空中机器人课程
空中机器人课程可以帮助您学习无人机设计、飞行动力学、导航系统和传感器集成。您可以掌握自主飞行编程、数据收集技术和实时决策的技能。许多课程都会介绍一些工具，如用于模拟的 MATLAB、用于机器人系统的 ROS 以及各种无人机平台，让您能够将自己的技能应用到实际场景中，如空中测绘、监控和环境监测。
热门空中机器人课程和认证
状态：免费试用您将获得的技能: PyTorch (Machine Learning Library), Model Evaluation, Deep Learning, Machine Learning, Artificial Neural Networks, Artificial Intelligence, Python Programming, Data Preprocessing, Regression Analysis, Software Installation, System Configuration, Development Environment, Performance Tuning
状态：免费试用Fractal Analytics
您将获得的技能: Python 程序设计, 大型语言模型, 面向对象编程（OOP）, 调试, 计算机编程, 人工神经网络, 生成模型架构, 批判性思维, 生成式人工智能, 语义网, Prompt Engineering
状态：免费试用Johns Hopkins University
您将获得的技能: 数字信号处理, 深度学习, 数据结构, 数据处理, 线性代数, 数据转换, 卷积神经网络, 性能调整, 人工神经网络, 数据科学, Algorithm, 数值分析, 机器学习, 图像分析
状态：预览DeepLearning.AI
您将获得的技能: Deep Learning, Artificial Neural Networks, Supervised Learning, Artificial Intelligence, Convolutional Neural Networks, Computer Vision, Recurrent Neural Networks (RNNs), Machine Learning
状态：免费试用Duke University
您将获得的技能: Responsible AI, Large Language Modeling, Generative AI, Artificial Intelligence, Model Evaluation, Python Programming, Applied Machine Learning, Machine Learning, Visualization (Computer Graphics), Deep Learning, Plot (Graphics), Artificial Neural Networks
状态：免费试用University of Illinois Urbana-Champaign
您将获得的技能: Python 程序设计, 模型评估, 深度学习, 无监督学习, 嵌入, 自动编码器, 降维, 医学影像, 健康信息学, 卷积神经网络, 模型部署, 应用机器学习, 递归神经网络 (RNN), 人工神经网络, 预测建模, 图像分析
您将获得的技能: Tensorflow, Natural Language Processing, Python Programming, Machine Learning Methods, Recurrent Neural Networks (RNNs), Data Preprocessing, Artificial Neural Networks, Machine Learning, Deep Learning
您将获得的技能: Regression Analysis, Exploratory Data Analysis, Model Evaluation, Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Machine Learning, Data Preprocessing, Deep Learning, Statistical Analysis, Data Analysis, Artificial Neural Networks, Data Import/Export, Matplotlib, Python Programming
状态：新状态：免费试用您将获得的技能: Natural Language Processing, Large Language Modeling, Model Evaluation, Recurrent Neural Networks (RNNs), Classification Algorithms, Data Ethics, Responsible AI, Text Mining, Transfer Learning, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Neural Networks, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Data Processing, Embeddings, Machine Learning, Data Analysis, Data Cleansing
Google Cloud
您将获得的技能: Google 云端平台, 云计算, 脚本, 开发环境, 深度学习, 张力流, 监督学习, 机器学习, 人工神经网络
Google Cloud
您将获得的技能: 深度学习, Machine Learning 方法, 自然语言处理, 性能调整, 递归神经网络 (RNN), 人工神经网络
状态：预览您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Model Evaluation, Machine Learning Methods, Machine Learning, Machine Learning Algorithms, Artificial Neural Networks, Computer Science, Deep Learning, Supervised Learning, Applied Machine Learning, Data Ethics, Recurrent Neural Networks (RNNs), Responsible AI, Convolutional Neural Networks, Data Science, Classification Algorithms
总之，以下是 10 最受欢迎的 aerial robotics 课程
- Foundations and Core Concepts of PyTorch: Packt
- 使用生成式人工智能编码: Fractal Analytics
- CUDA 高级库: Johns Hopkins University
- Нейронные сети и глубокое обучение: DeepLearning.AI
- Explainable Machine Learning (XAI): Duke University
- 医疗保健领域的深度学习方法: University of Illinois Urbana-Champaign
- Create a Superhero Name Generator with TensorFlow: Coursera
- Mining Quality Prediction Using Machine & Deep Learning: Coursera
- Mastering NLP: Tokenization, Sentiment Analysis & Neural MT: Edureka
- 学习 TensorFlow：机器学习的 "你好世界: Google Cloud
