Online coding and AI classes in the Lima provinces

People: the 2025 census tabulation of demographic indicators (INEI, table 1), census day 15 September 2025. Homes and internet users: the ENAHO survey as reprinted in INEI's 2026 compendium (cuadros 11.5, 11.6, 11.13), whose footnote defines Región Lima as the nine provinces listed above. The two columns are separate units and are never combined here.

Province totals from the same 2025 census table, which adds INEI's estimate of uncounted residents to the people counted, using the provincial limits valid in July 2026. Lines reproduced unchanged.

MINEDU school-census numbers, reprinted by INEI in its 2026 compendium (enrolment cuadros for primaria and secundaria by type of management). We changed the decimal mark only.

Technical and vocational centres in the region are active too: in November 2026 the DRELP announced the winners of its third regional CETPRO contest on innovation and enterprise. The ministry's own coding scheme, Fábrica de Programadores, chose its first thousand Python pupils (July 2025) from Lima Norte, which lies inside the capital rather than the provinces. A teenager in Barranca or Huacho who wants serious programming still has to look beyond school.

import csv
from collections import Counter

first_seen = {}
with open("matriculados_unjfsc_2020_2025.csv", newline="", encoding="utf-8-sig") as f:
    for row in csv.DictReader(f, delimiter=";"):
        term = row["ANIO"] + "-" + row["SEMESTRE"]
        if row["UUID"] not in first_seen or term < first_seen[row["UUID"]]:
            first_seen[row["UUID"]] = term

new = Counter(first_seen.values())
print("Different students:", len(first_seen))
for term in ["2020-1", "2020-2", "2021-1", "2025-1"]:
    print("New in", term, new[term])

The 25,700 different codes is a sound figure. The 10,589 "new" students in 2020-1 is not: that is every single student enrolled that semester, because the file begins there. Someone in the fifth year of a degree in 2020 also appears for the first time in 2020-1, simply because the window opens then. Statisticians call this left censoring: the data cannot see what happened before its first date.

Version 2 uses the CICLO column as a second witness. A student whose first appearance is in cycle 01 really did start then. A student who first appears in cycle 05 was already studying, and the window just cut into their degree.

import csv
from collections import Counter

first = {}
with open("matriculados_unjfsc_2020_2025.csv", newline="", encoding="utf-8-sig") as f:
    for row in csv.DictReader(f, delimiter=";"):
        term = row["ANIO"] + "-" + row["SEMESTRE"]
        if row["UUID"] not in first or term < first[row["UUID"]][0]:
            first[row["UUID"]] = (term, row["CICLO"])

started_here, already_studying = Counter(), Counter()
for term, cycle in first.values():
    if cycle == "01":
        started_here[term] += 1
    else:
        already_studying[term] += 1

for term in ["2020-1", "2020-2", "2021-1", "2025-1"]:
    print(term, "first year:", started_here[term], "| already further on:", already_studying[term])

Now the picture changes. Only 586 of the 10,589 students first seen in 2020-1 were in their first cycle. The rest were already on course. By 2025-1, almost every first appearance really is a beginner: 1,460 starters against 66 others. The few "already further on" in later years are worth a question of their own, perhaps transfers or returning students, and we do not guess.

Data credit: Universidad Nacional José Faustino Sánchez Carrión, enrolment 2020 to 2025, reused under CC-BY; file cut-off date 14 October 2025. Counts are ours. Each semester is a separate headcount: adding the twelve rows would count the same students many times over.

1. Under 8, with a photo album. If the album starts on your sixth birthday, does that mean you were born that day? What is missing from the album?
2. Block coding, around 8 to 10. Keep a list of names seen each week. Write a loop that marks a name "new" the first time it appears, then talk about the first week.
3. Typing Python, about 10 to 12. Try Version 1 and explain in two sentences why 10,589 cannot be the number of new students in 2020-1.
4. Ages 13 and over. 2022-2 has far fewer rows than the semesters around it. Write down three possible reasons, and what extra data would tell them apart.
5. Going further. For students who started in cycle 01 in 2021-1, count how many still appear in 2025-1. State clearly why students who started in 2020-1 or before cannot be treated the same way.

Course ages are ours; school years use MINEDU's normative age on 31 March, so birthdays after that date can mean one grade lower.

University students can read more on coding courses for university students in Peru, and anyone weighing up Java should see our Java course page for Peru.

In the tz database, America/Lima sits five hours behind UTC and has observed no summer time since 1994; INACAL maintains Peru's official hour. India is UTC plus five and a half hours, giving a constant gap of ten and a half hours.

A slot booked in summer stays at the same local time all year. Families in the provinces often like an early-morning class, before school or work, which is late afternoon or evening for the mentor.