Do you want to learn how machines can learn tasks we thought only human brains could perform? Then take this Deep Learning course developed by IVADO, Mila and Université de Montréal: an extensive overview of the essentials of deep learning, this ground-breaking technology already prevalent in our lives and spanning all sectors.

In the last six years, the financial sector has seen an increase in the use of machine learning models in financial, banking and insurance contexts. Data science and advanced analytics teams in the financial and insurance community are implementing these models regularly and have found a place for them in their toolbox.

If you want to learn to code with Python, this free course will give you an overview of the ins and outs of Python basics. Try our no-risk course today and see why Python has become one of the world’s most popular and in-demand programming languages. No previous coding experience required.

Google Analytics helps you make actionable decisions that can have a dramatic impact on engagement and conversions. This course will teach you how to add Google Analytics to a website, create custom campaigns, and evaluate the results via reports.

Create cohesive, inclusive, and efficient Power BI reports to effectively communicate results.

Explore key concepts of data analytics, including types of analytics, data, and storage. Explore the analytics process and tools used to discover insights.

Scalable data models enable enterprise-scale analytics in Power BI. Implement data modeling best practices, use large dataset storage format, and practice building a star schema to design analytics solutions that can scale.

Learn about the history of natural language processing (NLP), including how the Transformer architecture revolutionized the field and helped us create large language models (LLMs). Work with LLMs in Azure Machine Learning through the foundation models in the model catalog.

Factor Analysis and PCA are powerful tools, applicable in many common situations in business and data analysis. This course covers both the theory and implementation of factor analysis and PCA, in Excel (using VBA), Python, and R.

Linear regression is a powerful tool, applicable in many common situations in business and data analysis. This course will cover both the theory and implementation of linear regression in Excel, Python, and R.

This course will teach you both the theory and implementation of logistic regression, in Excel (using solver), Python, and R.

Optimization is all about smart trade-offs given difficult choices. This course focuses on three specific aspects of numerical optimization: correctly setting up optimization problems, linear programming, and integer programming.