Advanced Python in Excel: Machine Learning
36mAdvanced2024-09-12
Authors
Christian Martinez
Course details
Demand is increasing for data-driven decision-making and the rapid integration of Python in Excel and ML across business sectors. In this course, Finance Transformation Senior Manager Christian Martinez offers timely training that empowers you to efficiently leverage vast amounts of data for competitive advantage, aligning with current market needs.
Learning objectives
Gain proficiency in integrating Python with Excel to implement machine learning models directly within a familiar spreadsheet environment.
Explore practical applications of machine learning in business and finance, such as predictive analytics and automated decision-making processes.
Develop skills in using libraries like pandas, NumPy, and scikit-learn within Excel, enhancing the analytical capabilities of business data processing.
Learn how to use machine learning algorithms like linear regression, random forests, and clustering techniques for business and finance.
Learning objectives
Gain proficiency in integrating Python with Excel to implement machine learning models directly within a familiar spreadsheet environment.
Explore practical applications of machine learning in business and finance, such as predictive analytics and automated decision-making processes.
Develop skills in using libraries like pandas, NumPy, and scikit-learn within Excel, enhancing the analytical capabilities of business data processing.
Learn how to use machine learning algorithms like linear regression, random forests, and clustering techniques for business and finance.
Skills covered
Machine LearningSpreadsheetsMicrosoft ExcelPythonArtificial Intelligence (AI)Programming LanguagesBusiness Software and ToolsOpen SourceMicrosoftSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Introduction
- 02 - What you should know
1. Recap of Python, ML, and Data Cleaning
- 03 - Recap of Python
- 04 - Recap of machine learning
- 05 - Data cleaning and preparation
- 06 - Challenge - How would you solve this problem with ML
- 07 - Solution - How would you solve this problem with ML
2. Applied Machine Learning for Finance and Business
- 08 - Introduction to machine learning concepts
- 09 - Building regression models in Excel
- 10 - Classification models for business data
- 11 - Challenge - Build a regression model
- 12 - Solution - Build a regression model
3. Practical Applications of Machine Learning in Business and Finance
- 13 - Predictive analytics for financial forecasting
- 14 - Automated decision-making processes
- 15 - Real-time data processing and analysis
- 16 - Challenge - Create a financial forecast
- 17 - Solution - Create a financial forecast
4. Advanced Analytical Techniques with Python Libraries
- 18 - Data manipulation with pandas
- 19 - Numerical analysis with NumPy
- 20 - Machine learning with scikit-learn
5. Machine Learning Algorithms for Business and Finance
- 21 - Linear regression for business insights
- 22 - Random forests for predictive modelling
- 23 - Clustering techniques for market segmentation
Conclusion
- 24 - Next steps
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