The main IT jobs people in Nepal aim for are web and full stack developer, backend developer, data analyst, AI or machine learning engineer, cloud and DevOps engineer, cyber security, software QA, digital marketing and video editing. Each one needs a different set of skills. They all start the same way, though: learn the basics properly, build real things, and show your work where people can see it.
This guide explains each job in plain words, what you need to learn for it, and which of our courses fits. It ends with how to choose between them and how to start.
The jobs at a glance
| Job | What you do | Coding needed? | Our course |
|---|---|---|---|
| Web and full stack developer | Build websites and web apps, screens and server | Yes | Full Stack with Vibe Coding |
| Backend developer | Write the server code, APIs and databases behind an app | Yes | Backend Engineering |
| Data analyst | Turn business data into answers, reports and dashboards | Some (SQL, Python) | Data Science & Machine Learning |
| AI or machine learning engineer | Build app features that use models and AI tools | Yes | AI Engineering & Machine Learning |
| Cloud and DevOps engineer | Run servers and automate how code goes live | Scripting | Cloud Computing & DevOps |
| Cyber security | Find weak spots and watch for attacks | Some scripting | Cybersecurity & Ethical Hacking |
| Software QA | Test software and catch bugs before users do | Not at first, later yes | Software Quality Assurance |
| Digital marketing | Help a business get found and chosen online | No | Digital Marketing with AI |
| Video editor | Cut footage into finished videos, reels and ads | No | Video Editing |
The main IT jobs, one by one
Web and full stack developer
The work: A web developer builds the websites and web apps people use in a browser. "Full stack" means you handle both sides. The frontend is what users see and click. The backend is the server and database behind it. A full stack developer can take an idea from a blank screen to a live app.
What to learn: HTML, CSS and JavaScript come first. Then a frontend library such as React, a framework such as Next.js, a database, and Git for saving versions of your code. More and more developers now also use AI coding tools. That only works if you can read the code they write and spot mistakes.
Our course: Full Stack Development with Vibe Coding runs for 6 weeks. You build a full stack web app in Next.js and a Flutter mobile app by directing AI tools like Cursor and Claude Code, then checking and fixing what they produce. Both go live on a real domain. If you are torn between this and backend, read Backend Engineering or Full Stack with Vibe Coding.
Backend developer
The work: A backend developer writes the code that runs on the server. When an app logs you in, saves an order or shows your messages, backend code did that work. The main pieces are APIs, which are the doors an app knocks on to ask a server for data, and databases, where the data is stored. Backend developers also care about speed and security.
What to learn: One programming language well, such as JavaScript with TypeScript, Python or PHP. Then how the web works (HTTP), how to build an API, SQL for databases, login and security, Git and the Linux terminal. If you are not sure which language to pick, read Node.js, Django or Laravel: which backend to learn first.
Our course: Backend Engineering runs for 10 weeks and starts with no coding needed. It teaches JavaScript and TypeScript, Node.js, Express, NestJS, PostgreSQL, Prisma and Redis, then system design and Docker, and ends with a deployed project.
Data analyst
The work: A data analyst takes raw numbers from a business, cleans them, and answers questions with them. Which product sells most in which month? Why did sign-ups drop last week? The answers usually end up in a report or a dashboard that managers read.
What to learn: Excel, SQL for pulling data out of databases, Python with pandas for cleaning it, basic statistics, charts, and a dashboard tool such as Power BI. Clear writing matters too, because a good finding is useless if nobody understands it.
Our course: Data Science & Machine Learning runs for 12 weeks. It covers Python, SQL, pandas, Power BI and starter machine learning with scikit-learn, all from zero. To see how the analyst and scientist roles differ, read Data analyst vs data scientist.
AI or machine learning engineer
The work: A machine learning engineer builds software that learns patterns from data, such as a model that predicts which customers might leave. Many AI engineers today also build features with large language models, the kind of model behind ChatGPT and Claude. Examples are a chatbot that answers from a company's own documents, or a tool that reads forms and fills a database.
What to learn: Python first. Then the basics of machine learning with scikit-learn, how to call AI model APIs, how to give a model your own documents to answer from (often called RAG), and how to test that the answers are right. You also need enough backend skill to put your work into a real app.
Our course: AI Engineering & Machine Learning runs for 12 weeks. It teaches Python from zero, scikit-learn, PyTorch, the OpenAI, Claude and Gemini APIs, and RAG tools such as LangChain and LlamaIndex. If you want to use AI tools without writing code, look at No-Code AI, Agents & Automation, a 5-week course. This comparison explains the difference.
Cloud and DevOps engineer
The work: A cloud and DevOps engineer looks after the servers an app runs on and the path code takes to get there. They set up pipelines that test and release code automatically, package apps into containers, manage cloud services such as AWS, and watch dashboards so problems are caught early. When a site goes down, they are often the ones who fix it. What does a DevOps engineer do walks through a normal week.
What to learn: Linux and the terminal, networking basics such as DNS and HTTPS, Git, a scripting language, one cloud provider, Docker, a CI/CD tool for automatic testing and release, Terraform for setting up servers from code, and later Kubernetes and monitoring.
Our course: Cloud Computing & DevOps runs for 10 weeks. It covers Linux, Nginx, AWS, Docker, GitHub Actions, Terraform, Ansible, Kubernetes, Argo CD, Prometheus and Grafana, and ends with a capstone you build and present.
Cyber security
The work: Cyber security has two broad sides. One side tests systems for weak spots before an attacker finds them. This is often called VAPT, short for vulnerability assessment and penetration testing. The other side watches systems for signs of an attack and responds. That work often happens in a SOC, a security operations centre. Both sides write reports that explain risk in plain words.
What to learn: How networks and the web work, Linux, and Windows basics. Then tools such as Nmap, Wireshark and Burp Suite for testing, and log tools such as Wazuh or Splunk for watching. Always practise on labs and systems you have permission to test.
Our course: Cybersecurity & Ethical Hacking runs for 12 weeks and covers both sides, from recon and web testing to hardening and alert triage. See ethical hacking vs cybersecurity training for how the two differ, and short course or bachelor's degree if you are weighing a degree.
Software QA
The work: A QA (quality assurance) engineer checks that software works before users see it. You read what a feature should do, write test cases, try to break it, report bugs clearly, and check the fix. Most QA engineers also write automated tests, which are small programs that click through an app and check results by themselves.
What to learn: Test design and manual testing first, then a bug tracker such as Jira, API testing with Postman, and some SQL. After that, a programming language and an automation tool such as Playwright or Selenium. Is software QA a good career in Nepal? gives an honest answer.
Our course: Software Quality Assurance runs for 8 weeks. It starts with manual testing, moves to API testing and SQL, then teaches TypeScript with Playwright, plus a second framework in Selenium.
Digital marketing
The work: A digital marketer helps a business get found and chosen online. That covers SEO, which means getting a site to show up in Google search, running ads on Meta and Google, writing content, and reading the numbers to see what worked. It is the most people-facing job on this list.
What to learn: How marketing strategy works, SEO, Google Analytics and Search Console, Meta Ads and Google Ads, and basic marketing maths such as cost per lead. No coding is needed.
Our course: Digital Marketing with AI runs for 8 weeks. You come with a small business idea or niche and work on it through the course.
Video editor
The work: A video editor turns raw footage into a finished video. That includes YouTube videos, reels, ads and interviews. You cut the story, fix colour and sound, add titles and captions, and export the file in the right format for each platform.
What to learn: An editing app such as DaVinci Resolve or CapCut, colour correction, sound clean-up, vertical video for reels, and motion graphics in After Effects. A good eye for pacing matters as much as the software.
Our course: Video Editing runs for 5 weeks. It covers DaVinci Resolve, CapCut, After Effects, sound in Fairlight and delivery for YouTube and short video.
How to choose
Start from what you enjoy doing for hours, not from what your friends picked. Here is a rough guide:
- You like building things you can see and click: full stack development.
- You like logic and how things work behind the scenes: backend development.
- You like numbers and business questions: data analysis.
- You like maths and code together, and AI excites you: AI or machine learning.
- You like systems, servers and keeping things running: cloud and DevOps.
- You are curious how things break and how to protect them: cyber security.
- You notice small mistakes and like checking things carefully: software QA.
- You like people, writing and persuasion: digital marketing.
- You like stories, music and visuals: video editing.
If two of these sound right, try a free beginner tutorial in each for one week. The one you keep going back to without being pushed is usually the one to choose. Also look at real job posts for that role, and check whether the daily tasks they describe sound like work you would enjoy.
How to start
Whichever job you pick, the first steps look similar.
- Learn the basics properly. Do not rush to the advanced tools. For any coding role, learn Git and the terminal early. They come up every day.
- Build small projects early. A to-do app, a small API, a cleaned dataset with a chart, a test plan for a public website, a short edited reel. Small and finished beats big and half done.
- Put your work on GitHub. GitHub is a website that stores your code and shows its history. Give every project a short README file that says what it does, how to run it and what you learned.
- Make a simple portfolio. One page that links your two or three strongest projects is enough. Marketers can show a campaign case study. Video editors can show a short showreel.
- Practise a little every day. One hour daily works better than one long weekend session.
- Show what you built. Write a short LinkedIn post about each project: the problem, what you built and what went wrong along the way.
- Ask for feedback. Show your work to someone who already does the job. Their comments will teach you faster than another tutorial.
None of these steps needs money. A laptop, an internet connection and steady effort get you a long way.
Learning on your own or with a course
Plenty of people learn IT skills on their own with free material. It works if you are disciplined and know what to learn next. A course gives you a fixed plan, deadlines, and a mentor who reviews your work and tells you what is wrong with it.
Our courses run in small batches in Old Baneshwor, Kathmandu, with 10 seats in the room and up to 5 live online seats for students outside the valley. Every class is recorded. You can compare them all on the courses page, see how online classes work, or contact us to ask a trainer which job fits you.
