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Course Outline
Introduction to Google Gemini AI
- Overview of AI in data analysis
- Capabilities of Google Gemini AI
- Setting up the Gemini AI environment
Connecting Data Sources
- Importing data into Gemini AI
- Data cleaning and preprocessing
- Ensuring data security and privacy
Exploring Data with Gemini AI
- Using natural language queries
- Understanding Gemini AI's responses
- Advanced query techniques
Data Analysis and Insights
- Identifying patterns and anomalies
- Statistical analysis with Gemini AI
- Predictive modeling and forecasting
Data Visualization
- Designing effective visualizations
- Customizing charts and graphs
- Interactive dashboards with Gemini AI
Communicating Insights
- Storytelling with data
- Preparing reports and presentations
- Best practices for data-driven decision making
Summary and Next Steps
Requirements
- Basic understanding of data analysis concepts
- Familiarity with data visualization tools is recommended
Audience
- Data analysts
- Business professionals
21 Hours
Testimonials (5)
Dużo cierpliwości
Mateusz - WestWind Energy Polska Sp. z o.o.
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The trainer adapted the materials and contents to what he thought would be best for us and he succeeded. The quality of the training was excellent.
Jorge Sanchez Hernandez - CSMART - Carnival
Course - QGIS for Geographic Information System
I genuinely enjoyed the lots of labs and practices.
Vivian Feng - Destination Canada
Course - Data Analysis with SQL, Python and Spotfire
Professional and very practical, usuefull in a daily work
Jozefin Rékasi - SC Automobile Dacia SA
Course - Advanced Data Analysis with TIBCO Spotfire
It covered the areas i said i was interested in before the course: data relationships, using python script. Connecting to databases will be covered in the advanced module.
