scratch — authentication, automation, data-driven testing & Newman CLI.

⏱️Duration: 1 Month (2 sessions/week)

🎯Level: Beginner → Mid

🛠️Tools: Postman, Newman

💰Fee: ₹5,500

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

50+ Interview Questions & Mock Interview

Book Free Demo →

What is an API? API vs Web Services, SOAP vs REST
Importance and types of API Testing
HTTP Methods: GET, POST, PUT, DELETE, PATCH
Status Codes: 1xx, 2xx, 3xx, 4xx, 5xx
Request & Response Structure: Headers, Body, Parameters

Installing & setting up Postman, understanding the interface
Creating and sending requests: GET, POST, PUT, DELETE, PATCH
Managing Workspaces, Collections, Environments
Handling API Authentication: Basic Auth, OAuth 2.0, API Key, Bearer Token
Query vs Path Parameters, Headers & Cookies
Validating responses: Status Codes, Body, Headers

Postman Pre-Request Scripts vs Test Scripts (JavaScript)
Validating JSON Responses using Postman Assertions
Chaining requests & dynamic data passing
Importing CSV & JSON files for data-driven testing
Running API tests with multiple data inputs & dynamic variables

Creating & managing collections, collection variables, iteration mode
Newman (Postman CLI): Install, run collections via CLI, generate reports
API Security Testing: SQL Injection, XSS, Rate Limiting & Throttling
Testing Authentication & Authorization flows

End-to-end API Testing on a real-world project
Writing & executing automated API tests, generating reports
Debugging & fixing API issues
50+ Interview Questions, Mock Interviews, Best Practices

Database – SQL

SQL for testers — from basic queries to joins, window functions and database testing best practices.

⏱️Duration: 1 Month (Sat–Sun, 2 sessions/week)

🎯Level: Beginner → Mid

🛠️MySQL, PostgreSQL, SQL Server

💰Fee: ₹5,500

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

Career Guidance

Book Free Demo →

What is a Database? Relational vs NoSQL types
Understanding DBMS and popular RDBMS (MySQL, PostgreSQL, Oracle, SQL Server)
Introduction to SQL & its importance in testing
Database Testing vs UI Testing

DML – SELECT, INSERT, UPDATE, DELETE
DDL – CREATE, ALTER, DROP, TRUNCATE
DCL – GRANT, REVOKE
TCL – COMMIT, ROLLBACK, SAVEPOINT

Filters: WHERE, AND, OR, IN, NOT IN, BETWEEN, LIKE, IS NULL, IS NOT NULL, EXISTS, ALL, ANY
Operators: Comparison, Logical, Arithmetic, Set Operators
Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX(), GROUP BY, HAVING
Joins: Inner, Left, Right, Full, Self, Cartesian
String Functions: SUBSTRING(), INSTR(), CHARINDEX(), CONCAT(), LENGTH(), REPLACE(), ROUND(), CEIL(), FLOOR()
CTE, CASE WHEN, Date Functions
Ranking Functions: ROW_NUMBER(), RANK(), DENSE_RANK()

Playwright

Modern test automation with Playwright and TypeScript — from setup to CI/CD integration and real-world e-commerce projects.

⏱️Duration: 2 Months (Sat–Sun, 2 sessions/week)

🎯Level: Beginner → Advanced

🛠️Tools: Playwright, TypeScript, VS Code, Cucumber, Allure

💰Fee: ₹9,500

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

Career Guidance

Book Free Demo →

Overview of Playwright features and VS Code installation
Configuring Playwright in Visual Studio Code
Test Annotations and async/await, Browser Context & Page Fixtures
Importance of the configuration file, running tests in multiple browsers
Creating and running tests in VS Code, Test Generator (Codegen), Playwright Inspector

Finding elements with XPATH & CSS Selectors, Built-in Locators
Implementing Assertions — Soft and Hard
Input Boxes, Radio Buttons, Checkboxes, Dropdowns, Multi-Select
Auto-Suggestions, Dialogs, Alerts, Multiple Windows, Frames
Web Tables and Date Pickers

Mouse Hover, Right Click, Double Click, Drag & Drop
Keyboard Interactions, File Uploads
Hooks, Test Grouping, Test Tagging, Annotations
Page Object Model (POM) in Playwright
Retrying Failed Test Cases — Handling Flakiness

Screenshots, Test Videos, Trace Viewer for Debugging
Built-in Reports and Allure Reports
Reading/Writing Excel Files, Handling JSON Data
Playwright with Cucumber: BDD integration, writing & executing BDD test cases
Real-World Project: eCommerce app automation with POM + Cucumber

ETL Testing

Industry-ready ETL Testing from beginner to advanced — covering SQL, PySpark, cloud platforms (Azure/AWS) and a final capstone project.

⏱️Duration: 3 Months (Fri 9–10:30 PM, Sat–Sun 2–4:30 PM)

🎯Level: Beginner → Advanced

🛠️Tools: Informatica, Talend, SSIS, PySpark, Azure/AWS

💰Fee: ₹15,000

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

Career Guidance

Book Free Demo →

Data Engineering & ETL Pipeline Introduction, ETL vs ELT
SDLC vs STLC for ETL Projects
Data Warehouse vs Database, OLAP vs OLTP
Star / Snowflake Schema, Dimensions, Facts, Keys
Slowly Changing Dimensions (SCD Types 1–6)

Mini Practice: Create schema diagrams of a Sales Data Warehouse

Joins, Grouping, Window Functions; CTE, Subqueries, Aggregates
Ranking: ROW_NUMBER, RANK, DENSE_RANK
Data Validation Queries, UNION vs UNION ALL
Query Performance Tuning Basics

Hands-on: Compare source vs target using SQL, build SCD queries, duplicate/null/PK-FK validation

ETL Testing Lifecycle: Test Plan, Strategy, Test Case Design
Functional vs Non-Functional Testing, Data Validation & Reconciliation
Source-to-Target Mapping (STM/STTM), Completeness/Correctness/Consistency checks
Incremental vs Full Load Testing, Referential Integrity, Error Handling

Project Activity: Write ETL test cases with mapping sheet

Informatica PowerCenter: Workflows, mappings, transformations, session log validation
Talend Open Studio: Components, joins, tMap, tSortRow, debugging, metadata
SSIS: Packages, data flow tasks, Lookup, Merge Join, Derived Columns

Task: Perform ETL load & validate using SQL Test Cases

PySpark DataFrame APIs: Joins, aggregations, window functions
Data validation using PySpark Assertions, handling schema changes
Big Data File Testing: CSV, JSON, Parquet, ORC, Avro
Partitioning, Bucketing, Performance Tuning

Assignment: Build automated source vs target validation in PySpark

Azure: Data Factory Testing, Databricks ETL validation, ADLS file formats/partitions, Delta Lake & Time Travel
AWS: S3 validation, Glue ETL testing, Athena DQ queries, EMR PySpark execution testing

Use Case: Validate ETL pipeline from S3 → Glue → Redshift

SCD Types 1–6 Validation, Great Expectations Data Quality Framework
DQ Rules: null %, duplicate %, schema drift, alerting & reporting
Automate reconciliation scripts with PySpark + PyTest
GitHub Actions / Azure DevOps pipeline for DQ jobs
ETL Performance Testing: Load & Stress Testing
Security: Role-based access, audit, encryption, backup & recovery

🏆 Final Capstone: Build and test an end-to-end ETL pipeline

Data Engineer

Build and manage production-grade data pipelines — from Python and SQL foundations to Apache Spark, orchestration and cloud data platforms.

⏱️Duration: 3 Months (Sat–Sun, 2 sessions/week)

🎯Level: Mid → Advanced

🛠️Tools: Python, SQL, PySpark, Airflow, Azure/AWS

💰Fee: ₹25,000

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

Career Guidance & Mock Interview

Book Free Demo →

What is Data Engineering, role in the data lifecycle, ETL vs ELT
Data Lake vs Data Warehouse, OLTP vs OLAP
Batch vs Streaming pipelines, data pipeline architecture overview
File formats: CSV, JSON, Parquet, Avro, ORC

Mini Practice: Map out a simple end-to-end pipeline architecture

Python fundamentals: data types, loops, functions, error handling
Pandas & NumPy for data wrangling and transformation
Reading/writing CSV, JSON & Parquet files
Consuming REST APIs and working with authenticated data sources

Hands-on: Build a Python script to ingest and clean raw data

Advanced SQL: joins, subqueries, CTEs, window functions
Star & Snowflake schema design, fact/dimension tables
Normalization vs denormalization, indexing & query performance
Slowly Changing Dimensions (SCD Types 1–3)

Project Activity: Design a data warehouse schema for a retail dataset

Spark architecture: Driver, Executors, Cluster Manager
PySpark DataFrames: transformations, actions, joins, aggregations
Spark SQL, partitioning, bucketing & performance tuning
Handling large-scale batch data pipelines

Assignment: Build a PySpark job to process and aggregate a large dataset

Apache Airflow: DAGs, operators, scheduling & dependencies
Monitoring, retries, alerting & failure handling
Intro to dbt for transformation workflows

Task: Orchestrate a multi-step pipeline with Airflow DAGs

Azure: Data Factory pipelines, Databricks, ADLS storage
AWS: S3, Glue ETL jobs, Redshift, Athena queries
Choosing the right service for batch vs streaming workloads

Use Case: Build a pipeline from S3 → Glue → Redshift

Data quality checks with Great Expectations
Version control with Git & CI/CD pipelines for data jobs
Logging, monitoring & production best practices

🏆 Final Capstone: Build and deploy an end-to-end data pipeline

Data Analytics

Turn raw data into business decisions — from Excel and SQL fundamentals to Python analysis and interactive Power BI dashboards.

⏱️Duration: 2 Months (Mon–Thu, 3 sessions/week)

🎯Level: Beginner → Mid

🛠️Tools: Excel, SQL, Python, Power BI

💰Fee: ₹12,000

Access to Recorded Videos

Thoughtful Assignments

Comprehensive Study Materials

Resume Preparation Assistance

Career Guidance & Mock Interview

Book Free Demo →

Role of a Data Analyst, analytics lifecycle overview
Excel formulas, lookups (VLOOKUP/XLOOKUP), pivot tables & charts
Data cleaning techniques: duplicates, blanks, formatting issues

Mini Practice: Clean and summarize a messy sales dataset in Excel

SELECT, filtering, sorting, joins & aggregations
Subqueries, CTEs & window functions for reporting
Writing queries to answer real business questions

Hands-on: Build reporting queries on a sample sales database

Python basics for analysts, Pandas & NumPy essentials
Data wrangling: filtering, grouping, merging datasets
Exploratory Data Analysis (EDA) techniques

Project Activity: EDA on a real-world dataset with Pandas

Descriptive statistics: mean, median, mode, standard deviation
Distributions, correlation & basics of hypothesis testing
Interpreting results for non-technical stakeholders

Task: Summarize statistical findings in a one-page insight brief

Matplotlib & Seaborn for charts and plots
Choosing the right chart type, storytelling with data
Design principles for clear, decision-ready visuals

Assignment: Build a visual report from a business dataset

Data modeling, relationships & DAX fundamentals
Building interactive dashboards & reports
Publishing, sharing & scheduling refreshes

Use Case: Build an interactive sales performance dashboard

End-to-end business case study: raw data to insights
Combining SQL, Python & Power BI in one workflow
Presenting findings & recommendations to stakeholders

🏆 Final Capstone: Present a complete analytics case study

Quality Testing
Careers Start Here

Where Learning Takes Flight

Learn. Build. Get Hired.

Everything You'll Learn

Manual Testing

API Testing

Database – SQL

Playwright

ETL Testing

Data Engineer

Data Analytics

Learning Without Limits

Start Your
Journey Today

Before You Book

Building the Future
of QA Careers

Hiring Partners

Tech Companies

Impact Investors

Inclusive Growth

Quality Testing Careers Start Here

Where Learning Takes Flight

Learn. Build. Get Hired.

Everything You'll Learn

Manual Testing

API Testing

Database – SQL

Playwright

ETL Testing

Data Engineer

Data Analytics

Learning Without Limits

Start YourJourney Today

Before You Book

Building the Futureof QA Careers

Hiring Partners

Tech Companies

Impact Investors

Inclusive Growth

Quality Testing
Careers Start Here

Start Your
Journey Today

Building the Future
of QA Careers