Daten-, KI- und Cloud-Kurse

Learn how to efficiently collect and download data from any website using R.

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Visualize seasonality, trends and other patterns in your time series data.

Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

In this course, youll learn how to import and manage financial data in Python using various tools and sources.

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

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

Learn to build recommendation engines in Python using machine learning techniques.

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Learn the most important functions for manipulating, processing, and transforming data in SQL Server.

Learn to streamline your machine learning workflows with tidymodels.

Learn how to segment customers in Python.

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Master Amazon Redshifts SQL, data management, optimization, and security.

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

Learn how to identify, analyze, remove and impute missing data in Python.

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.