Data science courses

Learn efficient techniques in pandas to optimize your Python code.

Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.

Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

Learn the fundamentals of data visualization using Google Sheets.

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

In this course, you'll learn the basics of relational databases and how to interact with them.

Analyze text data in R using the tidy framework.

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

Discover how to become a data defender and keep data safe and secure with this beginner-friendly interactive course.

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

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

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

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

Learn to perform linear and logistic regression with multiple explanatory variables.

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

In this course, you'll learn how to import and manage financial data in Python using various tools and sources.

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.

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

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

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

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

Learn about responsible AI data management practices. Discover strategies covering all stages of an AI project to help you develop AI responsibly.

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

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

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

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.