强化学习课程
Reinforcement Learning 课程可以帮助您学习马尔可夫决策过程、奖励系统和策略优化等关键概念。您可以掌握算法设计、模拟环境和评估代理性能方面的技能。许多课程介绍了 TensorFlow 和 OpenAI Gym 等工具，这些工具支持在实际场景中实施和测试强化学习算法。
热门强化学习课程和认证
状态：免费试用您将获得的技能: Prompt Engineering, Exploratory Data Analysis, Prompt Patterns, LangChain, Large Language Modeling, Retrieval-Augmented Generation, Model Evaluation, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, LLM Application, Keras (Neural Network Library), Data Transformation, Supervised Learning, Responsible AI, Vector Databases, Data Import/Export
状态：新状态：免费试用您将获得的技能: Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Keras (Neural Network Library), Image Analysis, Deep Learning, Tensorflow, Computer Vision, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Data Manipulation, Data Transformation, Financial Forecasting, Data Visualization, Time Series Analysis and Forecasting, Exploratory Data Analysis, Python Programming, Customer Analysis, Applied Machine Learning, Cloud Computing
状态：免费试用您将获得的技能: 面向对象编程（OOP）, 数据结构, JSON, 计算机编程, Python 程序设计, 还原式 API, 文件输入/输出, Jupyter, 数据操作, Pandas（Python 软件包）, NumPy, 网页抓取, 数据导入/导出, 编程原则, 自动化, 应用编程接口 (API), 数据分析
状态：新状态：免费试用您将获得的技能: Risk Analysis, Risk Management Framework, Decision Making, AI Enablement, Continuous Deployment, Project Management Software, Strategic Decision-Making, Operational Analysis, Release Management, Project Planning, Predictive Modeling, A/B Testing, Business Priorities, Operational Efficiency, Algorithms, Experimentation, Advanced Analytics, Procedure Development, Product Planning, Product Development
状态：免费试用University of California, Irvine
您将获得的技能: 英语, 语言学习, 语言能力, 语法, 词汇
状态：新状态：免费试用您将获得的技能: MLOps (Machine Learning Operations), Responsible AI, CI/CD, Model Deployment, Continuous Integration, Continuous Delivery, Continuous Deployment, Cloud Platforms, Model Evaluation, Automation, Data Governance, Data Pipelines, Performance Tuning, Continuous Monitoring, Performance Analysis
状态：免费试用Johns Hopkins University
您将获得的技能: 机器学习, Knitr, 统计编程, 降维, GitHub, R（软件）, 统计分析, 数据操作, 绘图（图形）, Rmarkdown, 数据整合, 数据科学, R 语言程序设计（中文版）, 数据可视化软件, 统计可视化, 数据共享, Ggplot2, 数据清理, 版本控制, 探索性数据分析
状态：免费试用Imperial College London
您将获得的技能: 应用数学, Algorithm, 统计, 数据预处理, 回归分析, 人工神经网络, 微积分, 衍生产品, 无监督学习, Python 程序设计, 线性代数, 数学建模, 功能工程, 机器学习算法, Jupyter, NumPy, 高等数学, 降维
状态：新状态：免费试用Pearson
您将获得的技能: Large Language Modeling, Deep Learning, Prompt Engineering, Image Analysis, Model Deployment, Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Tensorflow, Vision Transformer (ViT), LLM Application, Transfer Learning, Computer Vision, Responsible AI, Natural Language Processing, Embeddings, Keras (Neural Network Library), Generative AI, Artificial Neural Networks, Multimodal Prompts
状态：免费试用IBM
您将获得的技能: 机器学习, 数据转换, 交互式数据可视化, 仪表板, 数据展示, Python 程序设计, 数据操作, 数据科学, 数据可视化软件, 数据清理, 网页抓取, Pandas（Python 软件包）, 数据可视化, Plotly, Model Evaluation, 数据导入/导出, 预测建模, 编程原则, 探索性数据分析, 数据分析
状态：免费试用IBM
您将获得的技能: 计算机视觉, 机器学习, LangChain, Prompt Engineering, 工程软件, 响应式网页设计, ChatGPT, 大型语言模型, 还原式 API, 生成式人工智能, Python 程序设计, 数据科学, 软件开发生命周期, 软件架构, AI 工作流程, IBM 云, 数据导入/导出, 提示模式, 检索-增强生成, 负责任的人工智能
状态：免费试用IBM
您将获得的技能: 机器学习, 统计推理, 数据预处理, 异常检测, 回归分析, 无监督学习, 监督学习, 分类算法, 统计假设检验, 数据访问, 逻辑回归, 预测建模, 探索性数据分析, 应用机器学习, 功能工程, 机器学习算法, Model Evaluation, 降维, Scikit-learn （机器学习库）, 统计方法
与 reinforcement learning 相关的搜索
总之，以下是 10 最受欢迎的 reinforcement learning 课程
- IBM Generative AI Engineering: IBM
- Deep Learning with Python: CNN, ANN & RNN: EDUCBA
- 用于数据科学、人工智能和开发的 Python: IBM
- Optimize AI: Plan, Evaluate, and Learn: Coursera
- 学习英语：初级语法: University of California, Irvine
- Automate, Validate, and Promote ML Models Safely: Coursera
- 数据科学：使用 R 的基础: Johns Hopkins University
- 机器学习数学: Imperial College London
- Learning Deep Learning: Pearson
- 应用数据科学: IBM
