数据、AI 和云课程

• 中级技能水平
• 4.8+
• 167 条评价

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

• 中级技能水平
• 4.9+
• 17 条评价

Get hands-on with Claude Code, Anthropics terminal AI agent: master context, plan mode, custom commands, MCP, and hooks to ship real work you can trust.

• 中级技能水平
• 4.8+
• 85 条评价

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

• 中级技能水平
• 4.7+
• 142 条评价

Learn to build recommendation engines in Python using machine learning techniques.

• 基础技能水平
• 4.8+
• 282 条评价

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

• 中级技能水平
• 4.8+
• 60 条评价

Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.

• 高级技能水平
• 4.8+
• 86 条评价

Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.

• 中级技能水平
• 4.8+
• 54 条评价

Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.

• 基础技能水平
• 4.8+
• 63 条评价

Modernize Infrastructure and Applications with Google Cloud

• 中级技能水平
• 4.8+
• 102 条评价

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

• 中级技能水平
• 4.8+
• 21 条评价

This course introduces the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Infrastructure Foundations.

• 中级技能水平
• 4.7+
• 103 条评价

Learn how to access financial data from local files as well as from internet sources.

• 基础技能水平
• 4.7+
• 164 条评价

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

• 基础技能水平
• 4.8+
• 80 条评价

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

• 基础技能水平
• 4.9+
• 45 条评价

Map agent types to your KPIs and explore use cases that solve problems, learn how Gemini Enterprise empowers you to build and orchestrate the right agents.

• 中级技能水平
• 4.7+
• 82 条评价

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

• 高级技能水平
• 4.7+
• 143 条评价

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

• 中级技能水平
• 4.7+
• 95 条评价

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

• 中级技能水平
• 4.8+
• 32 条评价

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

• 中级技能水平
• 4.7+
• 36 条评价

Learn to detect fraud with analytics in R.

• 中级技能水平
• 4.7+
• 78 条评价

This course is for R users who want to get up to speed with Python!

• 高级技能水平
• 4.8+
• 51 条评价

Learn how to tune your models hyperparameters to get the best predictive results.

• 基础技能水平
• 5
• 2 条评价

Get hands-on with Snowflake: query data, manage storage, control costs, and build with Cortex AI and Streamlit.

• 高级技能水平
• 4.7+
• 94 条评价

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

• 中级技能水平
• 4.5+
• 86 条评价

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

• 中级技能水平
• 4.6+
• 16 条评价

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

• 高级技能水平
• 4.9+
• 94 条评价

Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training

• 基础技能水平
• 4.8+
• 34 条评价

Use your knowledge of common spreadsheet functions and techniques to explore Python!

• 基础技能水平
• 4.6+
• 21 条评价

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

• 基础技能水平
• 4.8+
• 131 条评价

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.