Webinar - Haufe Akademie GmbH & Co. KG
Termin | Ort | Preis* |
---|---|---|
16.09.2024- 02.03.2025 | online | 5.176,50 € |
28.10.2024- 13.04.2025 | online | 5.176,50 € |
09.12.2024- 25.05.2025 | online | 5.176,50 € |
10.02.2025- 10.08.2025 | online | 5.176,50 € |
24.03.2025- 21.09.2025 | online | 5.176,50 € |
05.05.2025- 02.11.2025 | online | 5.176,50 € |
16.06.2025- 14.12.2025 | online | 5.176,50 € |
1. Basics of data analytics with Python
2. Linear algebra
3. Probability distribution
4. Supervised learning (regression)
5. Supervised learning (classification)
6. Unsupervised learning (clustering)
7. Unsupervised learning (dimension reduction)
8. Identification and excluding outliers
9. Collecting and merging data
10. Logistic regression
11. Decision trees and random forests
12. Support Vector Machines
13. Neural networks
14. Visualization and model interpretation
15. Using distributed databases
16. Exercise project
17. Final project
In this practice-oriented training course, you will learn how to carry outdata analyses with large data sets independently.
You will learn how to use Python competently, how to use the programming language for data analysis and how to create effective visualizations.
You will learn how to connect different data sources, filter and merge data from them.
You will learn comprehensive methods, algorithms and technologies of machine learning and how to use them with Python packages.
You will learn everything you need to know about the use of deep learning and create an artificial neural network with multiple layers
After the training, you will be able to visualize company data in a meaningful way and make it interactively accessible in dynamic dashboards.
The technical entry hurdles are minimized by the use of Jupyter Notebooks, with which you can carry out the programming exercises directly in the browser.
The online training course to become a Data Scientist with Python is suitable for anyone who wants to learn Python as a programming language and use it to carry out data analyses independently. No special requirements need to be met. The course is also suitable for career changers.