混合式学习课程
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。
热门混合式学习课程和认证
状态：免费试用您将获得的技能: Recurrent Neural Networks (RNNs), Embeddings, Deep Learning, Convolutional Neural Networks, Artificial Neural Networks, Python Programming, Classification Algorithms, Data Preprocessing, Model Evaluation
您将获得的技能: Unsupervised Learning, Dimensionality Reduction, Supervised Learning, R Programming, Applied Machine Learning, R (Software), Classification Algorithms, Machine Learning, Decision Tree Learning, Data Science, Ggplot2, Feature Engineering, Data Preprocessing, Statistical Programming, Predictive Modeling, Data Manipulation, Model Evaluation, Regression Analysis
您将获得的技能: Unsupervised Learning, Machine Learning Algorithms, Applied Machine Learning, Machine Learning, Scikit Learn (Machine Learning Library), Statistical Methods, Dimensionality Reduction, Algorithms, NumPy, Python Programming
状态：免费试用您将获得的技能: Predictive Modeling, Responsible AI, Predictive Analytics, Machine Learning, Data Ethics, Data Preprocessing, Technical Management, Model Evaluation, MLOps (Machine Learning Operations), Applied Machine Learning, Data-Driven Decision-Making, Statistical Modeling, Performance Reporting, Supervised Learning, Business Ethics, Decision Tree Learning, Artificial Intelligence and Machine Learning (AI/ML), Business Analytics, Data Science, Machine Learning Algorithms
Google Cloud
您将获得的技能: 预测建模, Apache Spark, 应用机器学习, 数据预处理, 大数据, Google 云端平台, 逻辑回归, 模型评估
状态：免费试用您将获得的技能: Feature Engineering, Responsible AI, Model Deployment, Tensorflow, Exploratory Data Analysis, Data Quality, Machine Learning, Data Preprocessing, Applied Machine Learning, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Google Cloud Platform, MLOps (Machine Learning Operations), Data Cleansing, Supervised Learning, Dataflow, Artificial Neural Networks, Model Evaluation, Logistic Regression, Performance Tuning
Commonwealth Education Trust
您将获得的技能: 课程规划, 同行评审, 撰写报告, 统计分析, 教育与培训, 调查, 学生参与, 教学策略, 教学和课程设计, 教学
状态：预览National Taiwan University
您将获得的技能: Feature Engineering, Autoencoders, Machine Learning Algorithms, Supervised Learning, Decision Tree Learning, Random Forest Algorithm, Applied Machine Learning, Machine Learning, Classification Algorithms, Deep Learning, Model Evaluation, Artificial Neural Networks, Dimensionality Reduction, Embeddings, Logistic Regression
状态：预览您将获得的技能: MLOps (Machine Learning Operations), Model Evaluation, Google Cloud Platform, Model Deployment, Cloud Management, Application Lifecycle Management, DevOps, Cloud Deployment, Applied Machine Learning, Continuous Deployment, Automation
状态：预览您将获得的技能: Predictive Modeling, Predictive Analytics, Marketing Analytics, Statistical Machine Learning, Machine Learning, Data Science, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Statistical Analysis
状态：免费试用New York University
您将获得的技能: 风险, 衍生产品, 市场数据, 强化学习, 机器学习, 信用风险, 金融交易, 市场动态, 金融, 金融建模, 市场流动性, 金融市场
状态：新状态：预览您将获得的技能: Data Preprocessing, Tensorflow, Scikit Learn (Machine Learning Library), Machine Learning, Feature Engineering, Deep Learning, Convolutional Neural Networks, Matplotlib, Jupyter, Python Programming, NumPy, Data Manipulation, Artificial Neural Networks, Seaborn, Development Environment, Pandas (Python Package), Regression Analysis
总之，以下是 10 最受欢迎的 blended learning 课程
- Natural Language Processing - Deep Learning Models in Python: Packt
- Clustering and Classification with Machine Learning in R: Packt
- Cluster Analysis and Unsupervised Machine Learning in Python: Packt
- Machine Learning Rock Star – the End-to-End Practice: SAS
- 在 Google Cloud Dataproc 上使用 Spark 进行机器学习: Google Cloud
- Machine Learning with TensorFlow on Google Cloud en Español: Google Cloud
- 为学习而教的基础学生评估入门: Commonwealth Education Trust
- 機器學習技法 (Machine Learning Techniques): National Taiwan University
- Machine Learning Operations (MLOps): Getting Started - Português Brasileiro: Google Cloud
- Four Rare Machine Learning Skills All Data Scientists Need: SAS
