Daten-, KI- und Cloud-Kurse

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Learn to design and run your own Monte Carlo simulations using Python!

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

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

Leverage the power of Python and PuLP to optimize supply chains.

This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.

Discover how to use the income statement and balance sheet in Power BI

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

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

This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.

Learn how to use Python to analyze customer churn and build a model to predict it.

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

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

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

Learn the bag of words technique for text mining with R.

Develop the skills you need to clean raw data and transform it into accurate insights.

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

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

Learn how to design and implement triggers in SQL Server using real-world examples.

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.

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!