Data, AI, and Cloud Courses

• AdvancedSkill Level
• 4.5+
• 612

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

• IntermediateSkill Level
• 4.4+
• 577

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

• AdvancedSkill Level
• 4.6+
• 572

Learn how to approach and win competitions on Kaggle.

• IntermediateSkill Level
• 4.7+
• 564

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

• IntermediateSkill Level
• 4.6+
• 547

Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

• AdvancedSkill Level
• 4.6+
• 530

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

• IntermediateSkill Level
• 4.5+
• 520

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

• IntermediateSkill Level
• 4.6+
• 503

Learn how to detect fraud using Python.

• BasicSkill Level
• 4.6+
• 479

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

• IntermediateSkill Level
• 4.8+
• 437

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

• IntermediateSkill Level
• 4.6+
• 399

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

• AdvancedSkill Level
• 4.4+
• 377

Learn to build pipelines that stand the test of time.

• IntermediateSkill Level
• 4.4+
• 373

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

• BasicSkill Level
• 4.6+
• 352

Learn how to prepare and organize your data for predictive analytics.

• IntermediateSkill Level
• 4.6+
• 341

Learn to build recommendation engines in Python using machine learning techniques.

• IntermediateSkill Level
• 4.7+
• 335

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

• IntermediateSkill Level
• 4.6+
• 331

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

• IntermediateSkill Level
• 4.8+
• 319

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

• AdvancedSkill Level
• 4.5+
• 287

This course covers everything you need to know to build a basic machine learning monitoring system in Python

• AdvancedSkill Level
• 4.4+
• 272

Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.

• AdvancedSkill Level
• 4.7+
• 251

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

• IntermediateSkill Level
• 4.5+
• 215

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

• IntermediateSkill Level
• 4.6+
• 183

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

• IntermediateSkill Level
• 4.6+
• 159

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

• BasicSkill Level
• 4.8+
• 158

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

• IntermediateSkill Level
• 3.8+
• 151

Learn the bag of words technique for text mining with R.

• IntermediateSkill Level
• 4.7+
• 146

Learn to streamline your machine learning workflows with tidymodels.

• IntermediateSkill Level
• 4.4+
• 129

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

• IntermediateSkill Level
• 4.6+
• 120

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

• IntermediateSkill Level
• 4.4+
• 120

In this course youll learn how to use data science for several common marketing tasks.