This course teaches how to systematically prepare, analyze, and clearly visualize data. This includes hands-on work with Python and SQL, creating meaningful visualizations and interactive Power BI dashboards, and communicating analysis results in a way that is tailored to the audience. In addition, the course demonstrates how generative AI can support various steps in the data analytics process.
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Certificates: Data Analytics" certificate
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Examination: Praxisbezogene Projektarbeit mit Abschlusspräsentation
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Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 4 Weeks
Introduction to Data Analytics (approx. 1 day)
Tasks, Areas of Application, and Typical Use Cases of Data Analytics
Data Analytics Processes and CRISP-DM
The Role of the Data Analyst and How It Differs from Data Science, Data Engineering, and Business Intelligence
Classification of Artificial Intelligence and Machine Learning
Python for Data Analytics (approx. 1 day)
Working with Jupyter Notebooks
NumPy and Pandas for Data Analysis
Importing and Exporting Data from Various Sources, e.g., Excel and CSV
Selecting and transforming data
Data Preparation and Exploratory Data Analysis (approx. 3 days)
Data cleaning and transformation with Pandas
Handling missing, incorrect, and outlier data
Merging, grouping, and aggregating data
Exploratory data analysis and deriving initial insights
Fundamentals of statistical analysis
SQL and Data Management (approx. 2 days)
Relational Databases and Data Models
Data Queries and Processing with SQL
Joins, aggregations, and analytical queries
Interaction Between SQL and Python in Data Analysis
Data Quality and Data Protection
Connecting to and Using Different Data Sources and Database Systems
Data Visualization and Data Storytelling (approx. 2 days)
Visualization with Matplotlib, Seaborn, and Plotly
Selecting Appropriate Charts and Visualization Methods
Preparing and interpreting analysis results
Data Storytelling and Communication Tailored to the Audience
Power BI and Interactive Dashboards (approx. 2 days)
Data Import and Preparation with Power Query
Data modeling and relationships
Basics of DAX and metrics
Creating interactive reports and dashboards
Visualization and Communication of Business KPIs
Overview of Alternative Business Intelligence and Visualization Solutions
AI-powered data analysis (approx. 2 days)
Use of generative AI in the data analytics workflow
AI-powered data preparation, analysis, and visualization
Support with Python and SQL queries
Prompting for data analysis and interpretation of results
Critical evaluation of data sources and detection of synthetic and implausible data
Quality assurance, data protection, and responsible use of AI
Business Analytics and Statistical Fundamentals (approx. 2 days)
Key Metrics and KPIs in a Business Context
Descriptive Statistics and Statistical Relationships
Correlation, Causality, and Simple Regression Analyses
Fundamentals of confidence intervals and hypothesis testing
Interpreting Analysis Results and Deriving Data-Driven Recommendations
Project work (approx. 5 days)
To consolidate the content learned
Presentation of the project results
Changes are possible, the course content is updated regularly.
After completing the course, you will be able to process and analyze data using Python and SQL, create meaningful visualizations and interactive dashboards with Power BI, and interpret and communicate analysis results in a way that is tailored to your audience. You will be able to use generative AI specifically to support data analysis.
This course is designed for individuals with a business, technical, or IT background who want to analyze and visualize data and use it to make data-driven decisions.
Data-driven decision-making is playing an increasingly important role in companies and organizations. Consequently, there is a need for professionals who can process, analyze, and clearly visualize data from various sources. Knowledge of Python, SQL, and business intelligence opens up career opportunities in the field of data analytics as well as in data-driven functional and business areas.
Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).