Lima · University students · Live online, in English
Coding for university students in Lima
You study in Spanish at a Lima university, between lectures, labs and a long ride across the city. The programming world you are heading into works in English: its documentation, its error messages, its code reviews. This page sets out what to learn beside your degree each year, why learning it in English pays off, how live classes fit a Lima timetable, and a statistics lesson on UNI's own open admission data that every computing student should meet once.
Live classes since 2020 · more than 10,000 learners worldwide · mentors who code with you, not at you
Short answer
Modern Age Coders teaches university students in Lima to program, live online and in English: Python from zero, data structures and algorithms, Git and GitHub, SQL, and then Java, web development or data science. Lessons are taught live over video by a mentor, either one to one or with fifteen to twenty classmates, at hours that fit around lectures, labs and the commute. Students write and test their own code every session, so they learn to reason about a problem instead of pasting an answer, and they learn the English vocabulary of the field as they go.
Start here
Three courses Lima university students start with
Python if you are new to code, data structures if you already program, and Git because every team expects it.
Who is this for, and how does it sit beside a Lima degree?
Any undergraduate in Lima, whether in computing, engineering, economics or a field that has nothing to do with code yet. Universities set your degree; we teach programming beside it and are not connected with any university.
A big student city
SUNEDU reported in September 2021 that Peru had 94 licensed universities, 46 public and 48 private, with "1 millón 100 mil de estudiantes universitarios". It has published no newer national total that we found, so the figure keeps its year. A large share of those students live in Lima Metropolitana, a city of 10,141,775 people in the 2025 census.
Lima's universities each run their own calendars. The Universidad de Lima, for example, starts its 2027-1 classes on Monday 29 March 2027, and UNMSM ran its 2026 admission in two stages, 2026-I and 2026-II.
Where our classes fit
Degrees in Peru are taught in Spanish, and they cover theory well. What students tell us they lack is volume of practice: writing hundreds of small programs, reading other people's code, and using the tools teams use.
Our classes add that practice, at an hour you choose, without asking you to travel. They do not replace a course, earn credits, or count towards a grade; your university alone decides those.
Year by year
What should a Lima university student learn beside the degree each year?
Our suggested plan. Adjust it to your degree; a computing student moves faster through the first rows, an economics student may stop after data.
A programming plan beside a five-year Lima degree (ours)
Year
Focus
Course
You can show at the end
First
Python and Git
Python masterclass, Git and GitHub
Small tools in a public repository
Second
Data structures and algorithms
DSA masterclass
Solutions you can explain and time
Third
Databases and the web
MySQL, full stack web development
A working web app with a database
Fourth
Data or a second language
Data science, or Java
An analysis on real open data, or a Java service
Final
Depth in one direction
AI and ML, generative AI, or interview practice
A finished project you can present in English
Start small and public. Push every exercise to GitHub from week one. A history of small commits is more convincing than one large upload.
Write before you search. Attempt each problem for twenty minutes before reading any solution or asking an AI tool. Then compare.
Learn to read errors in English. Copy the last line of every traceback into your notes with what it meant. In a month you will recognise most of them.
Explain your code aloud. In class the mentor asks you to walk through your solution. That is the skill technical interviews test.
Use real data once a semester. Peru's open-data portal has thousands of datasets. The lesson below is one example.
Python or Java
Should a Lima university student learn Python or Java first?
Python first for almost everyone; Java first only if your degree already teaches it in the first year or you are sure you want backend or Android work.
The case for Python
Python lets a first-year student write something useful in the first week: a script that renames files, a grade calculator, a chart from a CSV. The syntax gets out of the way, so attention goes to the logic.
It is also the language of data work in economics, engineering, the sciences and AI, which makes it useful to students well outside computing.
The case for Java
Java makes you state types and structure classes from the start. Many computing degrees use it for object-oriented programming courses, and students who meet it early find those courses easier.
If your curriculum switches to Java in the second year, learn Python now and take our Java course the semester before. The ideas carry over; only the syntax is new.
Whichever you choose, the habits matter more than the language: small programs every week, tests before trust, and code you can explain line by line in English. Students already deep in a computing degree will find the specific path on our Java course page for Peru and our Python course page for Peru.
Why English
Why learn programming in English as a Lima student?
Because the field already works in English, and because your English is likely to grow fastest in exactly these years. We teach only in English, and always live.
What the EF figures suggest
EF's English Proficiency Index 2025 gives Peruvians aged 18 to 20 a score of 469, in its low band, and those aged 26 to 30 a score of 559, in its high band. The same edition scores Lima city 555 and people working in IT 522.
These are different people, not the same people measured twice, so we read it cautiously: the years around university look like a time when English can grow fast. Practising it with code, where the vocabulary is narrow and repeated, is an efficient way to use that window.
What it changes day to day
Python's documentation, Stack Overflow answers, library READMEs and most video courses are in English. So are compiler errors, whatever the language of your operating system.
Mentors are based in India and teach in clear, steady English. They expect questions, repeat when asked, and help you say "this function returns a list of tuples" as naturally as you say it in Spanish.
English you will use in your first month (our list)
English
In a sentence
Spanish
to return
The function returns the average
devolver
an argument
Pass the file name as an argument
un argumento
to raise an exception
It raises a ValueError on empty input
lanzar una excepción
a pull request
Open a pull request for review
una solicitud de cambios
edge case
An empty list is an edge case
caso límite
A Lima data lesson
Do applicants really score higher on every retake at UNI?
UNI publishes anonymised data on its admission applicants as open data. We use it, in our own lesson, to teach a mistake that appears in research, business dashboards and student projects alike: comparing averages of groups whose members keep changing.
The data
The Universidad Nacional de Ingeniería shares "Postulantes a los procesos de admisión" through Peru's national open-data portal, licensed ODC-By (Open Data Commons Attribution). The file Admision_UNI_2018-2_al_2020-1.csv covers four admission cycles, 2018-2 to 2020-1, in 30,358 rows.
Its data dictionary describes the id column as an anonymous identifier that "debería aparecer nuevamente con el mismo identificador" when a person applies more than once. That makes repeat applicants traceable without knowing who they are. We use only the ordinary exam route, rows with a score, and print only averages.
The question
For each applicant we sort their attempts in time, then ask: how does the average score change from first attempt to second, third and fourth?
Version 1 does what most first analyses do. It puts every first attempt in one column, every second attempt in another, and compares the column averages.
Version 1: average score by attempt numberPython
import csv
from collections import defaultdict
from statistics import mean
tries = defaultdict(list)
with open("Admision_UNI_2018-2_al_2020-1.csv", encoding="utf-8") as data:
for row in csv.DictReader(data):
if row["modalidad"] == "ORDINARIO" and row["calificacion_final_postulante"]:
when = (int(row["año_postulacion"]), int(row["ciclo_postulacion"]))
tries[row["id"]].append((when, float(row["calificacion_final_postulante"])))
by_attempt = defaultdict(list)
for scores in tries.values():
for n, (when, score) in enumerate(sorted(scores), start=1):
by_attempt[n].append(score)
print("Applicants:", len(tries))
for n in sorted(by_attempt):
print("Attempt", n, "rows", len(by_attempt[n]), "mean", round(mean(by_attempt[n]), 3))
It prints: Applicants: 11054, Attempt 1 rows 11054 mean 7.45, Attempt 2 rows 3888 mean 9.301, Attempt 3 rows 1312 mean 10.124 and Attempt 4 rows 305 mean 10.24.
Read naively, retakes help a lot at first and then barely at all: from attempt 3 to attempt 4 the average rises by only 0.116 points. But the columns contain different people. Only 305 applicants reach a fourth attempt, and they are not a random fifth of the 1,312 who made a third. Version 2 compares each person with themselves.
Version 2: the same person, before and afterPython
import csv
from collections import defaultdict
from statistics import mean
tries = defaultdict(list)
with open("Admision_UNI_2018-2_al_2020-1.csv", encoding="utf-8") as data:
for row in csv.DictReader(data):
if row["modalidad"] == "ORDINARIO" and row["calificacion_final_postulante"]:
when = (int(row["año_postulacion"]), int(row["ciclo_postulacion"]))
tries[row["id"]].append((when, float(row["calificacion_final_postulante"])))
for scores in tries.values():
scores.sort()
for k in (1, 2, 3):
pairs = [(s[k - 1][1], s[k][1]) for s in tries.values() if len(s) > k]
stayed = [s[k - 1][1] for s in tries.values() if len(s) == k]
gain = mean(b - a for a, b in pairs)
print(f"Attempt {k} to {k + 1}: {len(pairs)} people, same-person gain {gain:.3f}")
print(f" at attempt {k}: returners {mean(a for a, b in pairs):.3f}, leavers {mean(stayed):.3f}")
It prints: Attempt 1 to 2: 3888 people, same-person gain 1.698, at attempt 1: returners 7.603, leavers 7.367, Attempt 2 to 3: 1312 people, same-person gain 1.043, at attempt 2: returners 9.081, leavers 9.413, Attempt 3 to 4: 305 people, same-person gain 0.856 and at attempt 3: returners 9.385, leavers 10.348.
Two ways to measure the change between attempts (our calculation, ordinary route)
Step
Change in column averages
Average change for the same people
People in the pair
Attempt 1 to 2
1.851
1.698
3,888
Attempt 2 to 3
0.823
1.043
1,312
Attempt 3 to 4
0.116
0.856
305
Data: Universidad Nacional de Ingeniería, Postulantes a los procesos de admisión, 2018-2 to 2020-1, from the national open-data portal under an ODC-By licence. Every figure is our own, in points on the file's own score scale. The file also contains addresses and school names, which we neither use nor print. A "first attempt" here is the first within these four cycles; some applicants may have applied before 2018-2.
The last line explains everything. At attempt 3, the people who came back for a fourth try averaged 9.385; those who did not come back averaged 10.348. The column for attempt 4 is filled by weaker attempt-3 scorers, so its average looks flat even though those same people improved by 0.856 on average. Comparing crowds hid most of the change. This is the general rule: when membership changes between groups, compare matched pairs. It says nothing about whether anyone should retake an exam; that is a personal decision, and admission is decided by the university alone.
Check the pairing. Confirm no id appears twice in the same cycle in the ordinary route before trusting the sort.
Add uncertainty. Compute a 95% interval for the 0.856 gain with 305 pairs. Is it clearly above zero?
Find the selection. Group attempt-1 scores into bands and show, band by band, who returns.
Write it in English. Summarise the finding in three sentences a non-programmer could follow, without claiming cause.
Generalise. Name one dashboard at a company or university where the same trap could appear, and how you would pair the data.
Around a Lima timetable
How do live online classes fit a Lima student's week?
Better than a second commute. A class you join from your room, a campus library or a quiet corner at work costs only the hour itself.
Fixed or moving
Groups meet at a regular hour you choose when joining. One-to-one classes can move week by week around exams, lab reports and part-time work.
Connection
INEI found that 97.3% of people aged 19 to 24 in Peru were internet users in its survey for April to June 2026. A laptop and a stable connection are all you need.
During exams
Pause during finals and restart afterwards. Monthly plans have no long contract, so the plan can follow the semester.
At hours you pick. Lima keeps the same clock all year, and so does India, so a slot never drifts.
Lima hours against the mentor's India time (illustrations, not a timetable)
Lima
India
India date
07:00
17:30
Same
09:30
20:00
Same
12:00
22:30
Same
17:00
03:30
Next
21:00
07:30
Next
Lima runs five hours behind UTC and never changes its clocks (tz zone America/Lima); India runs five and a half hours ahead of UTC. The gap stays at 10 hours 30 minutes.
Book in Lima time and the mentor sees the India time automatically. Many students choose early morning before lectures or a lunchtime hour on campus; late evening works too.
Progress
How a university student progresses with us
Our milestones for students, whatever their degree. Each one is something you can demonstrate, not a number of hours.
Programming milestones for university students (ours)
Milestone
Usually by
You can
1. Fluent basics
Month 2
Write and debug small Python programs alone
2. Versioned
Month 3
Work through branches and pull requests
3. Efficient
Month 6
Choose a data structure and state its cost
4. Persistent
Month 8
Store and query data with SQL
5. Analytical
Month 10
Analyse a real file and avoid a misleading comparison
6. Communicative
Month 12
Present a project and its limits in English
In practice
Milestone 5 is the UNI lesson: spotting that the attempt-4 column holds different people from the attempt-3 column.
You get a short note after each block on what to strengthen.
A rule to keep
When the members of a group change, compare each member with themselves.
A flat average can hide a real change.
More courses
Nine more courses for Lima university students
Three directions. Every course is live, in English, with a regular mentor, in a group or one to one.
A weather forecasting site with live conditions for any location.
by Krish
Fees
Fees for university students in Lima
Plans are paid month by month. The price is set in US dollars and your card is billed in dollars; the soles amount on your statement depends on your bank's exchange rate that day.
From Google, in the words of students and parents.
★★★★★
"The one step solution for my son. Modern Age Coders make learning coding so simple that kids love it. The teachers explain complex concepts clearly with practical exercises and interactive content."
Ria Mukherjee
Parent
★★★★★
"Modern Age Coders has been a game-changer for me. I struggled to grasp IT concepts and coding before joining, but their classes transformed everything. I can now confidently write complex programs with ease."
Samriddha Mondal
Student
★★★★★
"One of the most wonderful education centres out there. Education is not limited to school syllabus but focuses on skill development."
Vansh Agarwal
Student
★★★★★
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Parent of Dhairya
★★★★★
"Modern Age Coders have wonderful teachers who teach in a clear, easy and practical way. The teacher boosts students' confidence and inspires them to learn without hesitation."
Sonu Goyal
Parent
★★★★★
"I highly recommend this computer coding class! The teachers are incredibly knowledgeable and passionate about coding."
Ritu Kedia
Parent
Lima students ask
Coding for university students in Lima: questions and answers
Are the classes in Spanish?
No. All classes are live, online and taught only in English. Mentors keep a steady pace, adapt to your accent, and help you put into English what you already understand in Spanish.
I study at a Lima university. Do your classes count towards my degree?
No. We give no credits or grades and we are not connected with UNI, UNMSM, PUCP, the Universidad de Lima or any other university. Our classes are practice beside your degree.
I have never programmed. Where do I start?
With the Python masterclass and the Git course. Both start from zero. After about three months most students move on to data structures.
Will this get me a job?
We make no job or salary promises. We teach skills that software teams use and help you build projects you can show and explain; how you use them is up to you.
Can I use AI tools in class?
Sometimes, and openly. You attempt problems yourself first, then compare with an AI suggestion and explain any difference. The aim is that you understand every line you submit.
What time are classes?
Any day, any time, flexible: choose a batch, or for a very personalised plan choose 1-on-1 at the hour that suits your family. For the mentor in India it is always 10 hours 30 minutes later: 09:30 in Lima is 20:00 there.
Can I pause during exams?
Yes. Plans are monthly. Pause during finals and restart when the semester allows.
How much does it cost?
You pay monthly by card in the US dollars shown here, and your bank handles the change into soles. Browsing from India shows rupees instead. Your first class is free of charge.
Do I get a certificate?
Some courses close with a completion certificate from us. It records your work; it is not a university credit or degree, and neither SUNEDU nor any university has a part in it.
Teaching is live, online and English-only, from mentors in India. Message us on WhatsApp, in English, for a fast reply.
Want a class sooner? Book a priority demo
A priority demo is a full class of about 45 to 60 minutes. After the class the mentor sends a written skill report and a personal learning roadmap on WhatsApp. If you enrol, the demo fee is adjusted against your first month's fee. Share your demo Order ID with us on WhatsApp and we take it off.
