AI 和 Machine Learning 职业教育，技巧和洞察力 | Coursera

在這個單身日致力於職業發展。 享受全年的 Coursera Plus，享受 40% 的折扣。
AI 和 Machine Learning 正在推动各行各业的创新。通过这些资源了解有关 Generative AI、Large Language Model 等的更多信息。
This guide to learning artificial intelligence is suitable for any beginner, no matter where you’re starting from.
Here are some in-demand jobs amid the AI boom that you can consider pursuing a career in.
Learn what an artificial intelligence engineer does and how you can get into this exciting career field.
Learn about autoencoders, a type of neural network used for feature extraction, and their use cases in areas such as text and image generation.
Explore Mixture of Experts, including the use cases and benefits of this approach to machine learning.
Dijkstra’s algorithm finds the shortest path between nodes in a weighted graph. Learn how Dijkstra’s algorithm works, where it’s used, and why it remains a popular choice for solving shortest-path problems.
Learn about autoencoders, a type of neural network used for feature extraction, and their use cases in areas such as text and image generation.
Explore Mixture of Experts, including the use cases and benefits of this approach to machine learning.
AI and machine learning courses
您将获得的技能: Google Gemini, Generative AI, AI literacy, Model Training, AI Integrations, Google Sheets, Critical Thinking, Innovation
★ 4.8 (2.6万) · 初级 · 专项课程 · 3-6 个月
Saïd Business School, University of Oxford
您将获得的技能: Responsible AI, Artificial Neural Networks, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), AI literacy, Generative AI, Machine Learning Methods, Deep Learning, Machine Learning, Convolutional Neural Networks, Supervised Learning, Fraud detection, Reinforcement Learning, Unsupervised Learning
★ 4.8 (266) · 初级 · 课程 · 1-3 个月
您将获得的技能: Data Visualization, Prompt Patterns, AI powered creativity, AI Personalization, Generative AI, AI literacy, Timelines, LLM Application, Agentic Workflows, Ideation, Artificial Intelligence, Scenario Testing, Business Correspondence, Complex Problem Solving, Report Writing, Solution Design, Document Management, Critical Thinking, Software Versioning, Machine Learning
★ 4.8 (8203) · 初级 · 专项课程 · 1-4 周
Understand how the Rust programming language works, its main features, what you might use it for, and how it differs from other programming languages like C++, Python, and Go. Discover use cases and comparison to other languages.
Learn how to use Claude Code in the terminal, alongside VS Code and Cursor, and on the web. Explore practical coding workflows, debugging, Git, and tips for getting better results.
Learn about the A* algorithm, including how it works, its performance relative to other popular search algorithms, and real-world use cases.
Learn more about GraphRAG, an advanced, graph-based version of retrieval augmented generation (RAG), and explore its benefits in improving the context and accuracy of AI applications.
Explore the key concepts of graph theory and how it relates to real-world applications in computer science, biology, and social networks to model relationships, structures, and networks.
Learn how pseudocode can help you develop a programmer’s mindset and think through the logic of your program and the steps it needs to execute more efficiently.
Learn about Boolean logic and how it structures computing, programming, database search, and more. Explore some of the operators it uses, and what a truth table in Boolean algebra is.
Learn about principal component analysis, including how it works and its real-world applications in areas such as machine learning and data visualization.
Learn what AI risk management is, why it matters, and how organizations identify, assess, and reduce AI risks using governance frameworks and cybersecurity practices. Explore the key concepts, rules, and skills that support responsible AI.
Dijkstra’s algorithm finds the shortest path between nodes in a weighted graph. Learn how Dijkstra’s algorithm works, where it’s used, and why it remains a popular choice for solving shortest-path problems.
Understand how the Rust programming language works, its main features, what you might use it for, and how it differs from other programming languages like C++, Python, and Go. Discover use cases and comparison to other languages.
Learn how to use Claude Code in the terminal, alongside VS Code and Cursor, and on the web. Explore practical coding workflows, debugging, Git, and tips for getting better results.
Learn about the A* algorithm, including how it works, its performance relative to other popular search algorithms, and real-world use cases.
Learn more about GraphRAG, an advanced, graph-based version of retrieval augmented generation (RAG), and explore its benefits in improving the context and accuracy of AI applications.
Explore the key concepts of graph theory and how it relates to real-world applications in computer science, biology, and social networks to model relationships, structures, and networks.
Learn how pseudocode can help you develop a programmer’s mindset and think through the logic of your program and the steps it needs to execute more efficiently.
Learn about Boolean logic and how it structures computing, programming, database search, and more. Explore some of the operators it uses, and what a truth table in Boolean algebra is.
Learn about principal component analysis, including how it works and its real-world applications in areas such as machine learning and data visualization.
Learn what AI risk management is, why it matters, and how organizations identify, assess, and reduce AI risks using governance frameworks and cybersecurity practices. Explore the key concepts, rules, and skills that support responsible AI.
GenAI is poised to be the largest technological revolution since the internet. In today's technologically evolving world, professionals skilled in AI and machine learning are in high demand across many industries. A career in this fast-growing field provides opportunities to use technical skills to drive