Curriculum
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
How do you learn with this course?
This online course offers you a particularly practice-oriented learning concept with comprehensive self-study units and a team of mentors who are available to you at all times. A new chapter is activated for you every week. With a time budget of around 6 hours per week, you are sure to reach your goal in 12 weeks. This is how you learn in the course:
Assessment test: In an onboarding meeting at the start of the course, you and the mentoring team will determine what knowledge you already have and which parts of the course you should pay particular attention to. This will prepare you optimally for learning in the self-study units.
Data lab: In the course's learning environment, you can expect videos, interactive graphics, text and, above all, lots of practical exercises with comprehensive datasets and coding tasks. You carry these out directly in the browser - without any installation or configuration effort and with direct success control.
Mentoring team: Your learning coaches are available to answer any questions you may have. They are experienced data analysts who will be happy to help you - via chat, audio or video call.
Webinars: Once a week, you have the opportunity to take part in webinars and immerse yourself in selected specialist data analysis topics.
Career coaching: What professional goals are you pursuing with your further training and how can you achieve them? A team of mentors will be on hand to help you achieve your career goals.
Final project: In your own data project, you will work independently through the entire data pipeline and answer typical questions. At the end, you will present your project in a 1-to-1 feedback session with your mentoring team.
Certificate: After the final project, you will receive your official certificate as a Data Analyst with Python.
This online training course is run by our partner StackFuel GmbH. StackFuel is a specialist in the field of further training in data literacy, data science and AI.
Your benefits
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 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.
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.
Participants
The online training course to become a Data Analyst 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.
Final exam
In your own data project, you will work independently through the entire data pipeline and answer typical questions. At the end, you will present your project in a 1-to-1 feedback session with your mentoring team.
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Auch als deutschsprachiges Online-Training buchbar: Data Analyst