数据、人工智能和云计算课程

• 中间的技能水平
• 4.4+
• 3K

Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.

• 中间的技能水平
• 4.5+
• 2.9K

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

• 中间的技能水平
• 4.5+
• 2.8K

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

• 中间的技能水平
• 4.6+
• 2.8K

In this course, youll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

• 中间的技能水平
• 4.4+
• 2.7K

Leverage the OpenAI API to get your AI applications ready for production.

• 中间的技能水平
• 4.5+
• 2.7K

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

• 中间的技能水平
• 4.7+
• 2.7K

Learn the essentials of VMs, containers, Docker, and Kubernetes. Understand the differences to get started!

• 中间的技能水平
• 4.6+
• 2.6K

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

• 中间的技能水平
• 4.6+
• 2.6K

Boost your Excel skills with advanced referencing, lookup, and database functions using practical exercises.

• 中间的技能水平
• 4.5+
• 2.5K

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

• 中间的技能水平
• 4.6+
• 2.4K

Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!

• 中间的技能水平
• 4.5+
• 2.4K

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

• 中间的技能水平
• 4.6+
• 2.4K

In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.

• 中间的技能水平
• 4.7+
• 2.4K

Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.

• 中间的技能水平
• 4.6+
• 2.3K

Learn cutting-edge methods for integrating external data with LLMs using Retrieval Augmented Generation (RAG) with LangChain.

• 中间的技能水平
• 4.5+
• 2.2K

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

• 中间的技能水平
• 4.7+
• 2.2K

Step right into the dynamic world of data modeling with Snowflake!

• 中间的技能水平
• 4.6+
• 2.2K

Learn how to work with dates and times in Python.

• 中间的技能水平
• 4.5+
• 2.2K

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

• 中间的技能水平
• 4.7+
• 2.1K

Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.

• 中间的技能水平
• 4.5+
• 2.1K

Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.

• 中间的技能水平
• 4.5+
• 2.1K

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

• 中间的技能水平
• 4.5+
• 2.1K

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

• 中间的技能水平
• 4.7+
• 2K

Learn how to clean and prepare your data for machine learning!

• 中间的技能水平
• 4.5+
• 1.9K

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

• 中间的技能水平
• 4.6+
• 1.8K

Learn how to work with Claude using the Anthropic API to solve real-world tasks and build AI-powered applications.

• 中间的技能水平
• 4.6+
• 1.8K

Learn to retrieve and parse information from the internet using the Python library scrapy.

• 中间的技能水平
• 4.5+
• 1.8K

Discover modern data architectures key components, from ingestion and serving to governance and orchestration.

• 中间的技能水平
• 4.6+
• 1.7K

Learn to process, transform, and manipulate images at your will.

• 中间的技能水平
• 4.6+
• 1.7K

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.