Stock template
From Stock Exchange to Bible: AI that thinks along
Anomaly detection, stock market forecasts & AI text generation
Educational objectives
This course template conveys basic procedures of data analysis and machine learning through structured application examples from time series analysis, classification, and text generation. It supports the development of professional competencies in statistical modeling, algorithmic structuring, and practical implementation of data-driven decision-making processes. Through step-by-step development of analysis and forecasting models, the connection between data representation, model building, and code implementation becomes clear. The template is to be assigned to the area of modeling and data-driven problem-solving.
Key competencies
- Anomaly detection in time series using mean, standard deviation, and Z-score
- Forecasting stock prices through moving averages and weighted averages as well as linear regression
- Classification of animal species using decision tree and k-NN methods
- Binary Text Classification of Reviews based on a Bag-of-Words Approach
- Creation of KI-generated Texts using Markov Chains
- Analysis of Outliers and their Impact on Forecasting Models
Structure of Modules
Anomaly Detection in Temperature Time Series
Introduction to Statistical Methods for Identifying Outliers in Measurement Data as a Basis for Data-Driven Analysis Models.
Forecasting Stock Prices: Three Methods
Comparison of Basic Forecasting Methods for Modeling Stock Price Developments based on Historical Data.
Classifying Animals with Decision Trees & k-NN
Applying Classical Classification Methods for Structured Assignment of Objects based on Defined Characteristics.
Automatic Recognition of Restaurant Reviews
Introduction to Simple Text Classification Methods through Analysis of Key Words in Review Data.
Continuing Bible Verses with Markov Chains
Modeling Linguistic Patterns for Generating New Texts based on Statistical Word Sequences.
The clearly structured modules enable transparent learning objectives and can be integrated into existing lesson series.
Try out the template in demo access and adapt the content to your teaching situation.