混合式学习课程可以帮助您学习教学设计、有效的评估策略以及整合在线和面对面教学的技巧。您可以培养创造引人入胜的学习体验、利用多媒体资源和促进学生之间合作的技能。许多课程都会介绍学习管理系统(LMS)、视频会议软件和互动平台等工具,展示这些技术如何增强混合式学习环境并支持多样化的学习需求。

University of Colorado Boulder
您将获得的技能: Model Evaluation, Applied Machine Learning, Unsupervised Learning, Classification And Regression Tree (CART), Decision Tree Learning, Artificial Neural Networks, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Random Forest Algorithm, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Statistics
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中级 · 课程 · 1-4 周

Northeastern University
您将获得的技能: Data Mining, Health Informatics, Acute Care, Emerging Technologies, Big Data, Health Technology, Analytics, Data Preprocessing, Clinical Informatics, Machine Learning, Health Care, Applied Machine Learning, Artificial Intelligence, Social Determinants Of Health, Home Health Care, Generative AI, Business Process Improvement
混合 · 课程 · 1-4 周

The University of Tokyo
您将获得的技能: Oral Comprehension, Traffic Flow Optimization, Vocabulary, Water Resources, Literacy, Water Quality, Language Learning, Robotics, Grammar, Augmented Reality, Biochemistry
中级 · 课程 · 1-3 个月

您将获得的技能: Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Artificial Intelligence, Applied Machine Learning, Python Programming, Model Evaluation
中级 · 课程 · 1-4 周

Google Cloud
您将获得的技能: 模型部署, 监督学习, 技术分析, Machine Learning 方法, 统计机器学习, 机器学习, 人工智能和机器学习(AI/ML), 深度学习, 机器学习算法, 财务预测, 人工神经网络, 金融, 应用机器学习, 模型评估, 证券交易, 金融交易, Google 云端平台, 云平台, 预测建模, 时间序列分析和预测
中级 · 课程 · 1-4 周

您将获得的技能: Feature Engineering, Deep Learning, PyTorch (Machine Learning Library), Convolutional Neural Networks, Natural Language Processing, Data Preprocessing, Artificial Neural Networks, Transfer Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, Computer Vision, Jupyter, Predictive Modeling, Machine Learning, Model Evaluation, Data Transformation
混合 · 课程 · 1-3 个月

Duke University
您将获得的技能: 深度学习, 卷积神经网络, 监督学习, 数据科学, 决策树学习, Algorithm, 人工智能和机器学习(AI/ML), 机器学习, 分类与回归树 (CART), 预测分析, 随机森林算法, 无监督学习, 计算机视觉, 模型评估, 逻辑回归, 自然语言处理, 回归分析
中级 · 课程 · 1-3 个月

Universidad de los Andes
您将获得的技能: Recurrent Neural Networks (RNNs), Deep Learning, Convolutional Neural Networks, Generative Model Architectures, Generative Adversarial Networks (GANs), Transfer Learning, Vision Transformer (ViT), Image Analysis, Artificial Neural Networks, Machine Learning Methods, Computer Vision, Network Architecture, Natural Language Processing
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初级 · 课程 · 1-4 周

您将获得的技能: Deep Learning, Tensorflow, Keras (Neural Network Library), Matplotlib, NumPy, Artificial Neural Networks, Python Programming, Pandas (Python Package), Data Science, Artificial Intelligence, Data Preprocessing, Machine Learning, Data Manipulation, Model Evaluation, Classification Algorithms
初级 · 课程 · 3-6 个月

您将获得的技能: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Model Evaluation, Machine Learning Algorithms, Applied Machine Learning, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks, Supervised Learning, Statistical Machine Learning, Anomaly Detection, Classification Algorithms, Performance Tuning
中级 · 课程 · 1-3 个月

Johns Hopkins University
您将获得的技能: 概率与统计, 交互式数据可视化, 统计分析, 统计推理, GitHub, 统计建模, 数据展示, 统计假设检验, 机器学习, Plotly, 闪亮(R 套件), 统计机器学习, R 语言程序设计(中文版), 机器学习算法, 探索性数据分析, 数据可视化, 模型评估, Rmarkdown, 回归分析, 预测建模
中级 · 专项课程 · 3-6 个月

您将获得的技能: Model Evaluation, Applied Machine Learning, Data Preprocessing, Supervised Learning, Machine Learning, Pandas (Python Package), Machine Learning Algorithms, Unsupervised Learning, Feature Engineering, Taxonomy, Data Analysis, Artificial Intelligence, Deep Learning
中级 · 课程 · 1-3 个月