Math for Finance Professionals
Learn essential finance math skills with practical Excel exercises and real-world examples.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Learn essential finance math skills with practical Excel exercises and real-world examples.
Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.
Learn how to structure your PostgreSQL queries to run in a fraction of the time.
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Visualize seasonality, trends and other patterns in your time series data.
Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.
Learn how to work with streaming data using serverless technologies on AWS.
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.
Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.
Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!
Using Python and NumPy, learn the most fundamental financial concepts.
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.
Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.
Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Learn to manipulate and analyze flexibly structured data with MongoDB.
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.
Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.
Learn how to detect fraud using Python.
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.
In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.
Analyze text data in R using the tidy framework.
Explore GDPR through real-world cases on data rights, breaches, and compliance challenges.
Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.