Data science courses

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Learn how to clean data with Apache Spark in Python.

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Improve data literacy skills by analyzing remote working policies.

Master sampling to get more accurate statistics with less data.

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

Step right into the dynamic world of data modeling with Snowflake!

Master AWS cloud technology with our course - ideal for hands-on learning and practical applications in the AWS ecosystem.

Explore the world of Pivot Tables within Google Sheets, and learn how to quickly organize thousands of data points with just a few clicks of the mouse.

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

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

Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.

Learn how to blend business, data, and AI, and set goals to drive success with an effectively scalable AI Strategy.

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

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

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

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

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

Learn the core techniques necessary to extract meaningful insights from time series data.

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

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

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.

Gain experience using techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.