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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

Курс

Введение в машинное обучение

БазовыйУровень навыков
4.8+
12 290 отзывов
2 ч
Введение в машинное обучение без программирования.

Трек

Основы машинного обучения на Python

4.5+
9 отзывов
16 ч
Освойте искусство машинного обучения и станьте экспертом в прогнозировании, распознавании закономерностей и основах глубокого обучения и обучения с подкреплением.

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Просматривайте курсы и треки Machine Learning

Курс

Конструирование признаков для NLP на Python

Средний уровеньУровень навыков
4.8+
161 отзыв
4 ч
Изучите методы извлечения полезной информации из текста и преобразования её в формат, подходящий для машинного обучения.

Курс

Введение в версионирование данных с DVC

Средний уровеньУровень навыков
4.7+
457 отзывов
3 ч
Изучите Data Version Control для управления данными ML. Освойте настройку, автоматизируйте пайплайны и без труда оценивайте модели.

Курс

Введение в TensorFlow на Python

Средний уровеньУровень навыков
4.8+
58 отзывов
4 ч
Изучите основы нейронных сетей и научитесь создавать модели глубокого обучения с помощью TensorFlow.

Курс

Мониторинг машинного обучения на Python

Продвинутый уровеньУровень навыков
4.8+
425 отзывов
3 ч
Этот курс охватывает всё, что нужно знать, чтобы создать базовую систему мониторинга машинного обучения на Python

Курс

Machine Learning with Tree-Based Models in R

БазовыйУровень навыков
4.8+
282 отзыва
4 ч
Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

Курс

Unsupervised Learning in R

Средний уровеньУровень навыков
4.8+
112 отзывов
4 ч
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Курс

Machine Learning with caret in R

Средний уровеньУровень навыков
4.8+
47 отзывов
4 ч
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Курс

Ансамблевые методы в Python

Продвинутый уровеньУровень навыков
4.8+
443 отзыва
4 ч
Научитесь создавать продвинутые и эффективные модели машинного обучения на Python с помощью ансамблевых методов: bagging, boosting и stacking.

Курс

Cluster Analysis in R

Средний уровеньУровень навыков
4.8+
79 отзывов
4 ч
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Курс

MLOps для бизнеса

БазовыйУровень навыков
4.8+
181 отзыв
3 ч
Узнайте о MLOps, включая инструменты и практики, необходимые для автоматизации и масштабирования приложений машинного обучения.

Курс

Modeling with tidymodels in R

Средний уровеньУровень навыков
4.8+
194 отзыва
4 ч
Learn to streamline your machine learning workflows with tidymodels.

Курс

Machine Learning in the Tidyverse

Средний уровеньУровень навыков
4.8+
124 отзыва
5 ч
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Курс

Building Recommendation Engines in Python

Средний уровеньУровень навыков
4.8+
155 отзывов
4 ч
Learn to build recommendation engines in Python using machine learning techniques.

Курс

Designing Forecasting Pipelines for Production

Продвинутый уровеньУровень навыков
4.7+
75 отзывов
4 ч
Learn how to design, automate, and monitor scalable forecasting pipelines in Python.

Курс

Support Vector Machines in R

Средний уровеньУровень навыков
4.8+
107 отзывов
4 ч
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Курс

Text Mining with Bag-of-Words in R

Средний уровеньУровень навыков
4.8+
146 отзывов
4 ч
Learn the bag of words technique for text mining with R.

Курс

Конструирование признаков в R

Средний уровеньУровень навыков
4.7+
160 отзывов
4 ч
Изучите принципы feature engineering для моделей машинного обучения и научитесь применять их с помощью фреймворка R tidymodels.

Курс

Анализ тональности в R

Средний уровеньУровень навыков
4.7+
99 отзывов
4 ч
Изучите анализ тональности: определяйте позитивную и негативную лексику, эмоциональный посыл и создавайте наглядные визуализации.

Связанные ресурсы по теме Machine Learning

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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.
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Machine learning projects for beginners, final year students, and professionals. The list consists of guided projects, tutorials, and example source code.
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Ready to apply your skills?

Projects allow you to apply your knowledge to a wide range of datasets to solve real-world problems in your browser

    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.

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