Data Analyst in Python
Analyzing and visualizing data with Python
As the world has become increasingly digital, the demand for data analysis specialists has risen sharply in recent years. This change has made working competently and professionally with data an essential skill. In StackFuel’s Data Analyst course, you will learn the basics of the Python programming language and consolidate them by applying them to real business scenarios. In the Data Lab, StackFuel’s interactive learning environment, you will use real data sets. This makes it easier to integrate the skills you will gain into your day-to-day work life. After the course, you will be able to carry out data analyses with Python on your own and will be able to make data-driven decisions.
The Data Analyst course is suitable for anyone who wants to get to know Python as a programming language and who wants to analyze data themselves. The only requirement to participate is motivation to analyze data by yourself and an interest in learning a programming language in a short amount of time.
At the end of the course, the learning objective is to have the skills to perform complex data analyses and to merge different sources of data (databases & APIs, web crawling). You will also gain an understanding of the work steps that make up a complex analysis as well as best practices when carrying out a data analysis.
Conditions for participation
No previous programming knowledge is required for the Data Awareness course. You will develop these skills in the first module. However, you should be a frequent computer user, and be familiar with common software.
Next start dates
Contact and consultation
Tel: +49 (0) 30 6800 9503
Hands-on learning environment
Participants learn using current technologies and the latest Python libraries.
Advanced technology stack
Our trainings make use of real data sets as well as industry business cases to create hands-on Learning scenarios.
Participants have access to all the computing power they need to complete the course.
Innovative Data Lab
The course takes place in your browser, you don’t need to install any special software.
Python Beginner's Guide
Understand the role of data analysts
Learn basic Python skills in the context of data analyses
Use computer programs to automate data analysis
Complete several practical projects
Data Analytics with Python
Refresh the basics of Python
Import, process and export data with pandas
Data visualization in Python with pandas, matplotlib and other libraries
Apply the foundations of statistics to company data
Learn to work with various data structures
Tap into external data sources
Make data accessible with the help of reports and interactive dashboards
Request the course curriculum for more detail about the course material!
To make better use of the advantages of online courses, such as the flexibility and freedom to do the course wherever you are, StackFuel has added a new option to its range of services: FastTrack courses. This format combines the advantages of our training courses with the opportunity to complete them full-time or part-time, so that you can acquire the relevant knowledge in the field of analytics and data science in the shortest possible time and incorporate it into your company.
StackFuel's specialist courses follow a practical approach that helps employees get into the job roles of the future and gives them the necessary skills to create real added value from data. This is also reflected in the final project that the participants carry out and which our mentoring team, made up of educational data scientists, analyzes and evaluates. Participants receive a certificate based on this at the end of the course, which they can use in various social networks as well as privately, as proof of their newly acquired knowledge and skills.
The Data Lab offers real value, where the practical relevance is particularly noticeable. The tasks were clearly described and illustrated, so that I always knew what I had to do – that was a great experience!
The greatest value for me is the practical relevance and the fact, that I can quickly implement what I have learned and adapt it for myself – that is the real learning success behind the courses.