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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

Course

Understanding Machine Learning

BasicSkill Level
2 hours
12K
An introduction to machine learning with no coding involved.

Track

Machine Learning Fundamentals in Python

16 hours
6.8K
Learn the art of Machine Learning and come away as a boss at prediction, pattern recognition, and the beginnings of Deep and Reinforcement Learning.

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Browse Machine Learning courses and tracks

Course

ARIMA Models in Python

AdvancedSkill Level
4 hours
533
Learn about ARIMA models in Python and become an expert in time series analysis.

Course

Sentiment Analysis in Python

IntermediateSkill Level
4 hours
530
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

Course

Ensemble Methods in Python

AdvancedSkill Level
4 hours
518
Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Course

Supervised Learning in R: Regression

IntermediateSkill Level
4 hours
477
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Course

Unsupervised Learning in R

IntermediateSkill Level
4 hours
427
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Course

Machine Learning with caret in R

IntermediateSkill Level
4 hours
403
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Course

Monitoring Machine Learning Concepts

IntermediateSkill Level
2 hours
397
Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Course

Building Chatbots in Python

IntermediateSkill Level
4 hours
393
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Course

Cluster Analysis in R

IntermediateSkill Level
4 hours
385
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Course

Fully Automated MLOps

IntermediateSkill Level
4 hours
355
Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Course

Machine Learning for Marketing in Python

IntermediateSkill Level
4 hours
246
From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Course

MLOps for Business

BasicSkill Level
3 hours
236
Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Course

Machine Learning in the Tidyverse

IntermediateSkill Level
5 hours
185
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Course

Advanced NLP with spaCy

IntermediateSkill Level
5 hours
147
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

Course

Support Vector Machines in R

IntermediateSkill Level
4 hours
141
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Course

Feature Engineering in R

IntermediateSkill Level
4 hours
135
Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

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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.

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