Industry-based training

You will learn HTML5, CSS3, JavaScript (ES6+), Bootstrap, and TypeScript as listed on the Web tab, then move into React or Angular if that is your track.

Who should join: beginners aiming at frontend roles, and students who need a site they can host and explain.

Prerequisites: comfort using a computer and a browser. No prior framework is required for fundamentals.

Topics: page structure, layout, responsive CSS, JavaScript events and fetch, Bootstrap components, TypeScript types.

Exercises and project: landing pages, a multi-section site, then a small UI that calls an API.

Tools: a code editor, browser devtools, Git/GitHub as you progress.

Outcomes and careers: frontend intern or junior UI work; a portfolio site. FAQ: yes, this is the base for React and Angular on the same tab.

You will learn hooks and state, routing, Redux or Context, and API integration.

Who / prerequisites: people who already understand JavaScript functions and arrays. Complete frontend fundamentals first if you do not.

Topics, exercises, project: component trees, forms, lists, calling REST APIs, a small SPA such as a dashboard or catalogue UI.

Tools: Node.js tooling, React, browser, Postman later for APIs.

Outcomes: React intern/junior UI. Often combined with Node in the MERN track.

Modules and components, services and dependency injection, RxJS, Angular Material — the list already on the Web tab.

Who / prerequisites: JavaScript plus willingness to use TypeScript. Useful if you aim at MEAN or Ionic (Angular + Ionic).

Project exposure: a multi-view app with services and a Material UI, talking to a Node API when you join full stack.

REST APIs, JWT auth, middleware, and uploads as listed.

Who / prerequisites: JavaScript. You will use Postman to test routes.

Outcomes: backend for MEAN/MERN; internships that need API tickets.

MEAN is MongoDB, Express, Angular, Node.js. MERN replaces Angular with React. Delivery basics add GitHub workflow, API design, Postman, and deployments.

Who should join: learners who want a single project with login, data, and a UI they can demo.

Prerequisites: web fundamentals plus either React or Angular, or take those first.

Project: an authenticated app (for example a portal or operations tracker) with CRUD and a deployed or documented run path.

Careers: full stack intern/junior. Then optional internship.

Ionic: cross-platform UI with Angular + Ionic and native APIs. Android: Kotlin/Java basics, Android Studio, Firebase/SQLite. iOS: iPhone/iPad apps, App Store-oriented delivery, shared product flows.

Who: learners targeting mobile roles or event/field apps. Devidas Events on Projects is an Ionic quotation example from client work, not a classroom clone.

Prerequisites: for Ionic, Angular or web basics. For Android, Java or Kotlin willingness. iOS store accounts are not included as a gift; delivery process is taught.

Project: a forms-and-lists mobile app (quotes, tasks, or catalogue) you can run on a device or emulator.

Python: OOP, Pandas/NumPy intro, scripts. Java: OOP, collections, JDBC. C/C++: memory, pointers, DSA intro.

Who: students whose college syllabus or first job tests these languages. Python also feeds the data and ML tracks.

Prerequisites: none for intro Python/Java beyond logic-level comfort; C/C++ assumes you will work with a compiler.

Outcomes: language confidence for labs, campus tests, and later frameworks — not a fake “language mastery certificate” we do not sell on this page.

Python for data: cleaning, EDA, statistics basics. Visualisation: Power BI, Tableau, Matplotlib as listed.

Who: learners aiming at analyst intern roles or reporting inside a business.

Prerequisites: spreadsheet comfort helps; Python intro if you take the Python-for-data path.

Project: a cleaned dataset and a dashboard or notebook you can explain. Suon also builds analytics dashboards for clients on the software page; training uses practice data, not a client’s private warehouse.

ML: scikit-learn and model evaluation. Deep learning and GenAI: neural nets intro, prompting, and simple LLM apps.

Who: people who already have Python and some data handling.

Honest limit: this is an introduction you can demo, not a research lab claim. Production AI for businesses is quoted on AI Solutions.

Project: a trained baseline model with metrics, or a small LLM-assisted app with a human review step.

Manual: STLC, test cases, bug reports. Automation: Selenium, Cypress/Playwright, API tests in Postman.

Who: learners targeting QA intern/junior roles.

Prerequisites: patience for detail; some HTML/JS helps for UI automation; API testing needs HTTP basics.

Project: a test-case set and an automated smoke pack against a sample app, plus Postman collections.

Careers: manual QA, automation intern. Pair with job assistance when you can explain a bug report and a script.

MySQL: SQL, joins, indexing. MongoDB: CRUD and aggregation. SQL Server: T-SQL, views and backups.

Who: anyone on full stack, Java, or data tracks. Databases are not optional if your project stores records.

Project: a schema or collection design that matches a small app, with queries you can run live in a demo.

Git & GitHub: branches and pull requests. Docker & CI: images, Compose, pipeline basics. AWS fundamentals: EC2, S3, IAM, simple deploys.

Who: learners who already have an app to put somewhere. Cloud is not a first course.

Prerequisites: a project repo. AWS uses concepts and simple deploys; we do not impersonate an AWS partner badge we have not published.

Outcomes: you can explain how your project is versioned and where it runs.