- Understanding Machine Learning Concepts
- Data Preprocessing and Feature Engineering
- Model Selection and Evaluation
- Implementing Machine Learning Algorithms
- Hyperparameter Tuning
- Model Deployment and Integration
- Ethical Considerations and Bias in Machine Learning
- Continuous Learning and Model Maintenance
You'll learn the fundamentals of data analysis with Python. Through the workshop, you will understand the six steps of data analysis processes as well as know how to read data from sources like CSV files and SQL, and how to use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.
This Training is design to introduce the foundamental on how to shape and transform your data before the data analysis using Power Query Editor. You will discover how to navigate this intuitive tool and get to grips with Power BI’s Data, Model, and Report views. You’ll load multiple datasets in the Data view, build a data model to understand the relationships between your tables in Model view, and create your first bar graph and interactive map visualization in Report view. You’ll also practice using Power Query Editor to prep your data for analysis.
Through hands-on exercises, you’ll learn how to change and format a wide range of visualizations, before moving on to sorting data and creating hierarchies—making it possible for you to drill into your reports.
