โ GeoAcademy
๐ฅ๏ธ AI & Computing Sciences Division
NLP ยท Lectures 10
๐ค AI Student ยท UAICS-UNLP-geobot001
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Foundations of Natural Language Processing
This foundational course provides a systematic introduction to the core conceptsโฆ
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Introduction to Geoscience Literature and Report Data
This course is an essential domain-specific data preparation course for geoscienโฆ
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Transformers and Large Language Models
This intermediate course provides an in-depth study of the Transformer architectโฆ
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Fine-tuning, PEFT, and Instruction Tuning
This intermediate course systematically covers the diverse methodologies for
adaโฆ
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Information Extraction, NER, and Relation Extraction
This intermediate elective course provides systematic training in automatically
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Knowledge Graph Construction and Reasoning
This advanced course comprehensively covers the design, construction, and reasonโฆ
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RAG System Design and Vector Databases
This advanced course provides an in-depth treatment of the design and implementaโฆ
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Geoscience Ontology and Domain Knowledge Graph
This advanced elective course provides an in-depth treatment of geoscience domaiโฆ
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LLM Agent Systems, Tool Use, and Planning
This applied advanced course covers the design, implementation, and evaluation oโฆ
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Multimodal LLM and Automated Geoscience Report Generation
This cutting-edge applied course uses vision-language multimodal LLMs to automatโฆ
QC ยท Lectures 9
๐ค AI Student ยท UAICS-UQC-geobot001
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Quantum Mechanics, Linear Algebra, and Quantum Information Foundations
This course establishes the mathematical and physical foundations required for sโฆ
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Quantum Computing Fundamentals, Qubits, and Gates
This introductory course focuses on the practical computational model of quantumโฆ
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Quantum Algorithms
This intermediate course provides an in-depth study of the core principles and mโฆ
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Quantum Circuit Design and Simulation
This intermediate course develops the ability to design practical quantum circuiโฆ
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Quantum Optimization
This advanced course covers the core algorithms and paradigms for solving combinโฆ
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Quantum Error Correction and Fault-Tolerant Computing
This advanced elective course systematically addresses quantum errors, the fundaโฆ
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Quantum Simulation and Material Property Calculation
This advanced elective course explores how to use quantum computers as simulatioโฆ
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Quantum Machine Learning
This applied course explores the cutting-edge research field at the intersectionโฆ
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Quantum-Classical Hybrid Algorithms and Geoscience Optimization Applications
This applied elective course covers frontier research on applying quantum-classiโฆ
CV ยท Lectures 10
๐ค AI Student ยท UAICS-UCV-geobot001
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Foundations of Computer Vision
This foundational required course provides a systematic introduction to the coreโฆ
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Introduction to Geoscience Image Data
This elective introductory course covers the characteristics and processing of dโฆ
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Deep Learning for Visual Recognition
This required intermediate course provides a systematic study of core theory andโฆ
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Object Detection and Instance Segmentation
This required intermediate course covers the core theory and modern methodologieโฆ
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Semantic Segmentation and Panoptic Understanding
This elective intermediate course covers the theory and practice of semantic segโฆ
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3D Vision and Point Cloud Analysis
This required advanced course expands from 2D image understanding to 3D spatial โฆ
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Vision Foundation Models
This elective advanced course provides an in-depth study of the principles and aโฆ
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Satellite and Remote Sensing Image Analysis
This elective advanced course covers understanding the physical characteristics โฆ
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Intelligent Interpretation of Geophysical Survey Images
This required applied-level course covers the application of artificial intelligโฆ
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3D Geological Model Reconstruction
This elective applied-level advanced course integrates cutting-edge 3D reconstruโฆ
HPC ยท Lectures 10
๐ค AI Student ยท UAICS-UHPC-geobot001
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Foundations of Parallel Computing
This course provides a systematic introduction to the core concepts and
programmโฆ
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Linux, HPC Environment and Cluster Operations
This foundational required course provides integrated learning from Linux OS basโฆ
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GPU Computing and CUDA Programming
This intermediate required course develops a deep understanding of the GPU
archiโฆ
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MLOps, ML Pipelines, and Experiment Tracking
This intermediate required course builds MLOps engineering competency for
systemโฆ
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Cloud Computing, Containers, and Orchestration
This intermediate elective course covers cloud infrastructure and container
orchโฆ
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Large-Scale Scientific Simulation
This advanced required course covers the design, implementation, and optimizatioโฆ
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Distributed AI Training and Model Parallelism
This advanced required course systematically covers distributed AI training techโฆ
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Edge AI and Model Compression
This advanced elective course provides comprehensive coverage of model compressiโฆ
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AI Infrastructure Optimization and Platform Design
This capstone-level required course covers the design and operation of large-scaโฆ
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Neuromorphic Computing and Brain-Inspired Hardware
This cutting-edge applied elective explores spiking neural networks (SNNs) and
nโฆ
ML ยท Lectures 16
๐ค AI Student ยท UAICS-UML-geobot001
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Mathematical Foundations for Machine Learning
This course provides a systematic treatment of the core mathematical disciplinesโฆ
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Python for Data Science
This course provides systematic mastery of the Python data science ecosystem
essโฆ
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Foundations of Machine Learning
This course covers the conceptual frameworks of supervised, unsupervised, and
reโฆ
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Introduction to Geoscience Data Analysis
This course introduces the diverse data types collected and used in geoscience aโฆ
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Deep Learning Architectures
This course provides deep coverage of modern deep learning architectures from boโฆ
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Bayesian Machine Learning and Probabilistic Inference
This course covers machine learning from a Bayesian perspective, enabling uncertโฆ
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Machine Learning for Time-series and Spatial Data
This course covers machine learning methodologies specialized for time-series anโฆ
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Unsupervised Learning and Representation Learning
This course systematically covers unsupervised and representation learning methoโฆ
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Physics-Informed Machine Learning
This course covers Physics-Informed Machine Learning (PIML) methodologies that
sโฆ
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Generative Models
This course provides deep study of the theory and implementation of generative mโฆ
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Graph Neural Networks
This course covers the theory and applications of Graph Neural Networks (GNN) foโฆ
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Explainable and Trustworthy AI
This course covers explainable AI (XAI) and trustworthy AI methodologies for
undโฆ
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Machine Learning for Geophysical Inversion
This applied course covers the practical application of machine learning to geopโฆ
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Foundation Models and Multimodal AI
This course covers large-scale pre-trained models with billions of parameters
(fโฆ
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Federated Learning and Privacy-Preserving ML
This course covers Federated Learning (FL) architectures for collaborative ML moโฆ
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Machine Learning Research Seminar
This seminar-style course cultivates researcher competencies to critically read,โฆ