Manual Testing
SDLC & STLC, test case design, defect life cycle, smoke, regression & UAT testing with real project examples.
- 1.5 Months
- ₹7,500
- 5 modules
Courses & full syllabus
Choose a course to see everything it covers, how long it runs and what it costs.
Showing all 12 courses
API Testing
REST APIs, HTTP methods, status codes, authentication, Postman tool, real-time API scenarios & automation intro.
- 1 Month
- ₹5,500
- 6 modules
Database – SQL
SQL queries, joins, sub-queries, constraints, data validation, UI vs DB testing & API vs DB validations.
- 1 Month
- ₹5,500
- 4 modules
Selenium Automation
Selenium WebDriver, locators, waits, TestNG, Page Object Model & complete automation framework design with Java.
- 8 modules
Playwright Automation
Playwright with JS/TypeScript, browser contexts, API integration, CI/CD pipeline & modern scalable framework design.
- 2 Months
- ₹9,500
- 5 modules
ETL Testing
ETL concepts, data mapping, transformations & SQL-based testing from banking, insurance & analytics domains.
- 3 Months
- ₹15,000
- 7 modules
JMeter Performance
Load, stress & scalability testing of web and APIs. JMeter test plans, thread groups, listeners & performance analysis.
- 6 modules
Data Engineer
Build scalable data pipelines with Python, SQL & Apache Spark. Covers ETL/ELT design, data warehousing & cloud data platforms (Azure/AWS).
- 3 Months
- ₹25,000
- 7 modules
Data Analytics
Turn raw data into business insights using Excel, SQL, Power BI & Python. Covers data cleaning, visualization & statistical analysis.
- 2 Months
- ₹12,000
- 7 modules
AI-Assisted Testing
Use AI tools to design and automate tests, and learn to test chatbots and other AI features.
- 4 modules
CI/CD & DevOps for Testers
Run automated tests in a delivery pipeline with Git, Jenkins, GitHub Actions and Docker.
- 4 modules
Mobile Testing with Appium
Manual and automated testing of Android and iOS apps with Appium 2 and cloud devices.
- 4 modules
No course matches that search.
Learning Paths
Not sure where to start?
Courses can be taken one at a time or in sequence. These two routes suit most learners.
Fresher
From zero to job-ready QA engineer
- Manual TestingTesting fundamentals and defect reporting
- Database – SQLSQL for data validation
- API TestingREST APIs and Postman
- Playwright AutomationWeb automation with TypeScript
Experienced tester
From manual or Selenium to modern automation
- Playwright AutomationModern web automation
- API TestingAPI testing and automation
- CI/CD & DevOps for TestersRunning tests in pipelines
- AI-Assisted TestingWorking with AI tools
Why These Skills
What QA job postings ask for in 2026
Employers hire for automation together with API testing, CI/CD and a programming language. Manual-only roles pay the least.
| Skill | Demand in job postings | Pay range in India |
|---|---|---|
| Playwright (TypeScript) | 2,496 vacancies on Naukri, Feb 2026; rated growing | ₹7–20 LPA, median ₹12 LPA |
| Selenium (Java) | Rated high | ₹5–14 LPA, median ₹8.5 LPA |
| API testing | In over 60% of automation postings | ₹5–16 LPA, median ₹9 LPA |
| CI/CD, Git, SQL | In over 60% of automation postings | CI/CD ownership adds ₹2–4 LPA |
| Performance testing (JMeter, k6) | In 30–60% of postings | ₹6–18 LPA, median ₹11 LPA |
| AI-assisted testing | Emerging in 2025–2026 postings | No reliable figure yet |
| Manual QA only | Rated medium | ₹3–8 LPA, median ₹5 LPA |
Sources: TestDino Test Automation Jobs Report 2026 and SoftwareTestPilot salary data, June 2026. Job counts are single-day snapshots. Pay ranges are market indications and not a promise of salary.
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Foundation
Manual Testing
The foundation of every QA career — from SDLC to UAT with real-project simulations and interview prep.
- Duration
- 1.5 MonthsMon–Thu, 4 sessions/week21 Days structured learning
- Fee
- ₹7,500
- Level
- Beginner → Mid
- Content
- 5 modules25 topics
- Tools
- JIRA, Bugzilla, MantisBT
Course content
5 modules · 25 topics
1Week 1 — Fundamentals of Software TestingDays 1–5
- 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
2Week 2 — Test Design Techniques & Defect ManagementDays 6–10
- 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
3Week 3 — Testing in Real EnvironmentsDays 11–15
- 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
4Week 4 — Advanced Concepts & ProjectDays 16–21
- 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
52026 Update — AI-Assisted Test DesignNew
- Using AI assistants to draft test scenarios, test cases and test data from requirements
- Prompt writing for testers: giving context, constraints and expected format
- Reviewing AI output: missed scenarios, wrong assumptions, duplicate cases
- Data privacy: what project information must never be pasted into an AI tool
Practice: generate test cases for a login and checkout flow with AI, then correct them by hand
In-Demand
API Testing
Master REST APIs and Postman from scratch — authentication, automation, data-driven testing & Newman CLI.
- Duration
- 1 Month2 sessions/week
- Fee
- ₹5,500
- Level
- Beginner → Advanced
- Content
- 6 modules28 topics
- Tools
- Postman, Newman
Course content
6 modules · 28 topics
1Module 1 — Introduction to API TestingFoundation
- 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
2Module 2 & 3 — Postman Fundamentals & API TestingCore
- 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
3Module 4 & 5 — Scripting & Data-Driven TestingAutomation
- 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
4Module 6, 7 & 8 — Collections, Newman & SecurityAdvanced
- 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
5Module 9 & 10 — Real Project & Interview PrepCapstone
- 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
62026 Update — API Automation in Code & CINew
- Coded API tests: Playwright API with TypeScript or REST Assured with Java
- JSON schema validation and reusable request helpers
- Running Newman and coded API suites in GitHub Actions and Jenkins
- API vs database validation, GraphQL basics, mocking services with WireMock
Practice: move one Postman collection into a coded suite that runs on every commit
Essential
Database – SQL
SQL for testers — from basic queries to joins, window functions and database testing best practices.
- Duration
- 1 MonthSat–Sun, 2 sessions/week
- Fee
- ₹5,500
- Level
- Beginner → Advanced
- Content
- 4 modules19 topics
- Tools
- MySQL, PostgreSQL, SQL Server
Course content
4 modules · 19 topics
1Module 1 — Introduction to Databases & SQLFoundation
- 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
2Module 2 — Understanding SQL Query TypesCore
- DML – SELECT, INSERT, UPDATE, DELETE
- DDL – CREATE, ALTER, DROP, TRUNCATE
- DCL – GRANT, REVOKE
- TCL – COMMIT, ROLLBACK, SAVEPOINT
3Module 3 — SQL for Testers (Deep Dive)Advanced
- 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()
42026 Update — Database Validation in ProjectsNew
- UI vs DB and API vs DB validation on a live application
- Test data setup and cleanup queries
- Running database checks from automation code (JDBC or Node)
- Using AI to draft and explain queries, and how to verify the result
High Value
Selenium Automation
Selenium WebDriver with Java — from core Java to a complete framework with TestNG, Page Object Model, BDD and CI.
- Duration
- Shared at the free demo
- Fee
- Shared at the free demo
- Level
- Mid → Advanced
- Content
- 8 modules28 topics
- Tools
- Java, Selenium WebDriver, TestNG, Maven, Cucumber, Jenkins
Course content
8 modules · 28 topics
1Module 1 — Core Java for TestersFoundation
- Data types, operators, control flow, arrays and strings
- OOP: classes, inheritance, polymorphism, abstraction, interfaces
- Collections, exception handling, file handling
- Java 8 basics: lambdas and streams
- Coding practice for interview rounds
2Module 2 — Selenium WebDriver BasicsCore
- WebDriver architecture and browser setup
- Locators: ID, name, CSS selectors and XPath
- Implicit, explicit and fluent waits
- WebElement and browser commands, navigation
3Module 3 — Advanced InteractionsCore
- Actions class: hover, drag and drop, keyboard
- Frames, multiple windows, alerts, dropdowns
- JavaScript executor, file upload, screenshots
- Web tables and date pickers
4Module 4 — TestNG & MavenFramework
- TestNG annotations, groups, priorities, data providers
- Parallel execution and listeners
- Maven: POM.xml, dependencies, build lifecycle
5Module 5 — Framework DesignFramework
- Page Object Model and Page Factory
- Data-driven testing with Excel and JSON
- Config files, logging, Extent or Allure reports
6Module 6 — BDD with CucumberAdvanced
- Gherkin feature files and step definitions
- Hooks, tags and sharing state between steps
- Running Cucumber with TestNG
7Module 7 — Grid, Git & CIAdvanced
- Selenium Grid 4 and running tests in Docker
- Git workflow for automation projects
- Jenkins pipeline to run the suite on every build
8Module 8 — Project & Interview PrepCapstone
- Hybrid framework for a banking or e-commerce application
- Code review of the project
- Java and Selenium interview questions, mock interview
2025+ Ready
Playwright Automation
Modern test automation with Playwright and TypeScript — from setup to CI/CD integration and real-world e-commerce projects.
- Duration
- 2 MonthsSat–Sun, 2 sessions/week
- Fee
- ₹9,500
- Level
- Mid → Advanced
- Content
- 5 modules25 topics
- Tools
- Playwright, TypeScript, VS Code, Cucumber, Allure
Course content
5 modules · 25 topics
1Ch. 1–4 — Setup & ConfigurationGetting Started
- 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
2Ch. 5–6 — Locators, Assertions & UI ElementsCore Skills
- 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
3Ch. 7–8 — Mouse, Keyboard & Test ManagementIntermediate
- 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
4Ch. 9–12 — Reporting, Utilities, Cucumber & ProjectAdvanced
- 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
52026 Update — API, CI/CD & AINew
- API testing with APIRequestContext, combining API setup with UI tests
- Network mocking and intercepting, reusing authentication state
- Parallel runs, sharding and visual comparison
- CI/CD: GitHub Actions and Jenkins pipelines, running tests in Docker
- AI-assisted automation: Playwright MCP, generating tests with AI and reviewing them
Practice: run the eCommerce project suite on every pull request
Specialized
ETL Testing
Industry-ready ETL Testing from beginner to advanced — covering SQL, PySpark, cloud platforms (Azure/AWS) and a final capstone project.
- Duration
- 3 MonthsFri 9–10:30 PM, Sat–Sun 2–4:30 PM
- Fee
- ₹15,000
- Level
- Mid → Advanced
- Content
- 7 modules28 topics
- Tools
- Informatica, Talend, SSIS, PySpark, Azure/AWS
Course content
7 modules · 28 topics
1Module 1 — ETL FundamentalsWeek 1
- 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
2Module 2 — SQL for ETL TestingWeeks 2–3
- 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
3Module 3 — ETL Testing ConceptsWeek 4
- 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
4Module 4 — ETL ToolsWeeks 5–6
- 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
5Module 5 — PySpark for ETL TestingWeeks 7–8
- 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
6Module 6 — Cloud ETL Testing (Azure & AWS)Weeks 9–10
- 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
7Module 7–9 — Data Quality, Automation, CI/CD & Final ProjectWeeks 10–12
- 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
Performance
JMeter Performance
Performance, load and stress testing of web applications and APIs with Apache JMeter, plus an introduction to k6.
- Duration
- Shared at the free demo
- Fee
- Shared at the free demo
- Level
- Mid → Advanced
- Content
- 6 modules20 topics
- Tools
- Apache JMeter, k6, Grafana
Course content
6 modules · 20 topics
1Module 1 — Performance Testing FundamentalsFoundation
- Load, stress, spike, soak and scalability tests
- Key metrics: response time, throughput, error rate, percentiles
- Workload modelling and performance requirements
2Module 2 — JMeter BasicsCore
- Installing JMeter, test plan structure
- Thread groups, samplers, listeners
- Recording a web flow, HTTP request defaults
3Module 3 — Scripting in DepthCore
- Correlation with regular expression and JSON extractors
- Parameterization with CSV data
- Assertions, timers, logic controllers
- API performance testing with JMeter
4Module 4 — Execution & AnalysisAdvanced
- Non-GUI runs and distributed testing
- HTML dashboard report, reading graphs
- Finding bottlenecks: application, database and server
- Writing the performance test report
5Module 5 — k6 & CIAdvanced
- k6 scripts, checks and thresholds
- Running performance tests in a CI pipeline
- Live monitoring with Grafana
6Module 6 — Project & Interview PrepCapstone
- Load test of a sample e-commerce application
- Results report with findings and recommendations
- Interview questions and mock interview
High Demand
Data Engineer
Build and manage production-grade data pipelines — from Python and SQL foundations to Apache Spark, orchestration and cloud data platforms.
- Duration
- 3 MonthsSat–Sun, 2 sessions/week
- Fee
- ₹25,000
- Level
- Mid → Advanced
- Content
- 7 modules25 topics
- Tools
- Python, SQL, PySpark, Airflow, Azure/AWS
Course content
7 modules · 25 topics
1Module 1 — Data Engineering FundamentalsWeeks 1–2
- 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
2Module 2 — Python for Data EngineeringWeeks 3–4
- 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
3Module 3 — SQL & Data ModelingWeeks 5–6
- 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
4Module 4 — Big Data & Apache SparkWeeks 7–9
- 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
5Module 5 — Workflow OrchestrationWeeks 10–11
- 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
6Module 6 — Cloud Data Platforms (Azure & AWS)Weeks 12–13
- 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
7Module 7 — Data Quality, CI/CD & CapstoneWeek 14
- 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
Trending
Data Analytics
Turn raw data into business decisions — from Excel and SQL fundamentals to Python analysis and interactive Power BI dashboards.
- Duration
- 2 MonthsMon–Thu, 3 sessions/week
- Fee
- ₹12,000
- Level
- Beginner → Mid
- Content
- 7 modules21 topics
- Tools
- Excel, SQL, Python, Power BI
Course content
7 modules · 21 topics
1Module 1 — Analytics Fundamentals & ExcelWeek 1
- 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
2Module 2 — SQL for AnalyticsWeeks 2–3
- 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
3Module 3 — Python for Data AnalysisWeeks 4–5
- 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
4Module 4 — Statistics & Data InterpretationWeek 6
- 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
5Module 5 — Data VisualizationWeek 7
- 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
6Module 6 — Power BI DashboardingWeeks 8–9
- Data modeling, relationships & DAX fundamentals
- Building interactive dashboards & reports
- Publishing, sharing & scheduling refreshes
Use Case: Build an interactive sales performance dashboard
7Module 7 — Capstone ProjectWeek 10
- 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
New 2026
AI-Assisted Testing
Use AI tools to design and automate tests faster, and learn how to test AI features such as chatbots.
- Duration
- Shared at the free demo
- Fee
- Shared at the free demo
- Level
- Mid
- Content
- 4 modules15 topics
- Tools
- AI assistants, Playwright MCP, coding assistants
Course content
4 modules · 15 topics
1Module 1 — Generative AI for Test DesignFoundation
- How large language models work and where they go wrong
- Prompt writing for testers
- Generating scenarios, test cases and test data from requirements
- Reviewing AI output for gaps and wrong assumptions
2Module 2 — AI in Test AutomationCore
- Coding assistants for writing and refactoring test code
- Playwright MCP and agent-driven test generation
- Self-healing locators
- AI-assisted failure analysis
3Module 3 — Testing AI FeaturesAdvanced
- Testing chatbots and LLM-based features
- Building evaluation sets
- Hallucination and bias checks
- Prompt-injection basics
- Data privacy rules for using AI at work
4Module 4 — ProjectCapstone
- Extend an existing test suite with AI assistance
- Document what the AI got wrong and how it was corrected
New 2026
CI/CD & DevOps for Testers
Run automated tests in a delivery pipeline with Git, Jenkins, GitHub Actions and Docker.
- Duration
- Shared at the free demo
- Fee
- Shared at the free demo
- Level
- Mid
- Content
- 4 modules10 topics
- Tools
- Git, GitHub Actions, Jenkins, Docker
Course content
4 modules · 10 topics
1Module 1 — Git for TestersFoundation
- Repositories, commits, branches and merges
- Pull requests and code review
- Resolving conflicts
2Module 2 — PipelinesCore
- CI/CD concepts and where tests fit
- Jenkins jobs and declarative pipelines
- GitHub Actions workflows, triggers and secrets
3Module 3 — Containers & ReportingAdvanced
- Docker basics and running tests in containers
- Publishing test reports from a pipeline
- Cloud basics on AWS or Azure
4Module 4 — ProjectCapstone
- A pipeline that runs a test suite on every commit and publishes the report
New 2026
Mobile Testing with Appium
Manual and automated testing of Android and iOS apps with Appium 2.
- Duration
- Shared at the free demo
- Fee
- Shared at the free demo
- Level
- Mid → Advanced
- Content
- 4 modules13 topics
- Tools
- Appium 2, Android Studio, Appium Inspector
Course content
4 modules · 13 topics
1Module 1 — Mobile Testing BasicsFoundation
- Native, hybrid and mobile web apps
- Android and iOS differences
- Emulators, simulators and real devices
- Mobile-specific test scenarios: interrupts, network, battery, permissions
2Module 2 — Appium Setup & LocatorsCore
- Appium 2 architecture, drivers and capabilities
- Appium Inspector and locator strategies
- First test on an Android app
3Module 3 — Gestures & FrameworkAdvanced
- Tap, swipe, scroll, long press
- Hybrid apps and context switching
- Page Object framework, parallel runs
4Module 4 — Cloud Devices & ProjectCapstone
- Running on cloud device farms
- CI integration
- Appium suite for a sample Android app