Ementorhub

What you'll learn

Train and evaluate decision trees and random forests for regression and classification.

Train and evaluate support-vector machines (SVM) for regression and classification.

Train and evaluate multi-layer perceptron (ML) artificial neural networks (ANN) for regression and classification.

Train and evaluate convolutional neural networks (CNN) and recurrent neural networks (RNN) for computer vision and natural language processing tasks.

Skills you'll gain

Decision Tree Learning

Natural Language Processing

Computer Vision

Artificial Neural Networks

Machine Learning Algorithms

Applied Machine Learning

Random Forest Algorithm

Artificial Intelligence and Machine Learning (AI/ML)

Deep Learning

Regression Analysis

Supervised Learning

Statistical Machine Learning

There are 5 modules in this course

This fourth and final course within the Certified Artificial Intelligence Practitioner (CAIP) professional certificate continues on from the previous course by introducing more, and in some cases, more advanced algorithms used in both machine learning and deep learning. As before, you'll build multiple models that can solve business problems, and you'll do so within a workflow. Ultimately, this course concludes the technical exploration of the various machine learning algorithms and how they can be used to build problem-solving models.

Build Support-Vector Machines (SVM)

Build Multi-Layer Perceptrons (MLP)

Build Convolutional and Recurrent Neural Networks (CNN/RNN)

Apply What You've Learned