Mastering Multilingual GenAI Open-Weight for Indic Language

  • BeginnerLevel

  • 1 hrs 0 minsDuration

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About this Course

  • Learn to develop multilingual AI models using open-weight architectures, focusing on low-resource languages, fine-tuning techniques, and ethical AI practices.
  • Focus on training and fine-tuning AI models for low-resource Indic languages, ensuring high accuracy, inclusivity, and ethical AI development.
  • Ensure the fairness and reduce bias in efficient multilingual AI model development.

Learning Outcomes

Build Multilingual AI

Learn to create AI models for diverse languages on low-resource ones.

Hands-On Model Training

Get hands-on experience with good models and multilingual data.

Ensure Fair & Safe AI

mplement strategies for safer AI models in global applications.

Who Should Enroll

  • Developers aiming to build multilingual AI models for low-resource languages using open-weight architectures.
  • Tech innovators seeking to create scalable AI systems that support diverse linguistic communities
  • Data scientists and professionals exploring instruction fine-tuning, bias mitigation for global applications.

Course Curriculum

Explore a comprehensive curriculum covering Python, machine learning models, deep learning techniques, and AI applications.

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  1. 1. Introduction

  2. 2. Importance of Multilingual

  3. 3. Training for Multilingual Gen AI

  4. 4. Instruction Fine-Tuning Data for Multilingual

  5. 5. Measuring Performance for Multilingual

  6. 6. Building a Model

  7. 7. Human Preferences

  8. 8. Curse of Multilinguality

  9. 9. Coding Hands-On

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Viraat Aryabumi

Research Scholar, Cohere

Viraat is a Research Scholar at Cohere for AI, where he contributed to the Aya Project and Aya-101 model. led Machine Learning at Aiara and was a Machine Learning Scientist at Amazon. He holds a Master's in AI from the University of Edinburgh.

Get this Course Now

With this course you’ll get

  • 1 hrs 0 mins

    Duration

  • Viraat Aryabumi

    Instructor

  • Beginner

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility

Frequently Asked Questions

Looking for answers to other questions?

A basic understanding of AI and machine learning concepts is recommended. Familiarity with natural language processing (NLP) will be helpful but is not mandatory

You'll work with state-of-the-art open-weight models, instruction fine-tuning techniques, and the Aya dataset.

The course focuses on training models that perform well on low-resource languages, particularly Indic languages, through the use of the Aya dataset, multilingual instruction fine-tuning, and bias mitigation techniques.

Yes, the course includes practical coding exercises and real-world projects where you will build and fine-tune multilingual AI models, with a focus on tackling real-world challenges in low-resource language modeling.

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