Duration
6 weeks (6-8 hours per week)
About this course
Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.
In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using Python, and Azure Notebooks.
Length: 6 weeks
Effort: 6-8 hours per week
Level: Intermediate
What you'll learn
After completing this course, you will be familiar with the following concepts and techniques:
- Data exploration, preparation and cleaning
- Supervised machine learning techniques
- Unsupervised machine learning techniques
- Model performance improvement
Course Syllabus
- Introduction to Machine Learning
- Exploring Data
- Data Preparation and Cleaning
- Getting Started with Supervised Learning
- Improving Model Performance
- Machine Learning Algorithms
- Unsupervised Learning
Note: This syllabus is preliminary and subject to change.
This is a version-specific reference outline. Confirm the current syllabus and delivery arrangements with EIEIO.