Introduction to Databases in Python
In this course, you'll learn the basics of relational databases and how to interact with them.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
In this course, you'll learn the basics of relational databases and how to interact with them.
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
In this course, you'll learn how to import and manage financial data in Python using various tools and sources.
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.
Leverage the power of Python and PuLP to optimize supply chains.
Explore Large Language Models (LLMs) in business. Realize their value and where you can begin utilizing them today.
Learn how to build interactive and insight-rich dashboards with Dash and Plotly.
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Analyze text data in R using the tidy framework.
Discover how to become a data defender and keep data safe and secure with this beginner-friendly interactive course.
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.
Learn to perform linear and logistic regression with multiple explanatory variables.
Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.
In this course, you'll learn about the concepts of random variables, distributions, and conditioning.
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Learn about ARIMA models in Python and become an expert in time series analysis.
In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.
Learn how to efficiently collect and download data from any website using R.
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.