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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

Understanding Machine Learning

БазовыйУровень навыков
4.8+
9 542 отзыва
2 ч
An introduction to machine learning with no coding involved.

Трек

Основы машинного обучения на Python

4.5+
8 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

Supervised Learning with scikit-learn

Средний уровеньУровень навыков
4.8+
8 424 отзыва
4 ч
Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

Курс

Understanding Machine Learning

БазовыйУровень навыков
4.8+
9 542 отзыва
2 ч
An introduction to machine learning with no coding involved.

Курс

Unsupervised Learning in Python

Средний уровеньУровень навыков
4.8+
1 095 отзывов
4 ч
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

Курс

MLOps Concepts

Средний уровеньУровень навыков
4.8+
2 564 отзыва
2 ч
Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

Курс

Machine Learning with Tree-Based Models in Python

Средний уровеньУровень навыков
4.8+
716 отзывов
5 ч
In this course, youll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

Курс

Machine Learning for Business

БазовыйУровень навыков
4.8+
1 645 отзывов
2 ч
Understand the fundamentals of Machine Learning and how its applied in the business world.

Курс

Linear Classifiers in Python

Средний уровеньУровень навыков
4.8+
326 отзывов
4 ч
In this course you will learn the details of linear classifiers like logistic regression and SVM.

Курс

Image Processing in Python

Средний уровеньУровень навыков
4.8+
210 отзывов
4 ч
Learn to process, transform, and manipulate images at your will.

Курс

Extreme Gradient Boosting with XGBoost

Средний уровеньУровень навыков
4.8+
255 отзывов
4 ч
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

Курс

Introduction to MLflow

Продвинутый уровеньУровень навыков
4.7+
738 отзывов
4 ч
Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

Курс

Supervised Learning in R: Classification

Средний уровеньУровень навыков
4.7+
138 отзывов
4 ч
In this course you will learn the basics of machine learning for classification.

Курс

MLOps Deployment and Life Cycling

Продвинутый уровеньУровень навыков
4.7+
852 отзыва
4 ч
In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Курс

Introduction to Natural Language Processing in Python

Средний уровеньУровень навыков
4.7+
987 отзывов
4 ч
Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

Курс

Cluster Analysis in Python

Средний уровеньУровень навыков
4.8+
959 отзывов
4 ч
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

Курс

End-to-End Machine Learning

Средний уровеньУровень навыков
4.7+
341 отзыв
4 ч
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

Курс

Model Validation in Python

Средний уровеньУровень навыков
4.8+
833 отзыва
4 ч
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Курс

CI/CD for Machine Learning

Продвинутый уровеньУровень навыков
4.7+
368 отзывов
5 ч
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

Курс

Machine Learning with PySpark

Продвинутый уровеньУровень навыков
4.8+
689 отзывов
4 ч
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Курс

Hyperparameter Tuning in Python

Средний уровеньУровень навыков
4.8+
782 отзыва
4 ч
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Курс

Sentiment Analysis in Python

Средний уровеньУровень навыков
4.8+
429 отзывов
4 ч
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

Курс

Dimensionality Reduction in Python

Средний уровеньУровень навыков
4.8+
849 отзывов
4 ч
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Курс

Natural Language Processing with spaCy

Средний уровеньУровень навыков
4.7+
576 отзывов
4 ч
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Курс

Feature Engineering for NLP in Python

Продвинутый уровеньУровень навыков
4.8+
142 отзыва
4 ч
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

Курс

Developing Machine Learning Models for Production

Средний уровеньУровень навыков
4.8+
440 отзывов
4 ч
Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

Курс

Machine Learning for Finance in Python

Средний уровеньУровень навыков
4.8+
208 отзывов
4 ч
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Курс

Monitoring Machine Learning Concepts

Средний уровеньУровень навыков
4.8+
455 отзывов
2 ч
Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Курс

Fraud Detection in Python

Средний уровеньУровень навыков
4.7+
187 отзывов
4 ч
Learn how to detect fraud using Python.

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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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