PRISEE - VietAI Ai minicourse

• Collaborated with VietAI to organize a course that provides students with knowledge and practical projects in Machine Learning, Computer Vision, and Natural Language Processing.

• Designed with two modules: 

  • Module 1 covers foundational knowledge in AI and Machine Learning (CNN, Transformer, NLP, Word2Vec, RNN, Attention). It took place over 5 weeks during the summer of 2024, with classes held every Friday for 3 hours each session.

  • Module 2 focuses on programming skills and practical projects (OpenAI API, Prompting, Finetune Model - 32 projects). It took place over 5 weeks during the summer of 2024, with classes held every Wednesday for 2 hours each session.

• Teacher: Nguyen Vinh Tiep (University lecturer - University of Information Technology, Ho Chi Minh City), Tran Duong Viet Hoang (Machine Learning Engineer, Snorkel AI).

• Total participants of 100 students from 30 schools and universities among 7 provinces and cities in Vietnam (list trường ra - Link)

Module 1: Deep Learning

This course is designed to provide students from across the city with a solid foundation in deep learning concepts and techniques. Over the course of six engaging lessons, participants will explore the fundamentals of transformers, gain insights into machine learning and basic models, and delve into specialized topics such as Convolutional Neural Networks (CNNs), Natural Language Processing (NLP) with Word2Vec, Recurrent Neural Networks (RNNs), and the powerful attention mechanism. By the end of this module, students will have a comprehensive understanding of deep learning and its applications, equipping them with essential skills for future studies and projects in artificial intelligence.

Lesson 1: Transformer 

Lesson 2: Machine learning overview and basic models 

Lesson 3: CNN 

Lesson 4: NLP & Word2Vec 

Lesson 5: RNN Lesson 6: Attention 

Module 2: GenAI API Programming

This module is designed to equip learners with practical skills in Artificial Intelligence, focusing on essential tools and techniques. Throughout five informative lessons, participants will engage with the OpenAI API through a hands-on tutorial, learn effective prompting strategies, explore the NTI interface for ChatGPT, and understand the intricacies of model fine-tuning. We will also dive into the exciting process of fine-tuning models like GPT-3.5 and Llama2. By the end of this module, students will have gained valuable experience and knowledge, empowering them to apply AI solutions in real-world scenarios. 

Lesson 1: OpenAI API Tutorial 

Lesson 2: Prompting 

Lesson 3: NTI Interface for ChatGPT 

Lesson 4: Finetune model 

Lesson 5: Finetune GPT 3.5 - Llama2