Fusemachines AI Fellowship 2026

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Nepal

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A comprehensive six-month course to help you in advancing your career to the next level.

Application Deadline:

March 20, 2026

Class starts on:

April 20, 2026

Apply Now Download Syllabus

Post-fellowship outcomes

Hear what our fellows have to say about the program

About AI Fellowship Program

The Fusemachines AI Fellowship is a six-month, primarily online program designed to build strong, practical AI capabilities. Led by experienced AI practitioners, the fellowship focuses on applied learning through hands-on work and real-world problem solving.

The program is refreshed each year to reflect how AI is actually used in industry today. Fellows receive a full scholarship, earn a Microdegree™ in Artificial Intelligence, and gain exposure to real AI projects that prepare them for professional opportunities in the global AI ecosystem.

AI Fellowship
  • Full scholarship
  • Job placement opportunities
  • Microdegree™ in AI certification
1100+
Certified Fusemachines AI Fellows in USA, Nepal, Dominican Republic, Rwanda, Burkina Faso & Latin America.
Course Overview

Course overview

The Fusemachines AI Fellowship is a Microdegree™ program in Artificial Intelligence designed to help participants build practical AI and data science capabilities for real-world application. Delivered over six months, the program combines guided learning, mentorship, and hands-on project work.

Over the course of the fellowship, participants will:

  • Participate in guided learning sessions and mentor-led discussions
  • Learn how to collect, clean, map, and analyze data for AI use cases
  • Work through structured learning modules aligned with their project goals
  • Build strong foundations in machine learning, deep learning, and core AI concepts
  • Complete independent and team-based projects
  • Apply their learning by building and deploying real-world AI solutions
Apply Now Download Syllabus

AI stack fundamentals you’ll learn

To build impactful AI solutions, it's essential to master the full AI stack. In this program, you'll learn key components like data, infrastructure, frameworks, APIs, and deployment tools to create scalable, real-world applications.

AI stack
Monitoring and Maintenance

Logging system, monitor, model maintenance

Deployment

Deployment framework, containerization tools, orchestration systems

Application

Software Engineering to integrate AI into applications to provide value to end-users

Model Training

Optimization techniques, validation, evaluation, training frameworks and experimentation

Data

Storage & management of data: Database, Data lakes, Data warehouses, Data processing

Algorithm

ML algorithms, statistical models, computational methods

Hardware

Physical Infrastructure: Servers, GPU, TPU, and other components

Monitoring and Maintenance

Logging system, monitor, model maintenance

Deployment

Deployment framework, containerization tools, orchestration systems

Application

Software Engineering to integrate AI into applications to provide value to end-users

Model Training

Optimization techniques, validation, evaluation, training frameworks and experimentation

Algorithm

ML algorithms, statistical models, computational methods

Data

Storage & management of data: Database, Data lakes, Data warehouses, Data processings

Hardware

Physical Infrastructure: Servers, GPU, TPU, and other components

Syllabus highlights

Cources

Generative AI

  • Large language models (LLMs)
  • Image generations
  • Prompt engineering
Cources

Machine Learning

  • Regression and Classification
  • Clustering techniques
  • Model evaluation metrics
  • Reinforcement learning concepts
Cources

Computer Vision

  • Object detection
  • Image segmentation
  • Image generation techniques
Cources

Natural Language Processing

  • Text extraction
  • Named entity recognition (NER)
  • Sentiment analysis
Cources

Neural Network and Deep Learning

  • Neural network fundamentals
  • TensorFlow and PyTorch
  • Model training and fine-tuning
  • CNNs, RNNs, GANs and modern architectures
Cources

MLOPs

  • Model deployment basics
  • Monitoring and evaluation
  • ML as a service concepts

What's included

  • Guided learning led by AI practitioners

    Structured guidance and feedback from experienced AI professionals throughout the program

  • Access to the Fuse AI learning platform and community

    Learning resources, project tracking, and peer collaboration in one place

  • Mentorship and expert-led working sessions

    Project reviews, idea refinement, and focused sessions on relevant AI topics

  • Curated updates on AI trends and applications

    Regular insights on how AI is being applied across industries

  • Team-based and independent project work

    Opportunities to collaborate with peers or work independently on AI projects

  • Active learner community and collaboration spaces

    Discussion forums and shared spaces to learn, build, and problem-solve together

  • Microdegree™ in Artificial Intelligence

    Credential awarded upon successful completion of the program

What's included

Prerequisites

The AI Fellowship is designed for motivated learners with strong technical foundations, regardless of academic discipline. Applicants may come from computer science, engineering, or other domains where analytical and technical skills are applied.

To be successful in the program, applicants should have:

  • A solid foundation in mathematics, including linear algebra, probability, statistics, and basic calculus
  • Working knowledge of python programming and core programming concepts
  • Familiarity with data structures and basic data handling
  • Proficiency in english for technical communication and collaboration
  • A strong problem-solving mindset and willingness to learn in a collaborative environment
Prerequisites

All applicants are required to complete an online entrance assessment to evaluate technical readiness and problem-solving ability.

Shortlisted candidates are invited for interviews as part of the selection process.

Machine Learning

Why join our AI Fellowship?

  • Learn from experienced AI practitioners through guided sessions, mentorship, and project reviews
  • Build strong foundations in applied AI, including machine learning, deep learning, and generative AI
  • Work alongside a diverse community of peers, mentors, and alumni from across regions and disciplines
  • Develop and refine an AI project from idea through implementation with structured support
  • Gain exposure to deploying AI systems in real environments and understanding production constraints
  • Grow as an AI builder, whether your path leads toward applied engineering, research, or founding AI-driven ventures

AI Fellowship journey

AI Fellowship
Step 1
Online application
Deadline: March 20, 2026

Fill out and submit application form providing relevant details

Step 2
Online entrance exam
March 23 - March 30, 2026

Take online entrance exam to assess relevant skills

Step 3
Online interview
April 1 - April 10, 2026

Shortlisted candidates passing the entrance exam will be interviewed by a member of our team

Step 4
Enrollment and onboarding
April 20, 2026

After a successful interview, you will be enrolled and onboarded into the program

Program leaders

Our PhDs, AI industry experts and faculty from top universities around the world designed the course to provide advanced AI skills, career opportunities, and a lasting impact.

Machine Learning
Sameer Maskey, PhD
Founder and CEO,
Fusemachines Inc.
Adj. Associate Professor, Columbia University
Bülent Uyaniker, PhD
Bülent Uyaniker, PhD
Sr. Data Scientists,
Fusemachines Inc.
Former faculty of Univ. of British Columbia
Rakesh Kumar Katuwal
Rakesh Katuwal, PhD
Sr. Director of AI Services,
Fusemachines
Rojesh Man Shikhrakar
Rojesh M. Shikhrakar
Director of Talent Dev and AI Education, Fusemachines
Visiting Faculty at Kathmandu University, Nepal

Past Graduates Projects

Past Graduates Projects
Fuse Nirikshak

Online proctoring tool for online exam

Watch Demo
Past Graduates Projects
Nepali Document & Record Management System

Organizing managing and retrieving Nepali language documents.

Watch Demo
Past Graduates Projects
MUSE

A personal museum guide

Watch Demo
Past Graduates Projects
Local Tour Guide

Chatbot that helps tourist plan their travel experience

Watch Demo
Past Graduates Projects
Automatic Speech Recognition

Speech sentiment analysis and text summarization

Watch Demo
Past Graduates Projects
Code-Grader-Feedback

Automating code evaluation

Watch Demo

Program FAQs

Only applicants who are nepali are eligible to apply for The AI fellowship Nepal 2026. All classes will be conducted on nepal time. Nepalese residing outside need to manage their availability according to the course schedule.

We have created a detailed syllabus for all AI fellows. You can download it and get course topics for the AI Fellowship period.

Fusemachines AI Fellowship can be pursued by students and engineers who already possess Computer Science and Mathematics foundations. These prerequisites include basic knowledge of linear algebra, calculus, probability, and statistics. The program also requires programming experience in Python and know-how in the implementation of object-oriented programming, data structures and algorithms. Participants should have the ability to run programs and interpret output from a command line terminal or shell. Ideally, students fitting the enrollment criteria generally include 4th-year graduating students who check off the specifications. Prior to enrollment, students will be required to undergo an eligibility test to check if they have enough foundational skills to take the course.

After the completion of the courses in the program, you will develop a solid understanding of Machine Learning, Deep Learning algorithms, LLMs and Agentic AI, with an advanced understanding of underlying concepts. You will be able to then select and apply appropriate algorithms, libraries, and frameworks techniques for different AI problems and assess the performance, evaluate and compare different AI models to design and deploy end-to-end pipelines. You will also be able to run experiments to change code details to improve the algorithm.

We have 100 seats available for this 2026 fellowship. AI fellows should give their best performance in examination and interview stage. Only the best candidates will get selected.

Applicants for the AI Fellowship will receive updates via email prior to enrollment. Once enrolled, updates will continue to be provided through email and in the announcement section of the platform. Enrolled participants can also post questions in the forum section. Enrollment in the platform will occur within a few days after submitting the application form.

Active participation in sessions, following up with mentors is first and foremost, AI fellows should actively complete assigned assignments, chapter wise quizzes , final exam and capstone projects . Passive participation will be considered drop out from the program.

Yes, completing a capstone project is a core requirement for graduation from the AI Fellowship. To support your success, mentors will be assigned to provide guidance throughout the program. Students have the flexibility to work individually or collaborate in teams. Certain APIs, Cloud Services and GPUs may be provided to certain projects on a case-by-case basis.

The course is 24 Weeks long.

Classes will be held in the evening time usually after 5PM. The course schedule will be announced after the selection.

These courses are not university-accredited courses. They are provided by Fusemachines and are recognized by many other organizations.

Exams are held in the Fuse classroom virtually. The date of examination is mentioned on the website.

Launch Your AI Career

Your Journey Starts with the Fuse AI Fellowship Program!

Apply now