One challenge in the data science lifecycle is understanding the problem or opportunity, the next challenge is acquiring, understanding, and preparing data for the modeling phase. This step in the data science process is estimated to take up to 50% of the time allotted for a data science project.
This course addresses how to translate the problem statement into data sources, explore the data for relationships and recognize patterns, identify the starting inputs for the model, preparing data, and validating it for the model fitting process.
You will learn:
Module 1. Introduction to Crisp DM (21 min)
Module 2. Data Sources Identification (20 min)
Module 3. Exploratory Data Analysis (37 min)
Module 4. Data Preparation for Modeling (30 min)
Module 5. Data Pipelines (10 min)
Module 6. Visualization Techniques (33 min)
Module 7. Data Quality and Integrity (36 min)
–here- to download a more detailed outline of this course.
This exam tests knowledge and understanding of basic concepts, principles, and terminology of data understanding and preparation for business analytics.
Number of Questions: 20
Time Limit: 40 Minutes
Passing Score: 70%
Once you pass the exam, you will receive a Certificate of Education
documenting that you have demonstrated mastery of the topic. Course
exams count towards eLC certification programs. Visit our Certification page for more information about our various programs.
We recommend that you take detailed notes and review the course material multiple times before taking this exam.
Click here to learn more about CIMP exams.