Course Objectives
In this course, you will learn to:
- Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.
Agenda
- Topic A: Initiate a Data Science Project
- Topic B: Formulate a Data Science Problem
- Topic A: Extract Data
- Topic B: Transform Data
- Topic C: Load Data
- Topic A: Examine Data
- Topic B: Explore the Underlying Distribution of Data
- Topic C: Use Visualizations to Analyze Data
- Topic D: Preprocess Data
- Topic A: Identify Machine Learning Concepts
- Topic B: Test a Hypothesis
- Topic A: Train and Tune Classification Models
- Topic B: Evaluate Classification Models
- Topic A: Train and Tune Regression Models
- Topic B: Evaluate Regression Models
- Topic A: Train and Tune Clustering Models
- Topic B: Evaluate Clustering Models
- Topic A: Communicate Results to Stakeholders
- Topic B: Demonstrate Models in a Web App
- Topic C: Implement and Test Production Pipelines
FREE
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Course Type: Instructor Led