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Machine Learning courses

Machine learning courses cover algorithms and concepts for enabling computers to learn from data and make decisions without explicit programming. Build your skills in NLP, deep learning, MLOps and more.

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Recommended for Machine Learning beginners

Build your Machine Learning skills with interactive courses, curated by real-world experts

课程

理解机器学习

基础技能水平
4.8+
12,290 条评价
2小时
无需编码的机器学习入门。

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课程

使用 scikit-learn 的监督学习

中级技能水平
4.8+
9,710 条评价
4小时
用 Python 中的 scikit-learn 提升你的机器学习技能。 在这门互动课程中使用真实世界数据集,学习如何做出强大的预测!

课程

理解机器学习

基础技能水平
4.8+
12,290 条评价
2小时
无需编码的机器学习入门。

课程

Python 中的无监督学习

中级技能水平
4.8+
1,244 条评价
4小时
学习如何使用 scikit-learn 和 scipy 对无标签数据集进行聚类、转换、可视化并提取洞察。

课程

Python 树模型机器学习

中级技能水平
4.8+
824 条评价
5小时
在本课程中,你将学习如何使用 scikit-learn 中的基于树的模型和集成方法进行回归和分类。

课程

MLOps 概念

中级技能水平
4.8+
3,048 条评价
2小时
了解 MLOps 如何将机器学习模型从本地笔记本带到生产环境中运行,并创造实际业务价值。

课程

Python 中的线性分类器

中级技能水平
4.8+
369 条评价
4小时
在本课程中,你将学习逻辑回归和 SVM 等线性分类器的细节。

课程

MLflow 入门

高级技能水平
4.7+
903 条评价
4小时
学习如何使用 MLflow 简化构建机器学习应用的复杂性。 探索 MLflow 跟踪、项目、模型和模型注册表。

课程

R 中的监督学习:分类

中级技能水平
4.7+
159 条评价
4小时
在本课程中,您将学习用于分类的机器学习基础知识。

课程

MLOps 部署与生命周期管理

高级技能水平
4.7+
1,045 条评价
4小时
在本课程中,您将探索现代 MLOps 框架,了解机器学习模型的生命周期和部署。

课程

端到端机器学习

中级技能水平
4.7+
412 条评价
4小时
深入了解机器学习,学习如何设计、训练并部署端到端模型。

课程

使用 XGBoost 的极端梯度提升

中级技能水平
4.8+
288 条评价
4小时
学习梯度提升基础,并使用 XGBoost 构建最先进的机器学习模型,解决分类和回归问题。

课程

Python 图像处理

中级技能水平
4.8+
227 条评价
4小时
学会随心处理、转换和操作图像。

课程

Python 中的聚类分析

中级技能水平
4.7+
1,126 条评价
4小时
在本课程中,你将通过使用 SciPy 库的层次聚类和 k-means 聚类等技术了解无监督学习。

课程

Python 中的模型验证

中级技能水平
4.8+
1,049 条评价
4小时
学习模型验证基础、验证技术,并开始创建经过验证且高性能的模型。

课程

R 中的监督学习:回归

中级技能水平
4.6+
110 条评价
4小时
在本课程中,你将学习如何使用线性回归、广义加性模型、随机森林和xgboost预测未来事件。

课程

面向机器学习的 CI/CD

高级技能水平
4.7+
464 条评价
5小时
用 GitHub Actions 和 Data Version Control 通过 CI/CD 提升你的机器学习开发

课程

Python 中的降维

中级技能水平
4.8+
992 条评价
4小时
理解数据降维概念,并掌握在 Python 中实现这些技术的方法。

课程

机器学习监控概念

中级技能水平
4.8+
584 条评价
2小时
了解在生产环境中监控机器学习模型的挑战,包括数据漂移和概念漂移,以及应对模型退化的方法。

课程

Python 金融机器学习

中级技能水平
4.8+
245 条评价
4小时
学习使用线性模型、决策树、随机森林和神经网络来建模并预测股票数据值。

课程

使用 PySpark 进行机器学习

高级技能水平
4.8+
794 条评价
4小时
学习如何使用 Apache Spark 从数据中进行预测,涵盖决策树、逻辑回归、线性回归、集成方法和管道。

课程

Fully Automated MLOps

中级技能水平
4.8+
401 条评价
4小时
了解 MLOps 架构、CI/CD/CM/CT 技术和自动化模式,部署可持续创造价值的 ML 系统。

课程

Python 中的 ARIMA 模型

高级技能水平
4.8+
460 条评价
4小时
在 Python 中学习 ARIMA 模型,成为时间序列分析专家。

课程

Python 中的超参数调优

中级技能水平
4.8+
895 条评价
4小时
学习 Python 中的自动超参数调优技巧,包括网格搜索、随机搜索和智能搜索。

课程

Python 中的购物篮分析

中级技能水平
4.8+
313 条评价
4小时
用Python通过书店数据探索购物篮分析中的关联规则,并创建电影推荐。

课程

Python 中的情感分析

中级技能水平
4.8+
487 条评价
4小时
客户对您的产品感到满意,还是您的服务有所欠缺?学习如何执行端到端情感分析任务。

Machine Learning 相关资源

博客

How to Become a Machine Learning Engineer in 2026

Learn how to become a machine learning engineer and discover why it is one of the most lucrative and dynamic career paths in the data world.
Kurtis Pykes 's photo

Kurtis Pykes

15分钟

博客

33 Machine Learning Projects for All Levels in 2026

Machine learning projects for beginners, final year students, and professionals. The list consists of guided projects, tutorials, and example source code.
Abid Ali Awan's photo

Abid Ali Awan

15分钟

博客

Top 12 Machine Learning Engineer Skills To Start Your Career

Master these skills to become a job-ready machine learning engineer in 2024.
Natassha Selvaraj's photo

Natassha Selvaraj

11分钟


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Frequently asked questions

Is machine learning easy to learn?

DataCamp's beginner machine learning courses are a lot of hands-on fun, and they provide an excellent foundation for machine learning to advance your career or business. Within weeks, you'll be able to create models and generate predictions and insights. You'll also learn foundational knowledge of Python and R and the fundamentals of artificial intelligence.

After that, the learning curve gets a bit steeper. Machine learning careers require a deeper understanding of statistics, math, and software engineering, all of which can be mastered at DataCamp.

What is machine learning used for?

In a nutshell, machine learning is a type of artificial intelligence whose algorithms, as they acquire data, produce analytical models and make predictions with little to no human intervention.

It's difficult to find an industry that doesn't use machine learning. For example, marketers use machine learning to forecast returns on investments in marketing campaigns. Likewise, purchasing departments use machine learning to predict needed inventory.

Businesses of all kinds use machine learning to predict customer behavior, map supply chains, and forecast revenues. Machine learning is used to predict health outcomes and to improve patient satisfaction. Machine learning helps scientists model climate change scenarios, including possible solutions.

More specifically, machine learning is used in smart devices, search engines, and streaming services (when Netflix suggests a show or movie based on your viewing history, that's machine learning).

What jobs can you get with machine learning skills?

Machine learning skills are valuable in programming, data science, and other computer engineering disciplines. In addition, machine learning is a must for anyone wanting to work in robotics!

Not all jobs that require machine learning are in tech though. For example, linguists use machine learning to track ever-changing languages and dialects. In addition, business departments, such as marketing, accounting, logistics, and purchasing, to name a few, increasingly need machine learning experts to help them make informed business decisions. Knowing machine learning can give you a step up in nearly any position, as modeling and predicting are critical business needs.

Are machine learning skills in demand?

Yes, machine learning skills are in high demand. According to a report by the World Economic Forum, demand for AI and ML specialists is expected to grow by 40% between 2023 and 2027.

How much math do I need to take a machine learning course?

If you're looking to develop a high-level understanding of machine learning concepts, you don't need much math. If you want to dive deeper and make machine learning your career (as opposed to an added value to your existing career), a foundation in statistics and algebra is helpful. If you don't have a mathematical background, that's okay. We'll teach you everything you need, and our instructors are a lot less scary than your high school calculus teacher.

Do I need to download machine learning software to learn on DataCamp?

You do not need to download anything while learning with DataCamp. All the tools we use are web-based.

其他技术和主题

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