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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

Supervised Learning met scikit-learn

GemiddeldVaardigheidsniveau
4.8+
18.8K
4 uur
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!

Cursus

Unsupervised Learning in Python

GemiddeldVaardigheidsniveau
4.8+
4.7K
4 uur
Leer hoe je kunt clusteren, transformeren, visualiseren en inzichten kunt halen uit niet-gelabelde datasets met behulp van scikit-learn en scipy.

Cursus

MLOps-concepten

GemiddeldVaardigheidsniveau
4.8+
2.9K
2 uur
Ontdek hoe MLOps machine learning-modellen van lokale notebooks kan omzetten in werkende modellen in productie die echte bedrijfswaarde opleveren.

Cursus

Machine Learning voor Business

BasisVaardigheidsniveau
4.8+
1.8K
2 uur
Begrijp de basis van machine learning en hoe het in het bedrijfsleven wordt gebruikt.

Cursus

Beeldverwerking in Python

GemiddeldVaardigheidsniveau
4.8+
1.7K
4 uur
Leer hoe je afbeeldingen kunt bewerken, veranderen en aanpassen zoals je wilt.

Cursus

Lineaire classificatoren in Python

GemiddeldVaardigheidsniveau
4.8+
1.5K
4 uur
In deze cursus leer je de details van lineaire classifiers zoals logistische regressie en SVM.

Cursus

Introductie tot MLflow

GevorderdVaardigheidsniveau
4.7+
1.2K
4 uur
Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

Cursus

Extreme Gradient Boosting met XGBoost

GemiddeldVaardigheidsniveau
4.8+
1.2K
4 uur
Leer de basis van gradient boosting en bouw toffe machine learning-modellen met XGBoost om classificatie- en regressieproblemen op te lossen.

Cursus

Clusteranalyse in Python

GemiddeldVaardigheidsniveau
4.8+
1.1K
4 uur
In deze cursus leer je over onbegeleid leren met technieken zoals hiërarchische en k-means clustering met behulp van de SciPy-bibliotheek.

Cursus

Modelvalidatie in Python

GemiddeldVaardigheidsniveau
4.8+
867
4 uur
Leer de basis van modelvalidatie en validatietechnieken, en begin met het maken van gevalideerde en goed presterende modellen.

Cursus

MLOps-deployments en levenscyclus

GevorderdVaardigheidsniveau
4.7+
849
4 uur
In deze cursus ga je aan de slag met het moderne MLOps-framework en leer je meer over de levenscyclus en implementatie van machine learning-modellen.

Cursus

End-to-End Machine Learning

GemiddeldVaardigheidsniveau
4.7+
849
4 uur
Duik in de wereld van machine learning en ontdek hoe je end-to-end-modellen kunt ontwerpen, trainen en implementeren.

Cursus

Hyperparameter Tuning in Python

GemiddeldVaardigheidsniveau
4.8+
735
4 uur
Leer technieken voor het automatisch afstemmen van hyperparameters in Python, zoals Grid, Random en Informed Search.

Cursus

Dimensionality Reduction in Python

GemiddeldVaardigheidsniveau
4.8+
722
4 uur
Begrijp het idee van het verminderen van de dimensies in je data en leer de technieken om dit in Python te doen.

Cursus

Machine Learning for Finance in Python

GemiddeldVaardigheidsniveau
4.8+
717
4 uur
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Cursus

CI/CD for Machine Learning

GevorderdVaardigheidsniveau
4.7+
699
5 uur
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

Cursus

Sentimentanalyse in Python

GemiddeldVaardigheidsniveau
4.8+
629
4 uur
Zijn klanten enthousiast over je producten of laat je service te wensen over? Leer hoe je een volledige sentimentanalyse kunt uitvoeren.

Cursus

Natural Language Processing met spaCy

GemiddeldVaardigheidsniveau
4.7+
608
4 uur
Leer de belangrijkste functies van spaCy en train modellen voor natuurlijke taalverwerking. Haal info uit ongestructureerde data en zoek overeenkomsten.

Cursus

Feature Engineering voor NLP in Python

GevorderdVaardigheidsniveau
4.8+
598
4 uur
Leer manieren om nuttige info uit tekst te halen en deze om te zetten naar een formaat dat geschikt is voor machine learning.

Cursus

Market Basket Analysis in Python

GemiddeldVaardigheidsniveau
4.8+
570
4 uur
Ontdek associatieregels in marktmandanalyse met Python aan de hand van boekwinkelgegevens en het maken van filmaanbevelingen.

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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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