YOU open YouTube to learn Python. Twenty minutes later, you have five tabs open, three different roadmaps saved, and someone telling you that you must learn mathematics before you even think about AI. (k k garchau babu, ek choti ma euta kura ma dhyan deu.)
Then an advertisement appears: “Become an AI expert. Enrol now.”
You check the fee, close the page, and think, Maybe I’ll start later.
If this sounds familiar, let us make the starting part a little easier.
Whether you are studying in Kathmandu, working in Pokhara, or learning from home in a village in Syangja, you can begin without spending thousands on a course. You will still need time, practice, and access to a computer but the lessons themselves can be free. (tara paila ichhya hunuparcha, honest intention to learn.)
Here is a practical way to get going.
First, what do you actually want to make?
You do not need a complete career plan. Just pick something you would enjoy building.
Maybe your family runs a small shop, and you want to keep better sales records. Maybe a relative has a homestay in Garuda that could use a simple website. Maybe you’re applying to foreign colleges and you wish you could find all academic informations at one place. Or perhaps you keep hearing about AI and want to understand what happens behind the chat window.
Use that curiosity to choose your starting point.
| If you want to… | Start with… |
|---|---|
| Build websites | HTML, CSS, then JavaScript |
| Automate calculations and repetitive tasks | Python |
| Work towards AI and data projects | Python, then data handling and machine learning |
| Understand AI before trying programming | An introductory AI course |
For someone mainly interested in AI, Python is a sensible place to begin.
And yes, your first few programs may look very ordinary. A calculator. A list of expenses. A program that asks your name.
That is how you learn to make the computer follow your instructions.
Pick one free course and give it a fair chance
The internet has enough free lessons to keep you busy for years. Finding another course is easy. Staying with one when the exercises become difficult takes more effort.
These are a few useful starting points.
Want to learn Python? Try CS50P
Harvard’s CS50 Introduction to Programming with Python has lessons and exercises covering the basics, including variables, conditions, loops, functions, and files.
Watch a section, pause, and try the exercises yourself. Some will take longer than you expect. Getting stuck does not automatically mean you chose the wrong course.
Want to build websites? Try freeCodeCamp
freeCodeCamp offers free coding lessons and projects.
As you learn, make your own version of the exercises. Build a menu for a local café, a page for your college club, or a simple website for that homestay you know.
It is easier to care about spacing, colours, and buttons when you can picture someone actually using the page.
Ready to explore data and AI? Try Kaggle Learn
Kaggle Learn has material on Python, data handling, and machine learning.
Get comfortable with Python first. Then learn how to read a table, handle missing information, and make a chart. Those skills will come in handy when you start working with AI.
Just curious about AI? Try Elements of AI
You might want to understand AI without immediately writing code. That is a reasonable place to start too.
Elements of AI offers a free introduction to what AI can do, where its limits are, and how it affects everyday life.
Choose whichever fits your goal. You can leave the other tabs closed for now.
“But my laptop is old.” (You have laptop, i’ve seen folks code in a mobile phone)
Try it before deciding it needs replacing. (bekar ma paisa kharcha garne haina)
For basic programming, you are mostly writing text and running small programs. Your first expense tracker does not need the same hardware as a large AI model.
You can also use Google Colab to run Python in your browser without setting up a programming environment on your computer. It has a free option, including limited access to computing resources such as GPUs. Availability varies, so do not build your learning plan around always getting a free GPU.
If your phone is all you have right now, use it for lessons, notes, and short exercises. For longer coding sessions, try arranging regular access to a college lab, a shared computer, or a family laptop.
Even a few dependable sessions each week can help you make progress.
And if the Wi-Fi at home in Syangja keeps interrupting your lesson, work around it where you can: save permitted materials when connected, keep your code locally, and practice small programs offline. And honestly if these things are happening, you are a lucky fellow, constraints deepens your focus and you will have a purpose and direction which you won’t believe majority of people don’t have.
Let us build something you might actually use
Suppose you travel to college, eat lunch outside, and buy chiya on the way home. Each expense feels small. By evening, you are wondering where the money went.
Let Python add it up.
Open a Python notebook in Colab, paste this into a code cell, and run it:
expenses = {
"Bus fare": 80,
"Lunch": 150,
"Chiya": 30,
"Snacks": 60
}
total = sum(expenses.values())
print(f"Today's spending: NPR {total}")
budget = 300
if total > budget:
print(f"You spent NPR {total - budget} more than planned.")
else:
print(f"You have NPR {budget - total} left.")You should see:
Today's spending: NPR 320
You spent NPR 20 more than planned.Now make it yours.
Change the bus fare. Add printing expenses. Set your actual daily budget.
Here is what is happening:
expenseskeeps the expense names and amounts together.sum()adds the amounts.budgetstores your spending limit.ifchecks whether you crossed that limit.
Once that makes sense, try making the program ask you to enter the amounts.
After that, try saving a week’s expenses.
You have just given yourself a small project with several things to learn along the way.
When do you get to the AI part?
It is tempting to jump straight into a chatbot or an image-recognition project. You can explore those early, but understanding the basics will make the experience much less confusing.
A useful order is:
Python –> working with data –> basic statistics –> simple machine learning –> your own project.
Imagine you want to study vegetable prices in a market in Tansen.
Begin by recording dates, vegetable names, and prices in a table. Then write a program that answers simple questions:
- What was the average tomato price this month?
- Which item changed most in price?
- Are any dates missing?
Plot the prices before trying to predict them. You may discover that collecting consistent data is already a substantial part of the project.
If you use invented prices to practise, say so clearly. They can teach you how the code works, but they cannot tell you what will happen in the actual market.
Later, when you train a model, test it on data it has not already seen. Otherwise, a good-looking result can give you more confidence than it deserves.
Give your projects a local purpose
You do not have to build something the world has never seen. Start with something you understand well enough to improve.
Help with a family shop. Make a program that records quantities and calculates daily sales. Use sample records while learning; ask permission before using real business data.
Make a homestay page. Include room information, photos you have permission to use, directions, and contact details. Start with one clear page.
Organise college expenses. Track transport, food, printing, and stationery. Add a monthly chart once the basic version works.
Build a sample college notice page. Add categories for exams, events, and scholarships. Clearly mark fictional notices as examples.
A small finished project gives you something concrete to show a friend, teacher, or potential mentor. Their questions will often show you what to improve next.
Use AI when you get stuck
There will be days when one error takes longer than the whole lesson.
Ask for help, but keep yourself involved. Instead of requesting the entire finished program, try:
“Explain this error in simple English. Give me a hint first so I can try fixing it.”
Or:
“I understand this example, but I cannot write it myself yet. Give me a similar exercise using a grocery shop.”
You can also ask for an explanation in Nepali, then connect it back to the English terms used in your course.
Test the answer. AI can give incorrect explanations and code.
Once you fix the problem, try writing that part again without looking. That is a useful check of whether it has clicked.
And before pasting anything into a chatbot, remove passwords, private customer details, and confidential work information.
So, should you ever pay for a course?
Yes, if you know what you need from it.
Perhaps you practise regularly but need someone to review your code. Perhaps learning alone is difficult, and a scheduled class would help you stay consistent. Those are specific reasons to consider paying.
Before enrolling, ask:
- Will someone check my assignments?
- Can I ask questions when I am stuck?
- What will I actually build?
- Can I see a sample lesson and previous student projects?
- What does the full fee include?
“Lifetime access” sounds attractive, but think about whether you will use the material and receive the support you need.
If money is tight, begin with free lessons. Spend later when you can identify the gap you are paying to fill.
Check certificate terms too. Free lessons do not always include a free certificate. CS50x, for example, offers its own free certificate after you meet its requirements, while the optional edX verified certificate is separate.
A first-month plan you can fit around real life
You may have college assignments, a job, household work, or exams coming up. Plan around the time you actually have.
| Week | What to practise | Something to finish |
|---|---|---|
| 1 | Variables, input, and conditions | A daily budget calculator |
| 2 | Loops and functions | Record several expenses |
| 3 | Reading and saving files | Keep records after closing the program |
| 4 | Bringing it together | A small expense tracker with instructions |
Try setting aside 30–60 minutes when you can. Spend some of that time writing code yourself, even if you only manage a few lines.
If an exercise takes three evenings, let it take three evenings. If you miss a week because of exams, open the project again when you return. You do not have to restart from lesson one.
By the end of the month, aim for something modest: one program you can run, change, and explain. A first month is a beginning; becoming ready for professional work will take more practice.
For today, choose one course and try its first exercise.
If you want an even smaller start, run the expense calculator above and change it to match what you spent yesterday. That is enough to begin.
Yetti garisakepachi, you’ll have clearer ideas and if the intention to learn hasn’t died, you will definitely become good at your craft.
YO GENERATION MA LAST SAMMA PADHYAU, LAH DAMI. THANK YOU HAI TA.
