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SAP Learning

Getting Started with Data Science

via SAP Learning

Overview

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In 2012, Harvard Business Review named data science the "sexiest job of the 21st century." Why are data scientists in such demand these days? The answer is that over the past decade, there has been an explosion in the data generated and retained by companies, and they need to leverage and exploit it. Data scientists are the people who make sense out of all this data and figure out just what can be done with it.

If you’re interested in learning about data science, this course will introduce you to the fundamentals of data preparation, predictive modeling, data science, and the deployment and maintenance of models in a business environment following a tried and tested project methodology.

Data science is a complex subject to understand, but in this course, you’ll learn about the fundamental principles, look at how the algorithms can add value to your business, and complex processes will be demystified.

Syllabus

  • Business and Data Understanding
    • Introduction to the Course
    • Introduction to Data Science
    • Introduction to Project Methodologies
    • Business Understanding Phase – Overview
    • Defining Project Success Criteria
    • Data Understanding Phase – Overview
    • Initial Data Analysis and Exploratory Data Analysis
    • Downloads
    • Assignment Week 1
  • Data Preparation
    • Data Preparation Phase – Overview
    • Predictive Modeling Methodology – Overview
    • Data Manipulation
    • Data Encoding
    • Selecting Data – Variable and Feature Selection
    • Downloads
    • Assignment Week 2
  • Modeling (1)
    • Modeling Phase – Overview
    • Detecting Anomalies
    • Association Analysis
    • Cluster Analysis
    • Unit 5 A: Classification Analysis with Regression
    • Unit 5 B: Classification Analysis with Regression
    • Downloads
    • Assignment Week 3
  • Modeling (2)
    • Classification Analysis with Decision Trees
    • Classification Analysis with KNN, NN, and SVM
    • Time Series Analysis
    • Ensemble Methods
    • Simulation and Optimization
    • Downloads
    • Assignment Week 4
  • Evaluating Model Performance
    • Model Performance Metrics
    • Model Testing
    • Improving Model Performance
    • Evaluation Phase – Overview
    • Evaluating Model Performance
    • Downloads
    • Assignment Week 5
  • Deployment and Maintenance
    • Deployment Phase – Overview
    • Deployment Options
    • Monitoring and Maintenance
    • Data Science Applications and References
    • Downloads
    • Assignment Week 6

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