Data Analyst with Python

1. The Python guide for beginners

• Working with the Data Lab.
• Basics and concepts in Python.
• Saving numbers and texts as variables.
• Bundling variables as groups in lists.
• Reading and understanding error messages correctly.

2. Programming basics

• Programming basics for data analysts.
• Using functions and methods.
• Process controls with the help of conditions.

3. Loops and functions with Python

• Flow control with the help of loops.
• Extending the functional scope of the code.
• Importing additional Python packages.
• Programming concepts for data analytics.

4. Create data pipelines with pandas

• Get to know and use pandas.
• Importing CSV files correctly.
• Cleaning and aggregating data.

5. Exploring data with matplotlib

• Visualizing different levels of data.
• Displaying numerical data as histograms.
• Displaying numerical data as scatter plots.
• Visualizing categorical data as column and pie charts.

6. Making statistically based predictions

• Overview of statistical principles.
• Understanding and using medians and quartiles correctly.
• Identifying outliers.
• Predictions with linear and logistic regression.

7. Incorporating internal data from SQL databases

• Important queries with SQL.
• Making your own selections.
• Reading data using the example of a personnel database.

8. Incorporating external data via APIs

• Reading data from online databases.
• Scraping data from websites.
• Reading data via APIs.

9. Data visualization with Advanced Jupyter

• Advanced functions in Jupyter Notebooks.
• Presenting data in Jupyter Notebooks.
• Dashboards with live updates and interactive features.

10. Exercise project

• Complete data project from data cleansing to visualization.
• Data analysis with professional data set (with over one million cab rides in New York).
• Analysis task for independent implementation.

11. Final project

• Audit project on customer churn in a telecommunications company.
• Independent analysis of the data project.
• Presentation of results and 1:1 feedback meeting with mentoring team.
• Receipt of the certificate for Data Analyst with Python.

Lerndauer: 15 weeks (6 h/week)

Mit dieser Veranstaltung sind sie flexibel: Diese Veranstaltung wird vollständig online ausgeliefert!

Ablauf: Zum Start des Fernkurses haben Sie über Ihre Online-Lernumgebung Zugriff auf alle Lerninhalte. Sofern der gebuchte Fernkurs eine gedruckte Unterlage beinhaltet, erhalten Sie diese sieben Tage nach Starttermin.

Starttermine: Dieser Kurs startet mind. 1x pro Monat, Sie werden auf den nächst möglichen Starttermin gebucht.

In this practice-oriented training course, you will learn how to carry out data analyses with large data sets independently.

You will learn how to use Python effectively, 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.

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.