Data science courses

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Learn how to build a model to automatically classify items in a school budget.

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

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Learn how to use Python to analyze customer churn and build a model to predict it.

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

Learn to streamline your machine learning workflows with tidymodels.

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Learn how to design and implement triggers in SQL Server using real-world examples.

Learn how to pull character strings apart, put them back together and use the stringr package.

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Develop the skills you need to clean raw data and transform it into accurate insights.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

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

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

Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

In this course youll learn techniques for performing statistical inference on numerical data.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

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

Learn how to visualize time series in R, then practice with a stock-picking case study.