课程
Intermediate Functional Programming with purrr
- 中级技能水平
- 4.7+
- 34 条评价
Continue learning with purrr to create robust, clean, and easy to maintain iterative code.
软件开发
观看专家讲师的短视频,然后在浏览器中通过互动练习实践所学内容。
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课程
Continue learning with purrr to create robust, clean, and easy to maintain iterative code.
软件开发
课程
Deploy ADK agents to production using Vertex AI Agent Engine and Cloud Run. Add persistent cross-session memory with Memory Bank.
云计算
课程
Learn to upload, organize, share, and manage files and folders in Google Drive from any device.
云计算
课程
Build modern data lakehouses on Google Cloud using BigQuery, Cloud Storage, Apache Iceberg, BigLake, federated queries, and data governance tools.
云计算
课程
With Google Slides, you can create and present professional presentations for sales, projects, training modules, and much more.
云计算
课程
Learn to create and manage events, schedule meetings, share calendars, and use tasks and reminders to stay organized.
云计算
课程
Author Dags with the TaskFlow API, asset-based scheduling, and deferrable sensors, and run an end-to-end SQL ETL pipeline with quality checks.
数据工程
课程
Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.
机器学习
课程
Learn to schedule, host, and manage video meetings in Google Meet, including screen sharing and collaboration tools.
云计算
课程
Learn to message individuals and groups, collaborate in spaces, and integrate Google Chat with other Workspace apps.
云计算
课程
Learn to create, format, and collaborate on documents in real time using Google Docs, stored securely in the cloud.
云计算
课程
Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.
软件开发
课程
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
概率与统计
课程
Learn to create and edit spreadsheets in Google Sheets, work with data, build formulas, and collaborate in real time.
云计算
课程
Go beyond MCP basics with sampling, notifications, roots, and the STDIO and StreamableHTTP transports in Python.
人工智能
课程
Turn a basic AI agent into a sophisticated assistant using advanced instructions, model selection, planning capabilities, and structured output.
云计算
课程
Explore streaming data architectures on Google Cloud with Pub/Sub, Managed Kafka, Dataflow, and BigQuery for real-time data processing.
云计算
课程
Master Apache Beam and Dataflow foundations including portability, Runner v2, Shuffle Service, Streaming Engine, IAM, quotas, and security.
云计算
课程
Design and operate batch data pipelines on Google Cloud using Dataflow, Serverless Spark, Cloud Composer, and data validation techniques.
云计算
课程
Scale and manage multi-cluster GKE environments. Master fleets, Cloud Service Mesh, identity management, CI/CD at scale, and GKE Enterprise capabilities.
云计算
课程
Use Gemini AI to boost your productivity in BigQuery. Explore data, accelerate code development, and discover visualization workflows.
云计算
课程
Deploy and manage Kubernetes workloads on GKE. Cover networking, deployments, jobs, persistent storage, and data management in production environments.
云计算
课程
Secure and monitor GKE production environments. Learn access control, logging, monitoring, CI/CD pipelines, and managed storage integration on Google Cloud.
云计算
课程
Build stateful AI agents that maintain context and remember user preferences using session state, memory management, and personalization.
云计算
课程
Equip AI agents with tools for web search, code execution, database queries, and custom actions. Transform agents into capable assistants.
云计算
课程
Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network
概率与统计
课程
Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.
概率与统计
课程
Work with Gemini AI models in BigQuery for sentiment analysis. Analyze customer reviews using SQL and Python notebooks with Gemini.
云计算
课程
Develop data pipelines with Apache Beam and Dataflow. Cover transforms, windowing, I/O connectors, schemas, state APIs, Beam SQL, and notebooks.
云计算
课程
Operate Dataflow pipelines in production. Learn monitoring, logging, troubleshooting, performance tuning, CI/CD, reliability, and templates.
云计算
数据科学是一个专注于从数据中获取信息的专业领域。数据科学家使用编程技能、科学方法、算法等来分析数据,形成可操作的洞察。
您需要学习 Python 或 R 等编程语言,掌握数学和统计学原理。数据分析方法和数据科学工具的知识也是必不可少的。学习数据科学有很多方法。除了正式的教育途径,如学位或大学学习,还有很多其他资源可以帮助您按自己的节奏学习。除了在线课程和教程,还有书籍、视频等。
除了数学和统计学知识,数据科学家还需要 Python、R 和 SQL 等语言的编程技能。此外,数据科学需要处理大型数据集的能力、数据可视化、数据整理和数据库管理知识。机器学习和深度学习技能也很有用。
在专业领域,几乎每个行业都可以在某种程度上使用数据科学。医疗机构使用数据科学来检测和治疗疾病,金融公司用它来检测和预防欺诈。各种行业都将数据科学用于营销,如构建推荐系统和分析客户流失。
是的,数据科学是美国和全球增长最快的行业之一。它也是薪酬最高的职业之一。根据 Payscale 的数据,在美国,有经验的数据科学家平均收入为 97,609 美元,满意度评分为五星中的四星。
这里有几个需要考虑的因素。首先,数据科学学位的竞争可能很激烈,通常需要持续的高分。同样,数据科学所需的许多技能需要大量的学习和耐心。掌握所有必要的基础知识可能需要几个月的时间,还需要大量的实践经验才能获得入门级职位。
是的,您需要一些 Python、R、SQL、Java 和 C/C++ 等语言的编程经验。不过,由于语法相对简单,Python 编程语言通常是新手的首选。
对于没有编程经验和/或数学背景的人来说,通常需要 7 到 12 个月的密集学习才能达到入门级数据科学家的水平。但是,重要的是要记住,仅仅学习数据科学的理论基础可能不会让您成为真正的数据科学家。
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随时随地通过我们的移动课程和每日 5 分钟编程挑战提升技能。