IBM Machine Learning Professional Certificate
Course Features
Duration
6 months
Delivery Method
Online
Available on
Limited Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Effort
3 hours per week
Teaching Type
Self Paced
Course Description
Course Overview
International Faculty
Case Based Learning
Post Course Interactions
Case Studies,Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
What You Will Learn
Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud
Handle categorical and ordinal features, as well as missing values
Articulate why regularization may help prevent overfitting
Describe and use other ensemble methods for classification
Understand metrics relevant for characterizing clusters
Try clustering points where appropriate, compare the performance of per-cluster models
Identify types of problems suitable for survival analysis
Course Content
Module 1: Exploratory Data Analysis for Machine Learning
1. This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course, you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.
Course Instructors
Mark J Grover
Digital Content Delivery Lead
Miguel Maldonado
Machine Learning Curriculum Developer