Improving Financial Decision-Making with AI-Powered Analytics
Learnsignal
Last updated October 5, 2026
Improving Financial Decision-Making with AI-Powered Analytics is a continuing professional development course from Learnsignal in which finance professionals build forecasting models in Python for company financial results and environmental, social and governance (ESG) performance. In the first part you pull historical Microsoft share prices with the yfinance library and model them three ways: logistic regression to predict a gain or loss, multiple linear regression to predict the closing price, and a long short-term memory network, a deep-learning model suited to data ordered in time. In the second, you use panel data across several companies to relate profitability, leverage and earnings-per-share measures to ESG scores, and learn to read the resulting coefficients and p-values. The work is done in Google Colab with libraries including pandas, scikit-learn, Matplotlib, Seaborn and NumPy. It is a paid course.
What you'll learn
- Loading, cleaning and visualizing financial data in Python, working in Google Colab
- Predicting a share-price gain or loss with logistic regression
- Predicting closing prices with multiple linear regression
- Forecasting a time series with a long short-term memory deep-learning model
- Relating financial ratios to environmental, social and governance scores with panel regression, and reading coefficients and p-values
Frequently asked questions about Improving Financial Decision-Making with AI-Powered Analytics
Who is Improving Financial Decision-Making with AI-Powered Analytics for?
Accountants, analysts and finance professionals who want hands-on practice building predictive models in Python, including those new to the language.
Is Improving Financial Decision-Making with AI-Powered Analytics free?
No — Improving Financial Decision-Making with AI-Powered Analytics is a paid course.
What are the prerequisites for Improving Financial Decision-Making with AI-Powered Analytics?
Basic knowledge of finance theory and statistics. Prior programming experience is not required, since the course explains the code in stages, beginning with installing the libraries.
Do you need to code for Improving Financial Decision-Making with AI-Powered Analytics?
Yes — Improving Financial Decision-Making with AI-Powered Analytics involves hands-on coding.
Does Improving Financial Decision-Making with AI-Powered Analytics offer a certificate?
Yes. A Learnsignal continuing professional development certificate, issued on completion.
Why we suggest this course
For accountants and analysts who want to build a forecast themselves rather than read about forecasting. The datasets are real, the models range from a simple regression to a deep-learning network, and the ESG section spends time on reading coefficients and p-values, which is what a reader needs to judge whether a model's result means anything. Two things worth knowing: writing and running Python code is the core activity, though the code is walked through from installing the libraries onward, so prior programming experience is not required; and it assumes a basic grounding in finance theory and statistics.