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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

Cursus

Inzicht in Machine Learning

BasisVaardigheidsniveau
4.8+
12.7K
2 uur
Een introductie tot machine learning zonder coderen.

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Cursus

Unsupervised learning in R

GemiddeldVaardigheidsniveau
4.7+
555
4 uur
Deze cursus geeft je een inleiding tot clustering en dimensiereductie in R vanuit het perspectief van machine learning.

Cursus

Machine Learning met caret in R

GemiddeldVaardigheidsniveau
4.8+
537
4 uur
Deze cursus laat je kennismaken met de grote ideeën achter machine learning, zoals hoe je voorspellende modellen kunt maken en beoordelen.

Cursus

Ensemblemethoden in Python

GevorderdVaardigheidsniveau
4.8+
480
4 uur
Leer hoe je geavanceerde en effectieve machine learning-modellen kunt bouwen in Python met behulp van ensemble-technieken zoals bagging, boosting en stacking.

Cursus

Supervised Learning in R: Regressie

GemiddeldVaardigheidsniveau
4.6+
478
4 uur
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Cursus

ARIMA-modellen in Python

GevorderdVaardigheidsniveau
4.8+
466
4 uur
Leer meer over ARIMA-modellen in Python en word een expert in tijdreeksanalyse.

Cursus

Monitoring Machine Learning-concepten

GemiddeldVaardigheidsniveau
4.7+
458
2 uur
Ontdek de uitdagingen van het monitoren van machine learning-modellen in productie, zoals data- en conceptdrift, en aanpak van modeldegradatie.

Cursus

Cluster Analysis in R

GemiddeldVaardigheidsniveau
4.8+
407
4 uur
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Cursus

Volledig geautomatiseerde MLOps

GemiddeldVaardigheidsniveau
4.8+
385
4 uur
Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Cursus

Monitoring Machine Learning in Python

GevorderdVaardigheidsniveau
4.7+
370
3 uur
Deze cursus behandelt alles wat je moet weten om een eenvoudig monitoringsysteem voor machine learning te bouwen in Python.

Cursus

Introductie tot dataversiebeheer met DVC

GemiddeldVaardigheidsniveau
4.7+
342
3 uur
Check eens Data Version Control voor het beheren van ML-data. Zet je setup op, automatiseer je processen en evalueer je modellen zonder gedoe.

Cursus

Building Chatbots in Python

GemiddeldVaardigheidsniveau
4.7+
296
4 uur
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Cursus

MLOps voor bedrijven

BasisVaardigheidsniveau
4.8+
246
3 uur
Kom meer te weten over MLOps, inclusief de tools en methodes die je nodig hebt om machine learning-toepassingen te automatiseren en op te schalen.

Cursus

Machine Learning voor marketing in Python

GemiddeldVaardigheidsniveau
4.8+
224
4 uur
Van klantwaarde tot het voorspellen van klantverloop en segmentatie: leer en pas Machine Learning-toepassingen voor marketing toe in Python.

Cursus

Sentimentanalyse in R

GemiddeldVaardigheidsniveau
4.7+
213
4 uur
Leer sentimentanalyse door positieve en negatieve taal en specifieke emotionele bedoelingen te herkennen en door boeiende visualisaties te maken.

Cursus

Hyperparameterafstelling in R

GevorderdVaardigheidsniveau
4.7+
203
4 uur
Leer hoe je de hyperparameters van je model kunt afstemmen om de beste voorspellingsresultaten te krijgen.

Cursus

Machine Learning in de tidyverse

GemiddeldVaardigheidsniveau
4.8+
188
5 uur
Gebruik de pakketten tidyr en purrr in de tidyverse om machine learning-modellen te maken, te bekijken en te beoordelen.

Cursus

Fraudedetectie in R

GemiddeldVaardigheidsniveau
4.8+
145
4 uur
Leer fraude opsporen met analytics in R.

Cursus

Geavanceerde NLP met spaCy

GemiddeldVaardigheidsniveau
4.6+
143
5 uur
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

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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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