Programming & Development

Certified Data Science Practitioner (CDSP)

Introduction:

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, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes hands on activities for each topic area. 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, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes hands on activities for each topic area.

Who Should Attend
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.

Course Objectives
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.

Course Outline:

Initiate a Data Science Project
Formulate a Data Science Problem
Extract Data
Transform Data
Load Data
Examine Data
Explore the Underlying Distribution of Data
Use Visualizations to Analyze Data
Preprocess Data
Identify Machine Learning Concepts
Test a Hypothesis
Train and Tune Classification Models
Evaluate Classification Models
Train and Tune Regression Models
Evaluate Regression Models
Train and Tune Clustering Models
Evaluate Clustering Models
Communicate Results to Stakeholders
Demonstrate Models in a Web App
Implement and Test Production Pipelines

Enroll in this course

$3,475.00

Need Help Finding The Right Training Solution?

Our training advisors are here for you.