Predictive Analytics Essential Training: Data Mining
With Keith McCormick
Liked by 955 users
Duration: 1h 54m
Skill level: Intermediate
Released: 10/7/2021
Course details
Are you a data science practitioner, looking to develop or enhance your skills in predictive analysis and data mining? This course provides several “big picture” insights, via instructor Keith McCormick, a veteran practitioner who has completed dozens of real-world projects. Keith begins by introducing you to key definitions and processes that you will need to complete the course successfully. He steps you through defining the problem you need your predictive analysis to address, then focuses on how to make sure you meet the data requirements and how good data preparation improves your data mining projects. Keith dives into the skill sets and resources that you need and the problems you will face. Then he goes over the steps to find the solution and put it to work with probabilities, propensities, missing data, meta modeling, and much more. Keith finishes up with detailed explanations of CRISP-DM and Tom Khabaza’s nine laws of data mining, plus Tom’s new 10th law.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
-
Showcase on your LinkedIn profile under “Licenses and Certificate” section
-
Download or print out as PDF to share with others
-
Share as image online to demonstrate your skill
Meet the instructor
Learner reviews
-
Pradhakshana Duraiswamy
Pradhakshana Duraiswamy
💼Data Analyst | Actively Seeking Opportunities | Proficient in R, Python, SQL, Excel, Tableau, Data Analysis | Google Data Analytics Professional &…
-
-
Contents
What’s included
- Test your knowledge 8 quizzes
- Learn on the go Access on tablet and phone
- Stay up to date Continuing Education Units
Similar courses
Download courses
Use your iOS or Android LinkedIn Learning app, and watch courses on your mobile device without an internet connection.