个结果，搜索词为 "artificial intelligence and machine learning (ai/ml)"
IBM
您将获得的技能: 自然语言处理, 负责任的人工智能, 生成式人工智能, 风险缓解, 机器人, 人工智能扫盲, 法学硕士申请, 生成模型架构
Amazon Web Services
您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, AI literacy, Machine Learning, Digital Transformation
多位教师
您将获得的技能: 深度学习, 负责任的人工智能, 模型培训, Jupyter, 应用机器学习, 预测建模, 数据伦理, 分类算法, 无监督学习, Model Evaluation, Transfer Learning, 机器学习, 机器学习算法, 监督学习, 机器学习方法, NumPy, 迁移学习, 人工智能, Scikit Learn（机器学习库）, 模型评估, 张力流, 决策树学习
University of Pennsylvania
您将获得的技能: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Statistical Modeling, Python Programming, Supervised Learning, Machine Learning, Data Processing, Agentic systems, Artificial Intelligence, Algorithms, AI literacy
您将获得的技能: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Application Deployment, Software Development, Machine Learning
Microsoft
您将获得的技能: 数据管理, 数据基础设施, 应用程序部署, MLOps（机器学习运营）, 人工智能和机器学习（AI/ML）, 数据管道, 人工智能工作流程, 数据预处理, 应用框架, 模型部署, 人工智能集成, Data Management, Model Evaluation, 机器学习, 数据安全, 可扩展性, 数据清理, 基础设施架构, 人工智能, 模型评估
是什么让您今天来到 Coursera？
Microsoft
您将获得的技能: Unsupervised Learning, Fine-tuning, Model Deployment, Generative AI, Large Language Modeling, Data Management, Generative Model Architectures, Natural Language Processing, MLOps (Machine Learning Operations), Supervised Learning, Microsoft Azure, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Infrastructure Architecture, LLM Application, Responsible AI, Generative AI Agents, Data Preprocessing, Model Optimization
Google Cloud
您将获得的技能: Prompt Engineering, 数据基础设施, MLOps（机器学习运营）, 生成式人工智能, 应用机器学习, 多模式提示, 模型培训, 模型部署, Google Cloud 平台, 及时工程, 人工智能工作流程, Model Evaluation, 机器学习, 生成式人工智能代理, Google 双子座, 监督学习, 张力流, 人工智能, 模型评估, 生成模型架构, 云基础设施
University of Illinois Urbana-Champaign
您将获得的技能: Education Software and Technology, Responsible AI, Wealth Management, Machine Learning Methods, Supervised Learning, Machine Learning, Financial Services, Applied Machine Learning, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Learning Management Systems, Digital pedagogy, Artificial Intelligence, Compliance Training, AI literacy, AI Enablement, Rapport Building, FinTech, AI Integrations, Financial Planning
您将获得的技能: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Artificial Intelligence, Agentic systems, Machine Learning Algorithms, Bayesian Network, Applied Machine Learning, Computational Logic, Machine Learning, Unsupervised Learning, Agentic Workflows, Bayesian Statistics, Artificial Neural Networks, Reinforcement Learning, Decision Intelligence, Markov Model, Algorithms, Programming Principles, Probability & Statistics
您将获得的技能: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms
Microsoft
您将获得的技能: 微软 Azure, 预测建模, 模型培训, 应用机器学习, 无代码开发, 人工智能和机器学习（AI/ML）, 模型部署, 分类算法, 无监督学习, 机器学习, 机器学习算法, 回归分析, 机器学习软件, 监督学习, Microsoft Azure, 人工智能
总之，以下是 10 最受欢迎的 artificial intelligence and machine learning (ai/ml) 课程
- 人工智能（AI）简介: IBM
- Fundamentals of Machine Learning and Artificial Intelligence: Amazon Web Services
- 机器学习: DeepLearning.AI
- AI and Machine Learning Essentials with Python: University of Pennsylvania
- Machine Learning and Deep Learning for Software Engineers: Board Infinity
- AI 和机器学习基础: Microsoft
- Microsoft AI & ML Engineering: Microsoft
- 谷歌云上的人工智能和机器学习简介: Google Cloud
- Artificial Intelligence in Finance and Wealth Management: University of Illinois Urbana-Champaign
- AI & Machine Learning: Apply, Build & Solve: EDUCBA
