Kifiya AI Mastery (KAIM) Training Program

The Kifiya AI Mastery Training Program, delivered by 10 Academy, is a set of intensive three-month remote training program that create job-ready AI Engineers for the Ethiopian FinTech sector. Trainees will engage in a comprehensive curriculum covering key technology areas such as Generative AI Engineering, Machine Learning Engineering, and Data Engineering. The program emphasizes project-based learning, ensuring that trainees gain practical skills that can be directly applied to real-world scenarios. The program is delivered by 10 Academy, on behalf of Kifiya Financial Technology and is funded by the Mastercard Foundation.

The Kifiya AI Mastery Training Program, delivered by 10 Academy, is a set of intensive three-month remote training program that create job-ready AI Engineers for the Ethiopian FinTech sector. Trainees will engage in a comprehensive curriculum covering key technology areas such as Generative AI Engineering, Machine Learning Engineering, and Data Engineering. The program emphasizes project-based learning, ensuring that trainees gain practical skills that can be directly applied to real-world scenarios. The program is delivered by 10 Academy, on behalf of Kifiya Financial Technology and is funded by the Mastercard Foundation.

Overview

What is the KAIM Training Program?

The KAIM Program prepares top Ethiopian talent for roles in FinTech through a hands-on curriculum and personalized support. In just three months, trainees develop deep capabilities in Generative AI, Machine Learning, and Data Engineering. With a strong emphasis on project-based learning and career development, KAIM graduates are ready to contribute to real-world teams immediately.

Program Duration & Intensity

  • 12 weeks (remote)
  • 40 hours/week
  • Project-based, community-supported learning

Skills & Tools

Technology Areas Covered

  • Generative AI Engineering
  • Machine Learning Engineering
  • Data & Analytics Engineering
  • MLOps & AutoML
  • Prompt Engineering

Key Tools & Platforms

  • Python, SQL, Git, Docker
  • TensorFlow, PyTorch, HuggingFace
  • Apache Airflow, Spark, DBT
  • GPT-based APIs and LLM tooling
  • MySQL, Postgres, S3

Competencies

Domain

Competencies

AI/ML

Model development, Deep Learning, Feature engineering, AutoML

Data Engineering

ETL pipelines, Data warehouse setup, Streaming pipelines

GenAI

Prompt engineering, LLM use cases, API integration

MLOps

Workflow automation, versioning, deployment

Careers

Communication, Team collaboration, Time management, Job applications

Domains Explored

  • AI & Deep Learning
  • Machine Learning
  • Data Engineering
  • Prompt Engineering
  • MLOps
  • Career Readiness

Prerequisites

  • Undergraduate degree
  • English proficiency (B1 CEFR or above)
  • Legal right to live and work in Ethiopia

Project-Based Learning

Trainees complete weekly technical and career challenges that mirror industry scenarios, building a portfolio of 10+ projects with personalized feedback.

Weekly Schedule

The 12-week program follows a consistent structure with flexibility for asynchronous participation. Each week includes:

  • Daily Standups (recorded, available afterward)
  • 5+ Technical & Career Tutorials per week(recorded, available afterward)
  • Technical + Career Challenges
  • Community-building sessions on Slack
  • Guest speaker sessions
  • Women-only sessions (Fridays)

Submissions: Technical intrim submission - mid week submission (Sunday),Final Technical and Careers challenge (Tusday).

Feedback: Detailed feedback + grading within 2-5 minutes after submission and human verfication within one week.

Time Expectations

  • 40 hours/week active learning
  • Full-time work possible in parallel
  • Real-time tutor support (Mon–Sat, 8 AM–2 PM UTC)
  • Support response within 5 minutes
  • Dedicated community manager

Career Outcomes

Graduates are well-prepared to enter the FinTech workforce as:

  • AI Engineers
  • Machine Learning Engineers
  • Data Engineers
  • Prompt Engineers
  • AI-enabled Analysts and Developers

The KAIM program directly addresses Ethiopia's FinTech talent gap and builds future-ready teams for Kifiya and the broader ecosystem.

tenx Learning Platform

All training is delivered via the tenx platform, a personalized AI-powered learning environment that supports progress tracking, tutor interaction, challenge submissions, and community engagement.

Support for Women & Vulnerable Groups

The program actively supports women, people with disabilities, refugees, returnees, and IDPs through:

  • Dedicated Slack channels
  • Personalized support and mentorship
  • Access to additional resources
  • Networking and community sessions

Application & Admissions

How to Apply

  • Submit application form via 10 Academy's tenx platform
  • Include education background, and proof of residence in Ethiopia.

Week 0: Simulation Week

  • Applicants complete real challenges in Python, SQL, Statistics, and careers
  • Selection based on performance and readiness

Selection Timeline

  • 4 days of evaluation + decisions shared on Day 5

Contact

For any questions or inquiries, please contact the cohort manager via email at makida@10academy.com.

Partners

Kifiya Financial Technology is an industry-leading financial technology company based in Addis Ababa, Ethiopia, focused on enabling access to finance and access to markets through data-driven digital solutions. Founded in 2010, Kifiya simplifies complex financial services, bridging the digital divide and fostering financial and market inclusion across Ethiopia.

The company offers a diverse portfolio of services in payments, agriculture, micro-insurance, and mobility. Kifiya’s mission is to leverage AI-driven data and technology for social good, creating a more inclusive and sustainable future. Recognized for our contributions to Africa’s tech landscape, Kifiya continues to drive economic empowerment and community development.

FAQ

The program is fully funded by Kifiya Financial Technology. Participants will not need to make any deposits or payments during or after the training.

Table of Contents