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Good practice Imported

3MTT — Nigeria's 3 Million Technical Talent Programme

Nigeria · Abuja · See the Nigeria profile · See the Abuja profile

Evidence: Observational / pre–post Top 65% 62/100 · Ask Evidence Copilot about this practice

Nigeria's federal digital-skills programme aims to train 3 million tech workers by 2027; after two years it had onboarded ~90,000 of 1.8M applicants, but only 19% of the first cohort completed training and initial job-placement rates were around 11%.

3,000,000 people
Target trainees by 2027
1.8 million+
Total applications received
90,000+
Learners onboarded (first three cohorts) (by October 2025)
200+
Applied Learning Centres nationwide
7,500+
Fellows placed into jobs
35 % (against 40% internal target)
Female participation
19 % (6,000 of 31,270 selected)
Cohort-one completion rate (cohort 1)
11.2 %
Cohort-one job-placement rate (cohort 1)
$25 → $2.60 USD/year
AWS-modelled per-learner support cost
3MTT — Nigeria's 3 Million Technical Talent Programme

Details

Maturity
Scaling
Promoter
Federal Ministry of Communications, Innovation and Digital Economy (Nigeria) / National Information Technology Development Agency (NITDA)
Period
2023–present
Keywords
Digital skills training, tech workforce development, talent building

Context

3MTT (3 Million Technical Talents) is a federal digital-skills programme launched in November 2023 by Nigeria's Ministry of Communications, Innovation and Digital Economy, delivered through the National Information Technology Development Agency (NITDA), aiming to train three million Nigerians in software development, data, AI, cybersecurity and design by 2027.

Objectives

The programme's goal is to position Nigeria as a net exporter of tech talent by building a large, digitally skilled workforce drawn from nearly all of the country's 774 local government areas.

Activities

3MTT has drawn more than 1.8 million applications and, by October 2025, had onboarded over 90,000 learners across its first three cohorts, delivered through more than 200 Applied Learning Centres nationwide. Amazon Web Services partners on cloud infrastructure and has modelled an AI-supported learning-assistance approach intended to cut per-learner support costs from roughly $25 to $2.60 a year, aimed at making the eventual 3-million-learner target financially viable.

Results

The programme reports more than 7,500 fellows placed into jobs through employer networks, with female participation at 35% against an internal 40% target. Independent review by TechCabal of the first cohort found that only 6,000 of the 31,270 selected fellows (19%) completed the programme, with an 11.2% job-placement rate, and raised questions about whether a three-month course adequately prepares fellows for employment.

Conclusions

3MTT shows a national government building large-scale digital-skills infrastructure and AI-assisted delivery to reach a very large target population, but independent cohort-level data shows completion and placement rates for the first cohort were modest relative to the programme's ambitions.

Implementation

Indicative cost
High (€500k–€5M) — Independent reporting cites roughly $12 spent per fellow in cohort one; AWS has modelled cutting per-learner support costs from about $25 to $2.60 a year to make the full 3-million-learner target affordable.
Time to results
Medium (1–3 years)
Staffing & skills
Federal Ministry of Communications, Innovation and Digital Economy (policy sponsor), National Information Technology Development Agency (NITDA) (delivery agency), 200+ Applied Learning Centres nationwide (training delivery network), Amazon Web Services (cloud infrastructure and AI-supported learning-assistance partner)

Conditions for success

  • Nationwide network of 200+ Applied Learning Centres to deliver training at scale
  • AI-assisted learning-support model developed with AWS aimed at cutting per-learner support costs roughly ten-fold to make the 3-million-learner target financially viable
  • Private-sector job-placement partnerships used to connect fellows to employers

Common failure modes

  • TechCabal's independent review found only 19% of the 31,270 selected cohort-one fellows completed the programme and only 11.2% were placed in jobs, raising questions about whether a three-month course adequately prepares fellows for employment.

Where it fits

Governance type
federal government agency
Scale
national (Nigeria)
Income level
lower-middle-income country

Commonly funded by

National / regional programmes

Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.

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Data sources

Where this practice's information was retrieved from, and when.

Attachments

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