Live flagship programme12 weekends · Live cohort + four-week capstone · 8–10 hours per weekView curriculum
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Flagship programme · Software Engineering

AI-Native Developer Certification

Build production-ready applications with AI-assisted engineering, APIs, cloud and system thinking.

Python or TypeScriptLLM APIsVector databasesGitHubCloudDocker
Speak to a programme advisorView curriculum
12 weekends8–10 hours per weekLive cohort + four-week capstone
No payment on this pageProgramme guidance is captured for relevant follow-up
12 weekendsProgramme duration
Live cohort + four-week capstoneLearning format
8–10 hours per weekExpected effort
₹1,49,999Indicative fee

Demonstration contentPrices, commercial terms, mentor identities, testimonials and outcome claims in this starter build must be approved before launch.

Decision snapshot

Know who this is for and what changes after completion.

Designed for

  • Developers
  • Software engineers
  • Full-stack engineers

Prerequisites

  • Working programming knowledge
  • Experience building at least one application
  • Comfort with Git, APIs and debugging

Practical outcomes

  • Build LLM-enabled features around real product requirements
  • Design retrieval, tool-use and evaluation workflows
  • Integrate models through secure APIs
  • Test, observe and improve AI behaviour
  • Deploy a production-oriented capstone

Career relevance

Roles and capabilities this programme is designed to support.

Role outcomes depend on prior experience, project evidence, market conditions and interview performance.

Target roles

AI Software DeveloperAI Application DeveloperAI Product EngineerAI API & Integration EngineerFull-Stack Engineer

Tools and systems

Python or TypeScriptLLM APIsVector databasesGitHubCloudDockerObservability

Curriculum

A structured path from foundations to production evidence.

Modules are presented at decision level; the final syllabus should be governed through the course CMS.

Module 1

AI-native engineering foundations

  • Model behaviour
  • Prompt and context design
  • Task decomposition
  • Safety boundaries
Module 2

Application and API patterns

  • LLM APIs
  • Streaming
  • Tool use
  • Structured outputs
Module 3

Retrieval and knowledge workflows

  • Embeddings
  • Chunking
  • Vector search
  • Grounding
Module 4

Evaluation and reliability

  • Test sets
  • Quality rubrics
  • Guardrails
  • Failure analysis
Module 5

Cloud, deployment and observability

  • Containers
  • Deployment
  • Logging
  • Cost and latency
Capstone

AI-native product feature

  • Architecture
  • Build
  • Evaluate
  • Deploy and present

Projects and capstone

Build evidence that can be reviewed, explained and improved.

Projects should make decisions, trade-offs, tests and operating context visible.

01

Structured-output API

Define the problem, build the artefact, document decisions and review production readiness.

02

Retrieval-backed assistant

Define the problem, build the artefact, document decisions and review production readiness.

03

Tool-using workflow

Define the problem, build the artefact, document decisions and review production readiness.

04

Production capstone

Define the problem, build the artefact, document decisions and review production readiness.

Learning support

Support is designed around completion, evidence and readiness—not passive attendance.

Live expert instruction
Project review
Technical interview preparation
Eligible placement support

Experts

Sample mentor profiles

Meet mentors

Learner evidence

Concise proof without turning the page into a testimonial wall.

Replace each sample capsule with an approved name, designation, photo and outcome-backed quote.

Verified learner storyAI-native developer learner
Sample

Replace this sample capsule with a verified learner quote and approved photograph before production launch.

Verified learner storyWorking professional
Sample

This component supports a concise quote, designation and optional photo without turning the page into a long testimonial wall.

Role visibility

Related sample jobs

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PD
Sample listing

Frontend Engineer

Pixelcraft Digital

PuneHybrid2–5 years
ReactTypeScriptAccessibilityTesting
₹14L–₹22LView role

Programme thinking

Course-specific articles

Read all articles

Fees and financing

Indicative programme fee: ₹1,49,999

Use this section for approved enrolment amount, payment schedule, financing partners, refund terms and taxes. Commercial values in this build are placeholders until signed off.

View fees and financingRead refund policy
  • Transparent total fee and taxes
  • Approved 0% EMI or financing terms
  • Written refund and cancellation terms
  • No placement guarantee language

Questions

AI-Native Developer FAQs

Concise answers for the decision context of this page.

Is this programme suitable for working professionals?

Yes. The programme format is designed around structured live sessions, guided practice and planned project work. The exact weekly commitment is shown on the programme page.

Do I need prior experience?

Prerequisites differ by track. Foundational programmes accept earlier-stage learners, while advanced and leadership tracks expect relevant engineering experience.

How are learners assessed?

Assessment can include practical reviews, live problem-solving, project milestones, mock interviews and a capstone.

Does the programme include placement support?

Eligible learners receive the services described on the placement-support page. Placement support is not a job guarantee and depends on readiness, role fit and employer requirements.

Can I pay in instalments?

Financing and instalment options can be configured for each cohort. Final terms should be confirmed during admission.

Programme guidance

Decide whether AI-Native Developer fits your next role.

Share your experience, target role and learning objective. The form can be connected to the production CRM endpoint.

Your information is used only to respond to this request and manage relevant follow-up.

When no production endpoint is configured, this preview stores a demo submission in the browser only.

Related events

Learn with a live context around this pathway.

Events connect the curriculum with practitioners, hiring conversations and current role expectations.

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