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The certified Data Analyst training - Focus Python enables you to independently clean, process and visualize data and make company-relevant predictions.
You will gain highly sought-after skills in the Python programming language online to qualify you for the job role of Data Analyst or another analytical job role such as Business Intelligence Analyst or Financial Analyst upon successful completion of the career path.
Objective: Introduction to programming with Python
Description: Participants familiarize themselves with the interactive learning environment - the StackFuel Data Lab - and the Python programming language.
Chapter 1: Python Basics
Objective: Learn the basics of programming
Description: Participants navigate through the Data Lab for the first time and get to know the basics of programming. They learn to store numbers and text as variables in Python and to store these as groups in lists. To complete these basics, participants also learn how to read error messages correctly.
Chapter 2: Programming Basics
Objective: Build fundamental programming skills
Description: Participants continue to build their fundamental programming skills. This chapter focuses on applying functions and conditional flow controls.
Chapter 3: Loops and Functions
Objective: Expand knowledge of flow control with loops
Description: The last chapter of the basics module is dedicated to flow control using loops. Participants broaden their abilities by importing additional Python packages. By the end of the chapter, participants know the most important programming concepts that are important working as a data analyst.
Objective: Independent collection, analysis and visualization of data with Python
Description: Participants learn to access, filter, and merge new data sources. They practice making company data available in attractive visualizations tailored to the target audience, and independently carry out classic data processing (importing, filtering, cleaning, and visualizing data).
Chapter 1: Data Pipelines (Pandas)
Objective: Efficient use of Pandas for data analysis
Description: This chapter teaches the efficient use of Pandas – the standard data analysis tool in Python. Participants learn to use it to read, clean, and aggregate data in CSV files.
Chapter 2: Data Exploration (Matplotlib)
Objective: Practice visualizing different types of data
Description: Participants practice visualizing different types of data using marketing data. Numeric data is represented as histograms and scatter plots, while categorical data is represented as column and pie charts.
Chapter 3: Predictions (Statistics)
Objective: Learn statistical concepts and make predictions
Description: Participants learn statistical concepts such as the median and quartiles using product ratings. They identify outliers and make simple predictions using linear and logistic regression.
Chapter 4: Internal Data (SQL)
Objective: Learn SQL for data retrieval
Description: Participants learn to read databases using a human resources database as an example and formulate standard SQL queries.
Chapter 5: External Data (API)
Objective: Access external data sources using APIs
Description: Participants use Python to access information such as web pages and APIs designed by StackFuel on the Internet.
Chapter 6: Advanced Jupyter
Objective: Learn advanced Jupyter functionalities
Description: Participants learn Jupyter functionalities and solve advanced visualization problems such as live updates and interactivity in the context of a stock market scenario.
Chapter 7: Exercise Project
Objective: Apply Python skills to a practical project
Description: Participants analyze a New York taxi data set with over one million trips and use their Python skills as independently as possible to answer certain questions.
Chapter 8: Final Project
Objective: Complete a comprehensive data analysis project
Description: Participants analyze customer churn for a telecommunications company. They work through the entire data pipeline independently and answer typical questions. They then present their project in a 1-on-1 feedback session with the StackFuel mentor team.
Find your training program with us and start your data career! Book a non-binding consultation now.
Our training courses are developed and produced by our own team of data scientists and subject matter experts, who provide you as a participant with personal mentoring during the course. We not only focus on realistic and practical content, but also ensure that all your questions are answered in a personal exchange and thus guarantee your learning success.
Thanks to our "learning-by-doing" principle, you will learn in our interactive learning environment with realistic data sets and real business cases from the industry, preparing you perfectly for a successful career start in a data job.
With StackFuel, you can rely on a market leader with Germany's most innovative learning platform to develop your data skills in a practical way. In certified training programs, you learn online, flexibly and with 80 % of practical content.
This will enable you to make a lateral entry as a data analyst or data scientist and learn how to use data and the basics of artificial intelligence professionally. Your new data career starts with your online training at StackFuel.
Data has become an integral part of our (professional) lives. In almost all areas, data helps you to better understand facts and make more precise decisions. Data skills are the key to being able to use and interpret data correctly. Even though you may not realize it, you work with, interact with and generate data every day.
This data is becoming increasingly important for companies and is the basis for decisions and business models, which makes data professionals incredibly important for companies.
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