Huge progress has been made in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Much of this data analysis and machine learning work is completed leveraging modern scripting and programming skills, such as R or Python programming, for example. It's easy for Excel users not fluent in these skills or languages to feel sidelined from this innovation wave. However, that isn't the reality. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel.
Data Analysis and Machine Learning with Excel training course explores the fast-changing field and how experienced Excel users can leverage their skills to contribute. The course starts by providing an introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every lesson, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed.
By attending Data Analysis and Machine Learning with Excel workshop, delegates will learn to:
- Use Excel to preview and cleanse datasets
- Understand correlations between variables and optimize the input to machine learning models
- Use and evaluate different machine learning models from Excel
- Understand the use of different visualizations
- Basic concepts and calculations to understand how artificial neural networks work
- Connect Excel to the Microsoft Azure cloud
- Get beyond proof of concepts and build fully functional data analysis flows
- Basic to intermediate IT skills and machine learning with Microsoft Excel 2019 knowledge
- Good foundational mathematics or logic skills
- Basic Linux skills, including familiarity with command-line options such as ls, cd, cp, and su
- Analyst, Data Scientist, and other professionals who want a practical guide to extract the most out of Excel for data preparation, applying machine learning models, and understanding the outcome of your data analysis.