Daten-, KI- und Cloud-Kurse

Beherrsche strategisches Datenmanagement für Business Excellence.

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

Learn how to clean data with Apache Spark in Python.

Discover how Marketing Analysts use data to understand customers and drive business growth.

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Explore Azure services like Compute, Storage, and Automation, with hands-on experience.

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Learn the core techniques necessary to extract meaningful insights from time series data.

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Learn how to build interactive and insight-rich dashboards with Dash and Plotly.

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Build the foundation you need to think statistically and to speak the language of your data.

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

Learn to bring data into Microsoft Fabric, covering Pipelines, Dataflows, Shortcuts, Semantic Models, security, and model refresh.

Learn about ARIMA models in Python and become an expert in time series analysis.