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Data Analysis and Machine Learning in Excel is a three-day, foundation-level, hands-on course that explores this fast-changing field and how experienced Excel users can leverage their skills to contribute.
Unlimited Duration
March 3, 2021
This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. In this course you will learn about:
· 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
· Learn the basic concepts and calculations to understand how artificial neural networks work
· Learn how to connect Excel to the Microsoft Azure cloud
· Get beyond proof of concepts and build fully functional data analysis flows
Course Curriculum
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- Technical requirements 00:00:00
- Understanding learning and models 00:00:00
- Focusing on model features 00:00:00
- Studying machine learning models in practice 00:00:00
- Comparing underfitting and overfitting 00:00:00
- Evaluating models 00:00:00
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- Technical requirements 00:00:00
- Understanding supervised learning with multiple linear regression 00:00:00
- Understanding supervised learning with decision trees 00:00:00
- Understanding unsupervised learning with clustering 00:00:00
- Technical requirements 00:00:00
- Importing data from a text file 00:00:00
- Importing data from another Excel workbook 00:00:00
- Importing data from a web page 00:00:00
- Importing data from Facebook 00:00:00
- Importing data from a JSON file 00:00:00
- Importing data from a database 00:00:00
- Technical requirements 00:00:00
- Building a scatter diagram 00:00:00
- Calculating the covariance 00:00:00
- Calculating the Pearson’s coefficient of correlation 00:00:00
- Studying the Spearman’s correlation 00:00:00
- Understanding least squares 00:00:00
- Focusing on feature selection 00:00:00
- Technical requirements 00:00:00
- Modeling and visualizing time series 00:00:00
- Forecasting time series automatically in Excel 00:00:00
- Studying the stationarity of a time series 00:00:00
- Technical requirements 00:00:00
- Introducing the perceptron – the simplest type of neural network 00:00:00
- Building a deep network 00:00:00
- Understanding the backpropagation algorithm 00:00:00
- Automatic data analysis flows 00:00:00
- Automated machine learning 00:00:00
Course Reviews
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