Data-Science-Kurse

Step right into the dynamic world of data modeling with Snowflake!

Master the key concepts of data management, from life cycle stages to security and governance.

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Using Python and NumPy, learn the most fundamental financial concepts.

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

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

To understand Fabric’s main use cases, you will explore various tools in the seven Fabric experiences.

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

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

Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Learn the fundamentals of data visualization using Google Sheets.

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

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

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

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

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

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

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

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

Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.

This course will show you how to integrate spatial data into your Python Data Science workflow.

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

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

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.