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Certified Data Science Practitioner (CDSP)

(CDSP-210.AK1) / ISBN : 978-1-64459-727-9
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Skills You’ll Get

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1

Introduction

  • Course Description
  • How To Use This Course
  • Course-Specific Technical Requirements
2

Addressing Business Issues with Data Science

  • TOPIC A: Initiate a Data Science Project
  • TOPIC B: Democratize Data
  • TOPIC C: Formulate a Data Science Problem
  • Summary
3

Extracting, Transforming, and Loading Data

  • TOPIC A: Extract Data
  • TOPIC B: Transform Data
  • TOPIC C: Load Data
  • Summary
4

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
  • Summary
5

Designing a Machine Learning Approach

  • TOPIC A: Identify Machine Learning Concepts
  • TOPIC B: Identify Transformer-Based Deep Learning Concepts
  • TOPIC C: Test a Hypothesis
  • Summary
6

Developing Classification Models

  • TOPIC A: Train and Tune Classification Models
  • TOPIC B: Evaluate Classification Models
  • Summary
7

Developing Regression Models

  • TOPIC A: Train and Tune Regression Models
  • TOPIC B: Evaluate Regression Models
  • Summary
8

Developing Clustering Models

  • TOPIC A: Train and Tune Clustering Models
  • TOPIC B: Evaluate Clustering Models
  • Summary
9

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
  • Summary
10

Glossary

  • glossary

1

Extracting, Transforming, and Loading Data

  • Handling Irregular and Unusable Data
  • Consolidating Data from Multiple Sources
  • Extracting Data with Database Queries
  • Reading Data from a CSV File
2

Developing Classification Models

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