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Durch Klick auf die Schaltfläche akzeptierst du unsere Nutzungsbedingungen, unsere Datenschutzrichtlinie und die Speicherung deiner Daten in den USA.Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.
Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.
Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.
Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.
Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.
Erlerne den Umgang mit kontinuierlichen Datenströmen mithilfe von serverlosen Technologien basierend auf AWS.
In this course you will learn to fit hierarchical models with random effects.
Learn how to write recursive queries and query hierarchical data structures.
Learn how to make GenAI models truly reflect human values while gaining hands-on experience with advanced LLMs.
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.
Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
In this course youll learn how to perform inference using linear models.
Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.
Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Learn to build pipelines that stand the test of time.
Nutze die Überlebensanalyse, um mit Zeit-zu-Ereignis-Daten zu arbeiten und die Überlebenszeit vorherzusagen.
Learn how to load, transform, and transcribe speech from raw audio files in Python.
Learn to use the Bioconductor package limma for differential gene expression analysis.
In this course youll learn techniques for performing statistical inference on numerical data.
Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training