This course introduces you to watsonx.data, IBM’s open data lakehouse platform.

In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!

Create a project that you can use to showcase your Data Science skills to prospective employers. Apply various data science and machine learning techniques to analyze and visualize a data set involving a real life business scenario and build a predictive model.

Learn about the most popular data science tools, including how to use them and what their features are.

New to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using thepopular Keras library.

Sharing information from native Jupyter files is not an easy task. In under an hour, learn how to create computational, visually engaging, and interactive reports using Jupyter Book easily.

Ideal for beginners with some knowledge of Python and statistics, in this one-hour hands-on guided project, you will learn how to use essential Python tools for statistical analysis of agricultural data and present that data on interactive maps

In this beginner-friendly, hands-on guided project, develop your data science and machine learning skills in under an hour by building a prediction model for the 2022 FIFA World Cup. Perfect for anyone interested in learning more about prediction models.

In this one-hour of hands-on guided project, you can easily learn how to analyze data using pandas, a popular Python library used for data analysis. This project will teach you how to analyze credit risk on a client dataset using the pandas library.

Cloud computing never stops changing. And Cloud professionals are always growing and learning as the industry evolves.

Learn about the world of data science first-hand from real data scientists.

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in Data Engineering, Data Analytics or Data Science.