Inquire now

Duration 3 days – 21 hrs

 

Overview

This training provides a complete, practical foundation in software testing—covering the testing lifecycle (STLC), testing methodologies, test design techniques, defect management, test documentation, and quality practices used in real projects. Participants will learn how to plan, design, execute, and report tests effectively across web/mobile/API systems, and build a strong understanding of how testing integrates with Agile/DevOps delivery.

Objectives

  • Explain the role of QA/testing in software delivery and how quality is built-in.
  • Apply the Software Testing Life Cycle (STLC) from requirements to test closure.
  • Distinguish testing levels (unit, integration, system, UAT) and testing types (functional, non-functional).
  • Create effective test plans, test scenarios, and test cases using standard templates.
  • Use core test design techniques (equivalence partitioning, boundary value analysis, decision tables, state transition, exploratory).
  • Execute tests, manage evidence, and report results with clear traceability to requirements.
  • Log, triage, and verify defects using defect lifecycle best practices and severity/priority guidelines.
  • Perform Agile testing practices (user stories, acceptance criteria, sprint testing) and communicate risks and quality status.

Target Audience

  • Beginner to intermediate QA/Testers
  • Developers who need stronger testing discipline
  • Business Analysts/Product Owners involved in acceptance criteria and UAT
  • Project Managers/Scrum Masters who need QA visibility and governance
  • Support/Operations staff involved in regression and release verification

Prerequisites 

  • Basic understanding of software applications (web/mobile)
  • Basic SDLC awareness helpful but not required
  • Comfort with reading requirements/user stories is recommended
  • No coding required (automation is optional add-on)

 

Course Outline 

Module 1 — Introduction to Software Quality and Testing

  • Why testing matters: cost of defects, customer impact, risk control
  • QA vs QC; verification vs validation
  • Common myths and realities of testing
  • Quality attributes overview (functionality, reliability, usability, security, performance)

Module 2 — SDLC and STLC (Testing Lifecycle)

  • SDLC models: Waterfall, Agile, V-Model (testing perspective)
  • STLC phases:
    1. Requirements analysis
    2. Test planning
    3. Test design/development
    4. Test environment setup (concepts)
    5. Test execution
    6. Defect reporting & re-test/regression
    7. Test closure and lessons learned
  • Entry/exit criteria, Definition of Ready/Done (Agile context)

Module 3 — Testing Levels and Testing Types

  • Test levels: unit, integration, system, UAT (roles and ownership)
  • Functional testing: UI, API, workflow-based
  • Non-functional testing overview: performance, security, usability, compatibility, accessibility
  • Smoke vs sanity vs regression vs re-test
  • Static testing: reviews, walkthroughs, and requirement inspection

Module 4 — Requirements Understanding and Traceability

  • Translating requirements into testable statements
  • User stories and acceptance criteria (Given-When-Then)
  • Traceability Matrix (RTM): mapping requirements ↔ test cases ↔ defects
  • Managing changes: impact analysis for test updates

Module 5 — Test Planning and Test Strategy

  • What goes into a test plan: scope, approach, schedule, resources, risks
  • Test estimation basics (coverage, complexity, effort)
  • Test environment and test data planning
  • Risk-based testing: prioritizing what to test first
  • Test metrics and reporting expectations

Module 6 — Test Design Techniques (Core Competency)

  • Test scenario design: happy path + negative path + edge cases
  • Black-box techniques:
    • Equivalence Partitioning (EP)
    • Boundary Value Analysis (BVA)
    • Decision Table Testing
    • State Transition Testing
    • Pairwise / combinatorial testing (intro)
  • Exploratory testing: charters, time-boxing, note-taking, debriefing
  • Coverage thinking: functional coverage vs risk coverage

Module 7 — Test Documentation Standards (Practical Templates)

  • Writing effective test cases: clarity, steps, expected results, data, preconditions
  • Test suite organization and naming conventions
  • Evidence collection standards (screenshots, logs, video)
  • Versioning and maintaining test artifacts

 

Module 8 — Test Execution and Result Management

  • Execution discipline: how to run tests consistently
  • Recording outcomes: pass/fail/block, notes, evidence
  • Handling blockers and environment issues
  • Regression planning and execution for releases
  • Retest vs regression: when and why

Module 9 — Defect Management and Defect Lifecycle

  • Defect lifecycle: new → triage → assigned → fixed → retest → closed/reopen
  • Writing high-quality bug reports (steps, expected vs actual, evidence, environment)
  • Severity vs priority (with examples)
  • Triage meeting practices and root-cause thinking
  • Preventing defect leakage: when to stop the line

Module 10 — Agile Testing Practices and Collaboration

  • Testing in Scrum: story refinement, sprint testing, sprint review readiness
  • Acceptance testing and UAT support
  • Collaboration patterns: QA + Dev + BA + PO
  • Continuous testing mindset in DevOps (overview)
  • Test pyramid concept (unit vs service vs UI), high-level

Module 11 — Test Reporting, Metrics, and Test Closure

  • Test reports: what stakeholders need (status, risks, readiness)
  • Useful metrics: execution progress, defect trends, escape rate (intro)
  • Go/No-Go decision support
  • Test closure: summary, lessons learned, improvement actions

Module 12 — Capstone Workshop (Hands-On)

Participants complete an end-to-end mini testing cycle using a sample application/system case:

  • Extract testable requirements from a feature description
  • Create test scenarios and test cases using EP/BVA/decision tables
  • Execute a subset (simulated) and record results
  • Write defect reports with severity/priority
  • Create a simple test summary report + risks

Inquire now

Best selling courses

The Data Analytics with DAX, Python, SQL, and Business Intelligence Tools Training Course provides participants with practical knowledge and skills for collecting, preparing, analyzing, modeling, and visualizing data to support informed business decision-making. The course combines key data analytics technologies and techniques, including Python, SQL, DAX (Data Analysis Expressions), Power BI, data modeling, data transformation,...

The Project Management – SDLC (Software Project Management: The Complete Course) Training Course is a comprehensive program designed to equip project managers, software development leaders, business analysts, product owners, and IT professionals with the knowledge and practical skills required to successfully manage software development projects throughout the entire Software Development Life Cycle (SDLC). This course...

Warehouse Operations and Inventory Management Training Course     Duration 2 Days – 14 hrs.   Overview   This course provides a practical understanding of warehouse operations and inventory management for personnel who supervise, review, or audit warehouse processes. It covers the movement of goods from receiving through dispatch, with emphasis on warehouse layout, storage systems, picking strategies, stock rotation, inventory accuracy, and operational controls.   Participants will learn to identify process weaknesses, investigate stock discrepancies, reduce shrinkage, and interpret warehouse productivity indicators. The course connects day-to-day warehouse activities with the records, controls, and performance measures needed for effective supervision and auditing.   Objectives  

  • Explain warehouse processes and their impact on inventory accuracy and service performance.
  • Evaluate warehouse layouts, storage systems, and product locations.
  • Identify appropriate controls for receiving, put-away, storage, picking, and dispatch.
  • Apply First-In, First-Out (FIFO) and First-Expired, First-Out (FEFO) principles.
  • Compare picking strategies based on order characteristics and operational requirements.
  • Identify causes of inventory discrepancies and recommend corrective actions.
  • Develop a cycle counting approach based on inventory value, movement, and risk.
  • Recognize sources of shrinkage and recommend preventive and detective controls.
  • Interpret warehouse productivity and inventory performance KPIs.
  • Review warehouse processes using supporting records, observations, and control evidence.
        Target Audience  
  • Warehouse supervisors, team leaders, and managers.
  • Inventory controllers and stock control personnel.
  • Logistics and distribution supervisors.
  • Internal auditors and operational compliance personnel.
  • Supply chain and operations professionals.
  • Personnel responsible for reviewing warehouse controls and performance.
  Prerequisites  
  • Basic familiarity with warehouse, logistics, or inventory activities.
  • General understanding of business processes and operational documentation.
  • Basic numerical skills, including percentages and simple calculations.
  • Basic spreadsheet skills are helpful.
  • No prior experience with a specific Warehouse Management System (WMS) is required.
   

Course Outline

  Day 1: Warehouse Processes, Layout, and Storage Controls Module 1: Warehouse Operations and Process Controls  
  • Warehouse roles within the supply chain.
  • End-to-end flow: receiving, put-away, storage, replenishment, picking, packing, and dispatch.
  • Physical stock movement and corresponding system transactions.
  • Responsibilities, authorization, and segregation of duties.
  • Common operational weaknesses and audit evidence.
  Module 2: Warehouse Layout and Storage Systems  
  • Functional zones, movement paths, and space utilization.
  • Receiving, storage, picking, staging, and dispatch areas.
  • Storage options: floor stacking, shelving, pallet racking, and bin storage.
  • Fixed and dynamic location systems.
  • Product slotting based on movement, size, handling needs, and compatibility.
  • Layout bottlenecks and their effects on productivity and inventory control.
  Module 3: Receiving and Put-Away  
  • Purchase orders, delivery documents, and expected receipts.
  • Quantity, condition, and item identification checks.
  • Recording shortages, overages, damage, and discrepancies.
  • Controls for acceptance, quarantine, and release.
  • Put-away rules and location confirmation.
  • Traceability through labels, barcodes, lot numbers, and serial numbers.
  • Timely recording of receipts and stock movements.
  Module 4: Storage, Stock Rotation, and Replenishment  
  • Storage discipline and location integrity.
  • FIFO and FEFO principles, applications, and limitations.
  • Batch, lot, and expiry-date management.
  • Controls for slow-moving, obsolete, damaged, and expired stock.
  • Replenishment of picking locations.
  • Supervision and review of stock rotation compliance.
    Day 2: Order Fulfillment and Inventory Accuracy Module 5: Picking Strategies and Order Fulfillment  
  • Discrete, batch, zone, and wave picking.
  • Selecting picking strategies for different order profiles.
  • Pick paths, location sequencing, and travel reduction.
  • Replenishment coordination and stock availability.
  • Picking verification and error prevention.
  • Packing, staging, and dispatch confirmation.
  • Handling short picks, substitutions, cancellations, and returns.
  Module 6: Inventory Records and Accuracy Controls  
  • Item master data, units of measure, and location records.
  • On-hand, available, allocated, and quarantined stock.
  • Transaction controls for receipts, transfers, issues, returns, and adjustments.
  • Common causes of physical and system stock mismatches.
  • Barcode scanning and WMS control points.
  • Inventory reconciliation and supporting documentation.
  • Measuring inventory accuracy and interpreting discrepancies.
  Module 7: Cycle Counting and Physical Inventory  
  • Cycle counting versus full physical inventory.
  • ABC classification and risk-based count priorities.
  • Count frequency based on value, movement, and discrepancy history.
  • Count preparation, blind counting, and movement controls.
  • Recounts, variance investigation, and adjustment approval.
  • Root cause analysis and corrective action follow-up.
  • Reviewing the effectiveness of the counting program.
  Module 8: Shrinkage Reduction and Inventory Protection  
  • Sources of shrinkage: loss, damage, theft, misplacement, and recording errors.
  • Access controls and accountability for stock movements.
  • Controls for high-value and sensitive inventory.
  • Returns, write-offs, scrap, and disposal controls.
  • Exception reporting and unusual transaction patterns.
  • Investigating recurring losses and unexplained adjustments.
  • Preventive and detective controls for shrinkage reduction.
    Day 3: Performance Management, Process Review, and Improvement Module 9: Warehouse Productivity and Inventory KPIs  
  • Receiving productivity and dock-to-stock time.
  • Put-away productivity and replenishment performance.
  • Picking productivity and order accuracy.
  • Inventory accuracy and cycle count variance.
  • Space utilization and storage capacity.
  • Shrinkage, damage, and expiry indicators.
  • Defining KPI formulas, data sources, and reporting boundaries.
  • Interpreting trends while balancing speed, accuracy, and service.
      Module 10: Supervising and Auditing Warehouse Processes  
  • Process mapping and identification of critical control points.
  • Reviewing procedures against actual warehouse practices.
  • Tracing transactions from documents to systems and physical stock.
  • Reviewing approvals, access rights, and segregation of duties.
  • Identifying control gaps and recurring process exceptions.
  • Documenting findings with clear supporting evidence.
  • Prioritizing corrective actions and tracking closure.
  Module 11: Warehouse Improvement Planning  
  • Identifying bottlenecks, unnecessary movement, and rework.
  • Improving layout, slotting, and picking arrangements.
  • Addressing inventory discrepancy root causes.
  • Standardizing transaction recording and exception handling.
  • Assigning improvement owners and measurable targets.
  • Monitoring results and sustaining operational improvements.
  Module 12: Capstone — Warehouse Operations and Inventory Improvement Plan  
  • Review a warehouse scenario containing layout, transaction, inventory, and performance information.
  • Identify weaknesses across receiving, put-away, storage, picking, and dispatch.
  • Recommend appropriate FIFO or FEFO controls.
  • Develop a cycle counting and inventory reconciliation plan.
  • Propose controls to reduce shrinkage and improve traceability.
  • Select relevant KPIs and define their calculation and reporting requirements.
  • Produce a prioritized improvement plan with responsibilities and expected outcomes.
 

This course develops the foundational knowledge and practical skills needed to configure, administer, and maintain the ServiceNow platform. Participants explore platform navigation, instance configuration, application collaboration, self-service, automation, database management, security, and configuration migration. The proposed five-day duration accommodates foundational learning, configuration activities, and an integrated capstone. Duration 5 Days – 35 hrs.   Objectives...

Duration: 5 days – 35 hrs   Overview The “SOC Network and Threat Detection and Analysis” training course is designed to equip Security Operations Center (SOC) analysts and IT security professionals with the skills and knowledge required to detect, analyze, and respond to network threats effectively. This comprehensive course covers essential topics such as threat...

Duration 1 day – 7 hrs   Overview   This 1-day training builds upon basic warehouse operations knowledge and introduces key logistics concepts involved in the movement and coordination of goods—especially wet and dry food items—within and outside the warehouse. Participants will explore transport logistics, inbound and outbound coordination, documentation practices, and cold chain considerations,...

Duration 2 days – 14 hrs   Overview   This hands-on course provides an introduction to Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data. The training focuses on how developers and QA professionals can leverage Splunk to gain insights from logs and metrics, improve application observability, detect anomalies, and support test validation....

Duration 3 days – 21 hrs   Overview.   This course is designed for fresh graduates aspiring to build a career in Data Science. It introduces the fundamentals of data science, focusing on data analysis, visualization, and basic machine learning concepts using Python. The course provides hands-on practice with real-world datasets, equipping participants with the...

// BG EARTH WHEN NOT PLAYING

We use cookies on our website to personalize your experience by storing your preferences and recognizing repeat visits. By clicking “Accept”, you agree to the use of all cookies. You can also select “Cookie Settings” to adjust your preferences and provide more specific consent. Cookie Policy