Researcher course in machine learning
Alternative Data and NLP for Finance
Alternative data and natural language processing as funds use them: turning news, filings and earnings calls into signals with language models, judging satellite, card and web data, and testing whether any of it adds return once costs and timing are honest.
Alternative data is information beyond prices and company accounts that investors use to see changes earlier: the tone of an earnings call, a shift in a filing’s wording, spending on cards, cars in car parks. This course teaches how to turn such data into signals, especially text with natural language processing, and how to test whether a dataset is worth its price.
Why is timing the hardest part?
Because a signal is only real if the data was available when the trade would have been made. News carries publication times, filings are revised and vendors backfill history. The course builds every signal on point-in-time data so that the backtest matches what could have been traded.
How is the course taught?
Audio lessons give the general subject, explainer films show text turned into numbers and signals, and the workbooks hold notebooks, worked examples and cheat sheets. Assignments and the project receive written feedback from the faculty.
Who is this course for?
Quants, data scientists and analysts at funds that buy or build alternative data.
What you will be able to do
- Turn news, filings and earnings call transcripts into features with classical NLP and language models.
- Build and test a sentiment signal with correct timestamps and no look-ahead.
- Evaluate an alternative dataset for coverage, history, bias and decay.
- Write the due-diligence note a fund needs before buying a dataset.
Syllabus, module by module
What alternative data is
Text, transactions, satellite, web and app data, and the market for them.
Text as data
Tokens, dictionaries, the Loughran-McDonald word lists and embeddings.
Language models
Transformer models and large language models for classification, extraction and summaries.
News, filings and calls
Sentiment, surprise and change in tone; timestamps and point-in-time text.
What every course contains
Every paid course comes with the first seven and the certificate, whichever level it sits at. The proctored exam and the credential come when the course is taken as part of a Certificate, Diploma or Fellowship. Everything is self-paced: the material is yours to study in any order, at any hour, for the whole of the license.
- Workbooks. Written to train the thinking patterns and the important concepts of the course, with worked problems and the reasoning behind each answer, so that you learn to think the way the subject is thought.
- Audio edition. Focused, well-presented recordings with explainers and examples of the material, made to be interesting, relevant and entertaining, so that the general subject can be learned away from the desk.
- Notes. Pre-produced notes with every fact the course relies on, written out in full, so that nothing has to be transcribed from the films or the audio.
- Cheat sheet. One sheet with every important learning concept of the course on it, to keep beside you during the work and to revise from before the exam.
- Named sources. Every fact in the notes names its source, the paper, the book or the dataset, for anyone who wants to dig in further.
- Explainer films. Focused films, in the style of the sample films on the catalog page, that walk through the most difficult concepts of the course with visual explanations of a high standard.
- Transcript. A full transcript of every film and every audio recording, searchable and quotable.
- Proctored exam. Taken as part of a Certificate, Diploma or Fellowship, the course ends in a proctored multiple-choice questionnaire, with a pass mark of 60% and three retakes included. A course taken on its own is assessed by its coursework and has no exam.
- Verifiable certificate. A certificate of completion that a third party can verify: an employer sends the code on it to the credentials office and receives written confirmation of the course, the date and the result.
- Credential of the program. The Certificate, Diploma or Fellowship of the program, track or path the course belongs to, awarded when every course in it is passed. Which one depends on the program you choose.
How the certificate is earned
Graded assignments and a final project: a text-based signal built from filings or news, tested out of sample, with a dataset due-diligence note. On a pass you receive the Course certificate in Alternative Data and NLP for Finance, issued by the Institute with a verification code. A course taken as part of a Certificate, Diploma or Fellowship ends in a proctored online exam with a pass mark of 60%. The fee includes three retakes; each attempt after that carries a reduced proctored exam fee. A course taken on its own is assessed by its coursework and has no exam. Read how certification works.
Before you start
Machine learning for trading at the Institute's level.
This course counts toward
- Certificate in Machine Learning for TradingFive courses and a capstone on applying machine learning to markets without fooling yourself: labeling, features, purged validation, deep and language models, regimes and reinforcement learning.
- Fellowship in Computational FinanceThe top credential on the researcher path. Twenty-one courses and a dissertation supervised in writing and examined by two faculty members.
Questions applicants ask
What is alternative data in finance?
It is any data beyond prices, volumes and company accounts that investors use to forecast returns, such as news text, card spending, satellite images or web traffic.
Can language models predict stock returns?
They are good at reading text quickly and consistently, which can produce useful signals from news and filings. Much of the easy value is already priced, so the course tests every signal out of sample and after costs.