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Explore the dynamic field of generative artificial intelligence in our Hands-On Artificial Intelligence course, which emphasizes modern AI methodologies through a learning-by-doing approach. This course is designed to equip students with a thorough understanding of both the theoretical foundations and practical implementations of cutting-edge AI technologies. It spans a wide array of topics, including core AI principles, industry best practices, and the deployment of AI systems in real-world scenarios. The curriculum culminates in a final project, where students apply their skills to a research initiative or a practical application. This project not only challenges students to tackle specific problems but also allows them to explore specialized interests, showcasing their capability to develop innovative and effective AI solutions.

Course Schedule

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Fundamentals

Sep 18
Lecture 1Mathematical Fundamentals
📝 Homework 1 Released
Sep 25
Lecture 2Linear Methods

Neural Networks

Oct 9
Lecture 3Multilayer Perceptrons
📝 Homework 2 Released
Oct 16
Lecture 4Convolutional Neural Networks: LeNet, AlexNet and VGG
Homework 1 Due
Oct 23
Lecture 5Advanced Convolutional Neural Networks: Inception, Batch Normalization and ResNet
Oct 30
Lecture 6Computer Vision: Image Augmentation, Fine-tuning and Transfer Learning
📝 Homework 3 Released

Generative Artificial Intelligence

Nov 6
Lecture 7Generative Visual Models
Homework 2 Due
Nov 13
Lecture 8Generative Language Models
Nov 20
Lecture 9Transformers
📝 Homework 4 Released

Large Language Models

Nov 27
Lecture 10Large Language Models
Homework 3 Due 📋 Project Proposal Due
Dec 4
Lecture 11Prompt Engineering
Dec 11
Lecture 12Large Language Model Agents
Homework 4 Due

Final Project

Dec 18
Lecture 13Final Project: Presentations
Dec 25
Lecture 14Final Project: Presentations
Jan 4
📊 Project Report Due
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Shanghai Jiao Tong University