For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words.
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Description
1 - Addressing Business Issues with Data Science
Topic A: Initiate a Data Science Project
Topic B: Formulate a Data Science Problem
2 - Extracting, Transforming, and Loading Data
Topic A: Extract Data
Topic B: Transform Data
Topic C: Load Data
3 - Analyzing Data
Topic A: Examine Data
Topic B: Explore the Underlying Distribution of Data
Topic C: Use Visualizations to Analyze Data
Topic D: Preprocess Data
4 - Designing a Machine Learning Approach
Topic A: Identify Machine Learning Concepts
Topic B: Test a Hypothesis
5 - Developing Classification Models
Topic A: Train and Tune Classification Models
Topic B: Evaluate Classification Models
6 - Developing Regression Models
Topic A: Train and Tune Regression Models
Topic B: Evaluate Regression Models
7 - Developing Clustering Models
Topic A: Train and Tune Clustering Models
Topic B: Evaluate Clustering Models
8 - Finalizing a Data Science Project
Topic A: Communicate Results to Stakeholders
Topic B: Demonstrate Models in a Web App
Topic C: Implement and Test Production Pipelines
Audience
This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.