Data science courses

Learn how to develop deep learning models with Keras.

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

Learn how to identify, analyze, remove and impute missing data in Python.

Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

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

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

In this course youll learn about basic experimental design, a crucial part of any data analysis.

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

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

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Discover how to use the income statement and balance sheet in Power BI

In this course you will learn to fit hierarchical models with random effects.

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

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

Use your knowledge of common spreadsheet functions and techniques to explore Python!

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

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

Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

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

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

This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Discover how the Pinecone vector database is revolutionizing AI application development!

Explore Alteryx Designer in a retail data case study to boost sales analysis and strategic decision-making.

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.