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Cohort 014 · Software Testing & AI Agents · Enrolling Now

Software Testing
+ AI Agents

Master end-to-end Software Testing and AI Agents with real-world, job-ready implementation skills. Build foundations in Python and SQL, ship pipelines with PySpark and Databricks, scale on Microsoft Fabric, and integrate Generative + Agentic AI into production data workflows.

3mo
duration
30+
modules
4.7/5
cohort rating
100k+
enrolled
Where our Software Testing alumni work
MicrosoftAmazonSalesforceAI EngineerDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL MicrosoftAmazonSalesforceAI EngineerDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL
What you leave with

Four things every Software Testing grad walks away with.

Most programs stop at tools. Ours makes you ship pipelines, platforms, and AI-powered data products that hiring teams can verify.

01
Agent-Ready skills
Build, deploy, and monitor AI agents that run production workflows — not chatbot toys.
02
A shipped capstone
A live React + FastAPI + LangGraph app on Kubernetes, monitored, observable, public URL.
03
Verifiable credential
2026 Agent-Ready rubric, graded 1–5 with a public verification URL recruiters can check.
04
Direct placement pipeline
GitHub + LinkedIn rewrite, resume rebuild, and warm intros to our 1,000+ hiring partners.
3 months, four phases

From "loads CSVs" to ships AI-native data pipelines.

Weeks 1–3 build Python and SQL depth. Weeks 4–7 cover Power BI and data storytelling. Weeks 8–10 move into PySpark, Databricks, and Fabric. Weeks 11–12 ship Generative + Agentic AI data agents.

WEEKS 1–3 · FOUNDATIONS

Python + SQL for Software Testing

  • Python data structures, iterators, OOP
  • PostgreSQL querying, joins, windows, CTEs
  • Database design, indexing, optimization
  • Data file formats and transformation patterns
YOU SHIPA Python + SQL ingestion and transformation workflow over production-like datasets.
WEEKS 4–7 · ANALYTICS

Power BI and business intelligence

  • Power Query and source integrations
  • Star schema modeling and DAX measures
  • Advanced visuals, storytelling, KPI dashboards
  • Publishing, sharing, governance, refresh
YOU SHIPA complete Power BI reporting suite consumed by business teams and leaders.
WEEKS 8–10 · DATA PLATFORM

PySpark, Databricks, and Microsoft Fabric

  • Spark DataFrames, joins, windows, optimization
  • Databricks workflows, Delta Lake, Unity Catalog
  • Fabric OneLake, Lakehouse, Warehouse, RTI
  • Streaming, orchestration, and governance
YOU SHIPAn enterprise-grade ELT platform with scheduled jobs, observability, and governed data products.
WEEKS 11–12 · GENERATIVE + AGENTIC AI

Deploy AI agents that automate analytics, retrieval, and reporting across your data platform.

Use LLM APIs, LangChain, RAG, and LangGraph workflows with persistence and HITL. Add MCP tool access and enterprise guardrails. Your capstone connects pipelines, dashboards, and AI agents into a single production-ready data intelligence system.

Partner orgs (2026)48
Capstones deployed280+
→ Placement offers82%
Course curriculum

Seven sections. 65+ modules. The AI-native Software Testing stack.

Jump to any section on the left. Click a module to see topics, hands-on lab, and key technologies.

01

Fundamentals of IT & AI

How modern apps work, how teams ship them with Agile, where compute & cloud fit, and how AI plugs into the 2026 stack.
10 MODULES
WEEK 1
Key Topics: What is an Application Types of Applications Web Application Fundamentals Web Technologies: Frontend (HTML, CSS, JavaScript, React) Web Technologies: Backend (Python, Java, Node.js) Web Technologies: Databases (SQL: MySQL, PostgreSQL; NoSQL: MongoDB) Software Development Life Cycle (SDLC) SDLC Phases: Planning, Analysis, Design, Implementation, Testing, Deployment, Maintenance
Key Topics : Waterfall vs. Agile Methodologies The Agile Mindset Popular Agile Frameworks Scrum Overview & Pillars Scrum Roles (Product Owner, Scrum Master, Dev Team) Scrum Events (Sprint, Planning, Daily Scrum, Review, Retrospective) Scrum Artifacts (Product Backlog, Sprint Backlog, Increment) Writing User Stories Epics and Themes Acceptance Criteria Estimating User Stories Managing Backlogs Tools: Google Sheets, Azure Boards
Key Topics : The Importance of Computing Power Key Computing Technologies: CPU (Central Processing Unit) Key Computing Technologies: GPU (Graphics Processing Unit) Introduction to Cloud Computing Cloud Service Models: IaaS (Infrastructure as a Service) Cloud Service Models: PaaS (Platform as a Service) Cloud Service Models: SaaS (Software as a Service)
Key Topics : What is Artificial Intelligence (AI)? How AI Works? Machine Learning (ML) Fundamentals Deep Learning (DL) Fundamentals What is Generative AI? Large Language Models (LLMs) Image Generation Models AI in Everyday Learning
Key Topics : Customer Relationship Management (CRM) Human Resource Management Systems (HRMS) Retail & E-Commerce Applications Healthcare Applications
02

Manual Testing

Modern React with hooks, Redux Toolkit and routing, paired with PostgreSQL fundamentals through query optimization.
10 MODULES
WEEKS 2–4
Key Topics : What is Software & Types of Software (System, Programming, Application) Software Applications (Desktop, Web, Mobile) What is Software Testing & Why Testing is Important Real-world Testing Failures (Therac-25, Mars Climate Orbiter, Boeing 737 MAX) Software Development Life Cycle (SDLC) - Overview Quality, QA vs QC Errors, Bugs, Defects & Failures Software Testing Life Cycle (STLC) - Introduction
Key Topics : SDLC Models Overview Waterfall Model (Phases, Advantages, Disadvantages, When to Use) V-Model (Verification & Validation Model) BRS & SRS Documents HLD & LLD Documents Static Testing (Review, Walkthrough, Inspection) Comparison of SDLC Models White Box, Black Box & Grey Box Testing When to use each testing approach
Key Topics : Unit Testing Concept & Responsibility Unit Testing Techniques (Basis Path, Conditional Coverage, Loop Coverage) Unit Testing Frameworks (JUnit, NUnit, pytest) Integration Testing Purpose & Importance Integration Testing Types: Incremental (Top-Down, Bottom-Up, Sandwich/Hybrid) Non-Incremental (Big Bang) Stubs & Drivers Developer's Role in Testing
Key Topics : System Testing Overview Functional vs Non-Functional Testing GUI Testing Visual Design Verification Functional Elements Testing Content & Interaction Verification Usability Testing User-friendliness Assessment User Satisfaction Metrics User Acceptance Testing (UAT) Alpha Testing Beta Testing
Key Topics : Object Properties Testing Database Testing (SQL Basics for Testers) CRUD Operations Validation Data Integrity Testing Error Handling Testing Calculations/Computations Testing Links Testing (Internal, External, Anchor, Email) Cookie Testing Session Testing Practical Examples & Scenarios
Key Topics : Performance Testing Load Testing Stress Testing Spike Testing Endurance/Soak Testing Volume Testing Scalability Testing Security Testing (Authentication, Authorization, Encryption) Recovery Testing Compatibility Testing (Hardware, OS, Browser) Installation Testing (Fresh, Upgrade, Uninstall, Reinstall) Garbage Testing
Key Topics : Regression Testing (Unit, Regional, Full) Retesting vs Regression Testing Smoke Testing (Build Verification Testing) Sanity Testing Exploratory Testing Ad-Hoc Testing Monkey Testing Positive Testing vs Negative Testing Globalization Testing Localization Testing Severity vs Priority
Key Topics : Equivalence Class Partitioning (ECP) Valid & Invalid Equivalence Classes Practical Examples Boundary Value Analysis (BVA) Boundary Values & Conditions Test Case Creation Decision Table Testing Conditions, Actions & Rules Complex Business Logic Testing State Transition Testing States, Events, Transitions State Transition Diagrams & Tables Error Guessing (Experience-based Testing)
Key Topics : Software Testing Life Cycle (STLC) Phases Requirement Analysis Test Planning Test Case Development Test Environment Setup Test Execution Test Closure Test Plan (Contents, Creation, Sample) Use Case, Test Scenario & Test Case Understanding the Differences Use Case Components (Actor, Action, Goal) Test Case Design & Documentation Test Case Components & Format Test Data Management Writing Effective Test Cases Requirement Traceability Matrix (RTM) Defect/Bug Life Cycle & Reporting
Key Topics : Agile Methodology Agile Principles & Values Advantages & Disadvantages Agile Frameworks Overview Scrum Framework Scrum Roles (Product Owner, Scrum Master, Development Team) Scrum Artifacts (Product Backlog, Sprint Backlog, Increment) Scrum Events (Sprint, Sprint Planning, Daily Scrum, Sprint Review, Sprint Retrospective) Burndown/Burnup Charts Testing in Agile Environment JIRA for Test Management Creating Test Cases in JIRA Bug Tracking & Reporting Sprint Management Version Control System (GitHub Basics) Real Project Execution Interview Preparation & Resume Building
03

Automation Testing

Python from fundamentals through OOP, then FastAPI — async APIs with Pydantic validation, SQLAlchemy, and JWT auth.
15 MODULES
WEEKS 5–8
Key Topics : What is Automation Testing? Benefits of Automation Testing (Speed, Reusability, Cost-Effectiveness) When to Automate vs Manual Testing Automation Testing Pyramid (Unit, Integration, E2E) Introduction to Selenium WebDriver Selenium Architecture & Components Selenium vs Other Tools (Playwright, Cypress, Appium) Setting Up Selenium Environment Installing Java/Python & IDE (Eclipse, IntelliJ, VS Code) Selenium WebDriver Installation & Configuration Browser Drivers (ChromeDriver, GeckoDriver, EdgeDriver) Writing Your First Selenium Script Locating Elements: ID, Name, Class Name CSS Selectors (Basic & Advanced) XPath (Absolute & Relative) Link Text, Partial Link Text Tag Name WebDriver Commands: Navigation (get, navigate, refresh, back, forward) Browser Commands (maximize, minimize, fullscreen) Getting Page Information (title, currentUrl, pageSource) WebElement Commands: Click, SendKeys, Clear getText, getAttribute, getCssValue isDisplayed, isEnabled, isSelected Handling Different Web Elements: Text Boxes, Buttons, Links Radio Buttons & Checkboxes Dropdowns (Select Class) Multi-Select Dropdowns
Key Topics : Waits in Selenium: Implicit Wait Explicit Wait (WebDriverWait) Fluent Wait Custom Expected Conditions Handling Complex UI Elements: Alerts & Pop-ups (accept, dismiss, getText, sendKeys) Multiple Windows & Tabs (getWindowHandles, switchTo) iFrames (switchTo.frame, switchTo.defaultContent) Shadow DOM Elements Dynamic Elements & AJAX Calls Mouse & Keyboard Actions: Actions Class (moveToElement, clickAndHold, dragAndDrop) Right Click (contextClick) Double Click (doubleClick) Keyboard Actions (keyDown, keyUp, sendKeys) Taking Screenshots: Full Page Screenshots Element Screenshots Screenshots on Test Failure Handling JavaScript: JavaScriptExecutor Interface Executing JavaScript Commands Scrolling (scrollIntoView, scroll by pixels) Handling Hidden Elements File Upload & Download: File Upload (sendKeys, Robot Class, AutoIT) File Download Verification Cookies Management: addCookie, getCookies, deleteCookie, deleteAllCookies Browser Logs & Network Monitoring Test Automation Framework: Framework Types (Data-Driven, Keyword-Driven, Hybrid, BDD) Page Object Model (POM) Design Pattern Page Factory Pattern Creating Base Classes Utility Classes (Excel, Properties, Screenshots) TestNG Framework: Annotations (@Test, @BeforeMethod, @AfterMethod, etc.) Test Configuration (testng.xml) Assertions (Hard vs Soft Assertions) Parameterization & Data Providers Grouping Tests Parallel Execution Test Listeners & Reporting Data-Driven Testing: Reading from Excel (Apache POI) Reading from CSV, JSON, XML Database Connectivity (JDBC)
Key Topics : Introduction to Playwright Why Playwright in 2026? (Speed, Reliability, Multi-Browser) Playwright vs Selenium: Key Differences Playwright Architecture & Features: Auto-Waiting Mechanism Network Interception Multi-Tab & Multi-Context Support Built-in Test Runner AI-Powered Self-Healing Locators Setting Up Playwright: Installation (Node.js, Python, Java, .NET) Playwright Configuration (playwright.config.js/ts) Browser Installation VS Code Extension Writing Playwright Tests: Test Structure (@playwright/test) Page Object Model in Playwright Fixtures & Hooks (beforeEach, afterEach) Locators in Playwright: Role-Based Locators (getByRole) Text-Based Locators (getByText, getByLabel) Test ID Locators (getByTestId) CSS & XPath Selectors Chaining Locators Smart Locators (Auto-Retry) Actions & Assertions: Click, Fill, Type, Check, Select expect() Assertions (toBeVisible, toHaveText, toContainText) Auto-Waiting Assertions Soft Assertions Advanced Playwright Features: Handling Multiple Pages & Contexts Network Mocking & API Interception Route Handling (route.fulfill, route.abort) File Upload & Download Geolocation & Permissions Browser Context Isolation Playwright Inspector & Debugging: Codegen (Test Generator) Playwright Inspector Trace Viewer (Detailed Execution Trace) Screenshots & Videos on Failure Debug Mode (PWDEBUG=1) Cross-Browser Testing: Chromium, Firefox, WebKit Mobile Emulation (iPhone, Android) Device Descriptors Responsive Testing Playwright Test Runner: Configuration & Projects Parallel Execution & Sharding Test Retry Strategy Reporters (HTML, JSON, JUnit) Test Annotations & Tags
Key Topics : AI in Test Automation (2026 Trends): Self-Healing Tests AI-Powered Test Generation Visual AI Testing Intelligent Test Maintenance Selenium with AI: Healenium (Self-Healing Locators) AI4Selenium Framework OpenCV for Visual Testing Integrating AI Libraries Playwright AI Features: Smart Locators with Auto-Retry AI Test Generation Tools Visual Comparison Testing Headless & Headed Execution: Headless Browser Testing (Benefits & Use Cases) Headed Mode for Debugging Docker Containers for Testing Cross-Browser & Cross-Platform Testing: Browser Compatibility Testing Cloud-Based Testing (BrowserStack, Sauce Labs, LambdaTest) Device Farms & Real Device Testing Responsive Design Testing Visual Testing & Screenshot Comparison: Pixel-by-Pixel Comparison Percy, Applitools Integration Visual Regression Testing Handling Dynamic Content Performance Testing in Automation: Page Load Time Measurement Lighthouse Integration Performance Metrics (FCP, LCP, TTI) Network Throttling
Key Topics : Version Control with Git: Git Basics (clone, commit, push, pull) Branching Strategies .gitignore for Test Projects GitHub Continuous Integration/Continuous Deployment: Introduction to CI/CD GitHub Actions: Workflow Configuration Running Tests on Push/PR Matrix Strategy (Multi-Browser) Artifacts & Reports Azure DevOps Pipelines Docker for Test Automation: Docker Basics Selenium Grid with Docker Playwright Docker Images Docker Compose for Multi-Container Setup Test Reporting & Dashboards: Allure Reports (Installation & Configuration) Extent Reports Custom HTML Reports Test Result Dashboards Email Notifications Test Management Integration: JIRA/Zephyr Integration TestRail Integration Linking Test Cases to Requirements Defect Tracking Automation Best Practices for Automation Testing: Test Design Principles Naming Conventions Code Reusability & Modularity Avoiding Test Flakiness Test Data Management Parallel Execution Strategies Test Maintenance & Refactoring Logging & Debugging Common Challenges & Solutions: Handling Flaky Tests StaleElementReferenceException TimeoutException NoSuchElementException Dynamic Locators Test Execution Speed Optimization
04

API Testing

Production Software Testing : Power BI for analytics, then Microsoft Fabric — OneLake, Lakehouse medallion architecture, Spark, real-time intelligence, and Copilot.
25 MODULES
WEEKS 9–14
Key Topics : Introduction to APIs (Application Programming Interfaces) What is an API? Types of APIs (Web APIs, Library APIs, OS APIs) Why API Testing is Important? API Testing vs UI Testing Benefits of API Testing (Speed, Reliability, Early Detection) API Architecture Styles: REST (Representational State Transfer) SOAP (Simple Object Access Protocol) GraphQL RESTful API Concepts: Resources & Endpoints HTTP Methods: GET (Retrieve Data) POST (Create Data) PUT (Update/Replace Data) PATCH (Partial Update) DELETE (Remove Data) HEAD, OPTIONS HTTP Status Codes: 1xx (Informational) 2xx (Success: 200, 201, 204) 3xx (Redirection: 301, 302) 4xx (Client Errors: 400, 401, 403, 404) 5xx (Server Errors: 500, 502, 503) Request Components: URL/URI Structure Headers (Content-Type, Authorization, Accept) Query Parameters Path Parameters Request Body (JSON, XML, Form Data) Response Components: Status Code Headers Response Body (JSON, XML, HTML) Cookies JSON (JavaScript Object Notation): JSON Syntax & Structure Objects, Arrays, Key-Value Pairs Data Types (String, Number, Boolean, Null) Nested JSON Objects JSON Path Expressions XML Basics: XML Structure & Syntax Elements, Attributes, Tags XPath Expressions API Documentation: Reading API Documentation Swagger/OpenAPI Specification API Contracts
Key Topics : Introduction to Postman Installing Postman (Desktop & Web) Postman Interface Overview: Workspace, Collections, Environments Request Builder Response Viewer Creating API Requests: GET Requests POST Requests with Body (JSON, XML, Form Data) PUT & PATCH Requests DELETE Requests Setting Headers Query & Path Parameters Understanding Responses: Response Status, Time, Size Response Body (Pretty, Raw, Preview) Response Headers Cookies Collections & Folders: Creating Collections Organizing Requests in Folders Running Collections Collection Runner Sharing Collections Variables in Postman: Global Variables Environment Variables Collection Variables Local Variables Dynamic Variables ($guid, $timestamp, $randomInt) Pre-request Scripts: JavaScript in Postman Setting Variables Dynamically Generating Random Data Date & Time Manipulation Tests & Assertions: Writing Tests in Postman Chai Assertion Library Status Code Assertions Response Time Assertions Response Body Validation: Checking JSON Properties Array Length Validation Schema Validation Header Validation pm.expect() Assertions Data-Driven Testing: Using CSV Files Using JSON Files Iterating Through Test Data Authentication in Postman: No Auth API Key Bearer Token Basic Auth OAuth 1.0 & 2.0 Digest Auth JWT (JSON Web Token) Postman Mock Servers: Creating Mock Servers Using Mock Responses Testing Without Backend Postman Monitors: Scheduled API Testing Monitoring API Health Email Notifications
Key Topics : Introduction to API Test Automation Requests Library (Python): Installing Requests Library Making HTTP Requests (get, post, put, patch, delete) Passing Parameters & Headers Request Body (JSON, Form Data) Response Object: status_code, text, json(), headers, cookies Response Time (elapsed) Session Objects Authentication (auth parameter) File Upload & Download SSL Certificate Verification Pytest for API Testing: Pytest Installation & Setup Writing Test Functions Assertions (assert) Fixtures (setup, teardown) Parameterization (@pytest.mark.parametrize) Test Organization HTML Reports (pytest-html) Framework Design: Project Structure Config Files Utility Functions Test Data Management Logging Reporting
Key Topics : API Chaining: Dependent API Calls Extracting Data from Response Using Response Data in Next Request Database Testing with APIs: Database Connectivity (JDBC, PyMySQL) Validating API Response with Database Data Integrity Testing API Performance Testing: Introduction to Performance Testing Key Metrics (Response Time, Throughput, Latency) Load Testing with JMeter Stress Testing Spike Testing Endurance Testing API Security Testing: Authentication & Authorization Testing SQL Injection Testing XSS (Cross-Site Scripting) Testing HTTPS & SSL/TLS Validation API Key Security Rate Limiting Testing OWASP API Security Top 10: Broken Object Level Authorization Broken User Authentication Excessive Data Exposure Lack of Resources & Rate Limiting Security Misconfiguration Contract Testing: What is Contract Testing? Consumer-Driven Contracts Pact Framework Provider & Consumer Testing GraphQL API Testing: Introduction to GraphQL GraphQL vs REST GraphQL Concepts: Queries (Fetching Data) Mutations (Modifying Data) Subscriptions (Real-time Updates) Schema & Types Resolvers GraphQL Queries: Fields & Arguments Aliases & Fragments Variables & Directives Nested Queries Testing GraphQL APIs: Using Postman for GraphQL Automating GraphQL Tests Schema Validation Error Handling SOAP API Testing: Introduction to SOAP WSDL (Web Services Description Language) SOAP Request Structure (Envelope, Header, Body) Testing SOAP APIs with SoapUI SOAP API Automation Microservices Testing: Introduction to Microservices Testing Strategies for Microservices Service Virtualization Testing with Docker Containers
Key Topics : API Test Automation Framework: Hybrid Framework Design Folder Structure Configuration Management Environment Management (Dev, QA, Staging, Prod) Test Data Management Utility Classes Logging & Reporting CI/CD Integration: GitHub Actions: Workflow for API Tests Running Tests on Push/PR Environment Secrets Azure DevOps Pipelines API Mocking & Virtualization: Why Mock APIs? Creating Mock Servers WireMock (Java) Mock Server (Node.js) Using Postman Mock Servers Service Virtualization Tools Test Reporting: Allure Reports Extent Reports Custom HTML Reports Test Result Dashboards API Testing Best Practices: Test Case Design Positive & Negative Testing Boundary Value Testing Error Handling Testing Test Data Independence Reusability & Maintainability Clear Test Naming Assertions Best Practices Avoiding Hard-Coded Values Environment Configuration API Documentation Testing: Validating Swagger/OpenAPI Spec Documentation Accuracy Example Validation Monitoring & Observability: API Monitoring Tools Health Check Endpoints Logging & Error Tracking APM (Application Performance Monitoring) Common API Testing Challenges: Authentication Issues Data Dependencies Environment Differences API Versioning Response Time Variations Rate Limiting Interview Preparation: API Testing Interview Questions REST Assured Interview Questions Postman Interview Questions GraphQL Interview Questions Coding Challenges Resume Building for API Testers
05

SQL for AI & Testing

The mathematical backbone behind every ML and DL model: linear algebra, probability, distributions, hypothesis testing, and applied statistics for ML.
5 MODULES
WEEK 15
Introduction to Databases & DBMS Relational Database Management Systems (RDBMS) ACID Properties (Atomicity, Consistency, Isolation, Durability) Introduction to PostgreSQL PostgreSQL Installation & Setup (Windows, Mac, Linux) PostgreSQL Tools: psql, pgAdmin 4 Database Objects (Databases, Schemas, Tables) Data Types: Numeric, Character, Date/Time, Boolean, Special types Constraints: PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, CHECK, DEFAULT Creating Databases and Tables INSERT Operations and Data Population Referential Integrity
SELECT Statement Basics Column Aliases and Expressions WHERE Clause and Filtering Comparison Operators (=, !=, >, <,>=, <=) - Logical Operators (AND, OR, NOT) - BETWEEN, IN, LIKE operators - NULL handling (IS NULL, IS NOT NULL) - ORDER BY (Sorting data) - DISTINCT (Removing duplicates) - LIMIT and OFFSET (Pagination) - String Functions (UPPER, LOWER, CONCAT, SUBSTRING, etc.) - Numeric Functions (ROUND, CEIL, FLOOR, ABS, etc.) - Date and Time Functions (CURRENT_DATE, EXTRACT, DATE_TRUNC, etc.) - Aggregate Functions (COUNT, SUM, AVG, MIN, MAX) - GROUP BY and HAVING Window Functions (ROW_NUMBER, RANK, LAG, LEAD, etc.) - JOIN Operations: - INNER JOIN - LEFT JOIN / RIGHT JOIN - FULL OUTER JOIN - CROSS JOIN - SELF JOIN - Multi-table Joins - Join Optimization
Subqueries in WHERE, SELECT, FROM clauses Correlated Subqueries EXISTS and NOT EXISTS IN and NOT IN with subqueries Common Table Expressions (CTEs) Recursive CTEs for hierarchical data Multiple CTEs Set Operators: UNION and UNION ALL INTERSECT EXCEPT UPDATE Statements UPDATE with expressions UPDATE with JOIN DELETE Statements DELETE with subqueries TRUNCATE vs DELETE Transaction Management BEGIN, COMMIT, ROLLBACK Savepoints Transaction Isolation Levels Concurrency Control
ALTER TABLE Operations Adding, Modifying, Dropping Columns Managing Constraints Indexes and Performance Index Types (B-tree, Hash, GIN, GiST) Creating and Managing Indexes When to use indexes Views and Abstraction Creating Views Updatable Views Materialized Views Refreshing Materialized Views Stored Functions PL/pgSQL Programming Language Function Parameters and Return Types Control Structures (IF, CASE, LOOP) Functions Returning Tables Stored Procedures Procedure vs Function differences Exception Handling in PL/pgSQL Triggers BEFORE, AFTER, INSTEAD OF triggers Trigger Functions Audit Logging with Triggers Data Validation with Triggers Advisory Locks
Entity-Relationship (ER) Modeling Entities, Attributes, Relationships Relationship Types (1:1, 1:M, M:N) ER Diagrams Normalization Principles First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF) Normalization Benefits and Trade-offs When to Denormalize Database Design Best Practices Naming Conventions Data Type Selection Primary Key Strategies Foreign Key Design Query Optimization EXPLAIN and EXPLAIN ANALYZE Reading Execution Plans Index Strategies Query Rewriting Techniques Performance Tuning Database Statistics (ANALYZE) VACUUM and Maintenance Connection Pooling Table Partitioning
06

Generative AI & Agentic AI

The mathematical backbone behind every ML and DL model: linear algebra, probability, distributions, hypothesis testing, and applied statistics for ML.
5 MODULES
WEEK 15
Topics: Large Language Models fundamentals Transformer architecture Comparing major LLMs (GPT, Claude, Gemini, DeepSeek) Evolution of LLMs from GPT-1 to 2026 frontier models LLM architecture and tokenization Model selection for different use cases Cost optimization strategies
Topics: Advanced prompt engineering techniques Context engineering and design Reasoning mode optimization Reducing hallucinations Zero-shot, few-shot, and chain-of-thought prompting Multimodal prompting (text, image, audio) Domain-specific prompt design
Topics: OpenAI, Anthropic, Google, and DeepSeek APIs LangChain 1.0 fundamentals Create_agent abstraction Middleware systems for customization Multi-provider integration Streaming and batching Function calling and structured outputs Cost-optimized pipelines
Topics: Vector databases (ChromaDB, Pinecone, Qdrant) Building production RAG pipelines Agentic RAG and self-improving retrieval MCP-Enhanced RAG Embedding strategies Hybrid search (semantic and keyword) Document processing at scale Hallucination reduction techniques
Topics: Streamlit and Gradio interfaces LangGraph Platform deployment Cost optimization strategies AI governance and EU AI Act compliance API security and rate limiting Monitoring and observability Scaling strategies Integration with enterprise tools
Topics: Agentic AI fundamentals (plan, reason, act) LangChain 1.0 Agents with middleware Model Context Protocol (MCP) Tool integration patterns Enterprise adoption and use cases Agent architectures and design patterns
Topics: LangGraph 1.0 architecture State management and graph-based logic Node caching for development Pre/Post hooks for guardrails Building AI workflows Production use cases
Topics: Parallel execution with deferred nodes Conditional routing and decision trees Iterative refinement loops Type-safe streaming Essay evaluation systems Customer feedback routing Multi-stage approval workflows Quality-gated content generation
Topics: Durable state management Built-in persistence (PostgreSQL, Redis) Human-in-the-loop (HITL) implementations Multi-day workflow support Enterprise compliance and audit trails Restart and failure recovery
Topics: LangGraph Platform deployment Multi-agent system design Google A2A Protocol for agent-to-agent communication LangSmith observability and monitoring MCP security model Prompt injection prevention Compliance and audit trails Agent guardrails and safety
Tools you'll master

40+ tools, one production capstone.

Not a shallow tour. You'll use every one of these in at least one graded exercise.

R
React 18
RT
Redux Toolkit
TS
TypeScript
V
Vite
Nd
Node.js
Py
Python
FA
FastAPI
SA
SQLAlchemy
Pg
PostgreSQL
M
MongoDB
PB
Power BI
MF
MS Fabric
Np
NumPy
Pd
Pandas
Sk
scikit-learn
TF
TensorFlow
PT
PyTorch
HF
Hugging Face
SM
spaCy
OAI
OpenAI
LC
LangChain
LG
LangGraph
LS
LangSmith
MC
MCP
VD
Vector DBs
D
Docker
K
Kubernetes
G
Git
GH
GitHub
aws
AWS
Az
Azure
C
Cursor AI
Real-time projects

You don't watch videos. You ship software.

Three full-production projects, each threaded through the entire curriculum. By the capstone, you've built the whole stack around them.

Hero project · weeks 3–12

LMS analytics platform

Ingest learner events, build transformation layers, and publish executive and academic dashboards with AI-generated insight summaries.

PySparkDatabricksPower BILangGraphPostgreSQL
View project →
Enterprise · weeks 6–11

HRMS data pipeline

Build secure ETL workflows for employee, payroll, and performance datasets with governed semantic models and decision-ready KPIs.

MS FabricDelta LakePower BIUnity Catalog
Real-time · weeks 8–12

CRM intelligence stream

Create near real-time customer analytics with streaming events, automated anomaly flags, and AI-assisted executive reporting.

Structured StreamingKQLPower BILangChain
Capstone · weeks 11–12

Your AI Software Testing agent in a real partner org.

Pick a real partner data problem. Deploy a production data pipeline and an AI agent that explains metrics, detects risks, and accelerates business decisions.

2026: 220+ deployed76% → placement offers
See capstone gallery →
Your instructor

Taught by engineers who shipped agentic AI to production.

Not a career trainer. A practitioner who still ships code.

AS
Aarav Sharma
Lead Instructor · Software Testing & AI
React · FastAPI · PyTorch · LangChain
"A 2026 full-stack engineer doesn't stop at React + an API. They train the model, deploy it behind FastAPI, wrap it in an agent, and ship the whole thing to a real org. That's what we build, every cohort."
10 yrs
FULL STACK
2,400+
LEARNERS
4.9 /5
RATING

Aarav started as a React engineer at an Indian unicorn before leading platform teams across three continents. He's shipped React + FastAPI products for a healthcare network with 80M users, trained NLP classifiers in production for a top-3 bank, and — most recently — deployed the first LangGraph agent into a Fortune-500 insurer's claims pipeline.

His cohorts get two things other programs don't give you: a real engineer who still ships code, and a curriculum rewritten every quarter to match what hiring managers actually ask about.

FAQ

Questions we actually get — answered honestly.

If the answer you need isn't here, book a 20-minute advisor call. No-slides, no-pitch — just your questions.

No. About 40% of our Software Testing cohort comes from non-CS backgrounds — mechanical, electrical, and commerce. The first phase is foundations by design. What you need: consistency and around 12–15 hours/week.
Plan for 12–15 hours: 2 live classes × 2 hours, 1 lab × 3 hours, and roughly 5 hours of asynchronous project work. Weekends are optional office hours with the TA team.
Yes. Every student gets a dedicated placement advisor from week 8 onwards — not a helpdesk. They review your resume, redo your LinkedIn, mock-interview you, and make direct warm introductions to our 1,000+ hiring partners. We track individual outcomes, not cohort averages.
Full refund within 7 days of cohort start, no questions. Pro-rata refund through week 4 if the program isn't working for you. We'd rather refund than have an unhappy alum.
You actually build. Sections 6 (ML), 7 (DL/NLP), and 8 (Generative + Agentic AI) are hands-on — you'll train classifiers, build a RAG pipeline, ship a LangGraph workflow, and deploy your capstone agent into a real partner org. Nothing in the AI track is theory-only.
You get the Agent-Ready 2026 credential, graded on a 1–5 band with a public verification URL. It's co-branded with our partner ecosystem (Salesforce Partner + Software Testing), and it names the specific capstone artifact you deployed. Recruiters can verify in 10 seconds.
All three. On-campus at our Hyderabad flagship; online cohorts on IST and PST; weekend cohorts for working professionals. Every format ships the same three projects and the same capstone.
We'd rather pause your cohort than push you through. You can freeze your seat for up to 90 days and rejoin the next cohort without paying again. TAs run catch-up sessions every Saturday for anyone more than one week behind.

Cohort 014 starts 14 May 2026.
40 seats. 12 already claimed.

Book a 20-minute advisor call. We'll walk through the curriculum, match it to your current role, and show you two real capstones from cohort 022.

₹89,000
₹1,20,000
25% off · EARLY BIRD
3 MONTHS · STARTS 14 MAY · 40 SEATS · 12 CLAIMED

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