Nayaro Academy · Learn

Learn to build, properly.

Small batches, a laptop in front of you, and the same toolchain we ship client work on. You leave with projects that are deployed, documented and genuinely yours.

Ask about the next batch See the tracks

FormatIn person · Urlabari, Morang

EquipmentYour own laptop, strongly preferred

Batch size[ADD NUMBER] students

Tracks openWeb Development · Python + AI · Data Analytics

What you get

A serious place to learn, not a computer institute.

The difference is not the syllabus. It is that the people teaching it ship software for paying clients in the same building, using the same tools they are putting in front of you.

LAPTOP PREFERRED

Bring your own machine and set it up properly. You leave with a development environment you understand, not one someone configured for you.

SMALL BATCHES

Batches stay small enough that we know where every student is stuck, in the week they get stuck.

PROJECT-BASED

Every module ends in something that runs. Written exams do not tell you whether you can build.

REAL TOOLS

VS Code, the terminal, Git and GitHub from the early weeks — the same setup we use on paid work.

DEPLOYMENT

Your work goes online. A link you can send to someone, not a folder on a desktop.

PORTFOLIO

You finish with a GitHub profile and projects a hiring manager can open and read.

Course tracks

Three tracks to start with.

These are the courses we are opening first. Batch dates, fees and durations are confirmed before every intake — ask and we will tell you exactly what the next one looks like.

TRACK 01Laptop preferred

Web Development

HTML, CSS and JavaScript properly, then a real framework. Version control, deployment, and a portfolio site that is genuinely your own work.

You start by building pages by hand, so you understand what a framework is doing for you before you use one. By the end you can take a design, build it, put it online, and explain every decision in it.

HTML & CSSResponsive layoutJavaScriptReact basicsGit & GitHubDeployment

What you leave with

A personal portfolio site, live on the internet
Two or three project repositories on GitHub
A working local development setup you configured yourself
The vocabulary to read documentation and get unstuck alone

FormatIn person · Urlabari

LevelBeginner → building

DurationTBD

Next batchTBD

FeeTBD

Ask about this track

TRACK 02Laptop preferred

Python + AI Foundations

Python from the ground up, then the practical side of AI: working with APIs, automating real tasks, and learning where models actually help.

The AI half is deliberately practical. You will call real APIs, handle their failures, and build something that saves an actual hour of work — not a demo that only runs on a slide.

Python fundamentalsFiles & dataAPIsAutomation scriptsAI toolingGit & GitHub

What you leave with

Automation scripts that run on your own machine
A small AI-assisted tool you built and can explain
Comfort reading error messages instead of fearing them
Project repositories on GitHub

FormatIn person · Urlabari

LevelBeginner → building

DurationTBD

Next batchTBD

FeeTBD

Ask about this track

TRACK 03Laptop preferred

Data Analytics

Working with real data — cleaning it, questioning it, and turning it into something a business can act on.

Most of analytics is the unglamorous part: messy data, missing rows, and a question nobody has phrased clearly yet. That is what this track spends its time on, because that is what the job is.

SpreadsheetsSQLPython for dataCleaning & validationVisualisationReporting

What you leave with

An analysis of a real dataset, start to finish
A dashboard or report someone could act on
SQL you can write without a tutorial open
Project work on GitHub

FormatIn person · Urlabari

LevelBeginner → building

DurationTBD

Next batchTBD

FeeTBD

Ask about this track

How we teach

You learn by building things that break.

Four things we hold to. They are the reason the courses are shaped the way they are, and the reason batches stay small.

Build first, theory alongside

You write code in the first session. Concepts land better once you have already hit the problem they exist to solve.

Small batches, real attention

A batch stays small enough that nobody quietly falls behind for three weeks and then stops coming.

The real toolchain from day one

Terminal, Git, GitHub, code review, deployment. The parts most courses skip are the parts a job assumes you already know.

Finished work, not attendance

Progress is measured by what you have shipped and can explain, not by hours logged in a room.

The pathway

Learn → Build → Opportunity

Most institutes stop at the certificate because there is nothing on the other side. We build as well as teach, so there is somewhere for good work to go.

STAGE 01 · LEARN

Academy

Pick a track and work through it. You finish with deployed projects, a GitHub profile and the habits that make the rest possible.

STAGE 02 · BUILD

Real briefs

Scoped project work with review, deadlines and feedback from people who ship. Some of it is our own work, handed down.

STAGE 03 · OPPORTUNITY

Solutions & Labs

Students whose work stands up may be considered for an internship, paid project work, or a place on a Labs team.

This is a route, not a guarantee. There is no promised placement, and there are no numbers to quote yet — only the fact that the work exists inside the same company.

Before you start

What you actually need.

Short list. If one of these is a genuine obstacle for you, talk to us before you rule yourself out — some of them are easier to solve than they look.

A laptop

Strongly preferred, and it does not need to be new. Minimum we recommend: [ADD MINIMUM SPEC]. Setting it up is part of the course.

Consistent attendance

Building skill is cumulative. Missing three weeks in the middle is much harder to recover from than starting late.

Comfort being confused

You will be stuck regularly. That never fully goes away for any of us — the skill being taught is what you do next.

Enough English to read documentation

Teaching happens in the language the batch is comfortable in. Documentation and error messages will be in English, and we spend time on how to read them.

Common questions

Before you ask.

Do I need my own laptop?

It is strongly preferred. Setting up and owning your machine is part of the course, and you will keep working on it after the batch ends. If that is a genuine obstacle for you, talk to us before you rule yourself out.

Do I need any previous experience?

No. Every track starts from the beginning. What you do need is to be able to turn up consistently and be comfortable being confused for a while — that part never fully goes away, for any of us.

How big is a batch?

Small, by design. We cap each batch at 20 students so that nobody spends a month stuck on something a two-minute conversation would fix.

What happens after I finish?

You leave with deployed projects and a GitHub profile, which is what the next employer will actually look at. Students whose work stands out may be considered for an internship or paid project work with Solutions or Labs — that is earned, not promised.

Ask us something else

For businesses

Tell us what you are trying to do.

Describe the problem in plain language. If we are the wrong people for it, we will tell you that instead of quoting for it.

Start a Project

For students

Come and learn to build.

Ask about the next batch, what a laptop needs to run, and what you would actually be building in the first month.

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