Ementorhub

What you'll learn

Identify when and how machine learning can applied to solve problems

Apply human-centered design practices to design AI product experiences that protect privacy and meet ethical standards

Lead machine learning projects using the data science process and best practices from industry

Skills you'll gain

Human Centered Design

User Experience Design

Data Processing

Data Management

Human Computer Interaction

Decision Tree Learning

Artificial Neural Networks

Classification And Regression Tree (CART)

MLOps (Machine Learning Operations)

Artificial Intelligence and Machine Learning (AI/ML)

Applied Machine Learning

Unsupervised Learning

Specialization - 3 course series

3) In Course 3, you will perform a basic user experience design exercise for your ML-based solution and analyze the relevant ethical and privacy considerations of the project.

At the conclusion of this course, you should be able to: 1) Explain how machine learning works and the types of machine learning 2) Describe the challenges of modeling and strategies to overcome them 3) Identify the primary algorithms used for common ML tasks and their use cases 4) Explain deep learning and its strengths and challenges relative to other forms of machine learning 5) Implement best practices in evaluating and interpreting ML models

At the conclusion of this course, you should be able to: 1) Identify opportunities to apply ML to solve problems for users 2) Apply the data science process to organize ML projects 3) Evaluate the key technology decisions to make in ML system design 4) Lead ML projects from ideation through production using best practices

Managing Machine Learning Projects

Human Factors in AI