• Learn the basics of AI

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Python Programming

• Intro to Python and Programming Toolkit

• Data Science in Python with scikit-learn

• Regression

• Classification

• Clustering

• Data wrangling with pandas

• 💻 Local installation of Jupyter Book

• 💻 Local installation of Plotly Dash

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Data Engineering & Machine Learning Operations (MLOps)

• Data Engineering basics

TensorFlow and TensorFlow Extended (TFX)

• 💻 Local installation of TensorFlow & TensorFlow Extended
• 💻 Build your first TFX pipeline

Kubeflow

• 💻 Local installation of Kubeflow (MiniKF)
• 💻 Build your first Kubeflow pipeline

Apache Airflow

• 💻 Local installation of Apache Airflow

R Programming

Introduction to R

• First steps in R

Data Wrangling

• Introduction to data wrangling

Regression and Classifiaction models

• Introduction to Regression and Classification with Tidymodels in R

• XGBoost Hyperparameter tuning

• Classification with Tidymodels, Workflows and Recipes

• Data Science with Tidymodels, Workflows and Recipes

• Lasso regression hyperparameter tuning

Clusteranalyse

• Hierarchische Clusteranalyse mit Ward in R

Association Rule Mining

• Introduction to Association Rule Mining in R

Text Mining

• Text Mining in R

Data Exploration

• Data exploration with ggplot2

Create Reports with RMarkdown

• Reporting in RMarkdown

• Introduction to R-Markdown

Webscraping

• Webscraping with R

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SQL

1. Datenexploration (Selektieren, Ordnen und Filtern)

2. Datentypen und Datentransformationen

3. Gruppieren und Aggregieren

4. Tabellen verbinden (Joins)

5. Tabellen modifizieren

6. Subqueries

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I’m a Professor at HdM Stuttgart, where I help students and organizations to learn and use data science, statistics, and machine learning with Python and R programming to extract meaningful information from data. Please feel free to contact me if you are interested in data science seminars or data science consulting.

Copyright: Jan Kirenz (2021), Lizenz: Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0) License