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
In this course, you will implement data science techniques in order to address business issues:
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.
However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other datadriven situations.
Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business.
This course is also designed to assist students in preparing for the CertNexus® Certified Data Science Practitioner (CDSP) (Exam DSP-110) certification.
To ensure your success in this course, you should
Lesson 1: Addressing Business Issues with Data Science
Topic A: Initiate a Data Science Project
Topic B: Formulate a Data Science Problem
Lesson 2: Extracting, Transforming, and Loading Data
Topic A: Extract Data
Topic B: Transform Data
Topic C: Load Data
Lesson 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
Lesson 4: Designing a Machine Learning Approach
Topic A: Identify Machine Learning Concepts
Topic B: Test a Hypothesis
Lesson 5: Developing Classification Models
Topic A: Train and Tune Classification Models
Topic B: Evaluate Classification Models
Lesson 6: Developing Regression Models
Topic A: Train and Tune Regression Models
Topic B: Evaluate Regression Models
Lesson 7: Developing Clustering Models
Topic A: Train and Tune Clustering Models
Topic B: Evaluate Clustering Models
Lesson 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
Appendix A:
Mapping Course Content to CertNexus® Certified Data Science Practitioner (CDSP) (Exam DSP-110)
This course will help you prepare for the CertNexus Certified Data Science
Practitioner certification CDSP (exam DSP-110)