Data, AI, and Cloud Courses

• IntermediateSkill Level
• 4.6+
• 22.9K

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!

• BasicSkill Level
• 4.7+
• 13.1K

An introduction to machine learning with no coding involved.

• IntermediateSkill Level
• 4.6+
• 6.5K

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

• IntermediateSkill Level
• 4.7+
• 4K

In this course, youll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

• IntermediateSkill Level
• 4.6+
• 3.9K

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

• IntermediateSkill Level
• 4.6+
• 2.7K

Learn how to clean and prepare your data for machine learning!

• IntermediateSkill Level
• 4.4+
• 2.4K

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

• BasicSkill Level
• 4.6+
• 1.9K

Understand the fundamentals of Machine Learning and how its applied in the business world.

• IntermediateSkill Level
• 4.5+
• 1.9K

In this course you will learn the details of linear classifiers like logistic regression and SVM.

• IntermediateSkill Level
• 4.5+
• 1.8K

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

• IntermediateSkill Level
• 4.6+
• 1.6K

Learn to process, transform, and manipulate images at your will.

• IntermediateSkill Level
• 4.6+
• 1.6K

In this course you will learn the basics of machine learning for classification.

• IntermediateSkill Level
• 4.6+
• 1.5K

Create new features to improve the performance of your Machine Learning models.

• AdvancedSkill Level
• 4.6+
• 1.4K

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

• IntermediateSkill Level
• 4.7+
• 1.4K

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

• AdvancedSkill Level
• 4.5+
• 1.3K

This course focuses on feature engineering and machine learning for time series data.

• IntermediateSkill Level
• 4.1+
• 1.2K

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

• IntermediateSkill Level
• 4.6+
• 1.1K

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

• IntermediateSkill Level
• 4.7+
• 1.1K

Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

• AdvancedSkill Level
• 4.7+
• 1.1K

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

• AdvancedSkill Level
• 4.6+
• 1.1K

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

• AdvancedSkill Level
• 4.5+
• 1K

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

• IntermediateSkill Level
• 4.5+
• 1K

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

• IntermediateSkill Level
• 4.6+
• 1K

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

• IntermediateSkill Level
• 4.6+
• 854

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

• AdvancedSkill Level
• 4.8+
• 759

Learn about ARIMA models in Python and become an expert in time series analysis.

• IntermediateSkill Level
• 4.7+
• 748

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

• IntermediateSkill Level
• 4.6+
• 736

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

• AdvancedSkill Level
• 4.6+
• 734

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

• IntermediateSkill Level
• 4.4+
• 734

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.