Daten-, KI- und Cloud-Kurse

Lerne, wie du mit Amazon Bedrock auf grundlegende KI-Modelle zugreifen und mit KI arbeiten kannst – ohne dich um komplizierte Infrastruktur kümmern zu müssen.

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

Verbessere deine KNIME-Kenntnisse mit diesem Kurs zu Datentransformationen, Spaltenoperationen und Workflow-Optimierungen.

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Lerne, wie du das Training von LLMs mithilfe von Accelerator und Trainer für verteilte Trainingsprozesse beschleunigst.

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Learn how to pull character strings apart, put them back together and use the stringr package.

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Azure Security

Learn to solve increasingly complex problems using simulations to generate and analyze data.