Machine Learning Certification Course in Dublin, Ireland

By the end of this Machine Learning course, you will be able to accomplish the following: 

• Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
• Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project.
• Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.
• Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbours, K-means clustering and more.
• Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning.
• Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems

There is an increasing demand for skilled machine learning engineers across all industries, making this Machine Learning certification course well-suited for participants at the intermediate level of experience. We recommend this Machine Learning training course for the following professionals in particular:

• Developers aspiring to be a data scientist or machine learning engineer
• Analytics managers who are leading a team of analysts 
• Business analysts who want to understand data science techniques
• Information architects who want to gain expertise in machine learning algorithms 
• Analytics professionals who want to work in machine learning or artificial intelligence
• Graduates looking to build a career in data science and machine learning
• Experienced professionals who would like to harness machine learning in their fields to get more insights

Simplilearn’s Machine Learning course is a hands-on, code-driven training that will help you apply your machine learning knowledge. You will work on 4 projects that encompass 25+ ancillary exercises and 17 machine learning algorithms. 

Project 1: Build a Predictive Model for Housing Prices  
This project involves building a predictive model for determining housing prices in California using US census data. You will analyze various metrics such as population, median income, median housing price, and more for each block group to predict the home prices in any given district. 

Project 2: Build a Phishing Website Detector Using LR Algorithms
The purpose of the project is to build a machine learning model that is trained to use LR algorithms to detect phishing website datasets. 

Project 3: Build a Phishing Website Detector Using KNN Algorithms
The purpose of the project is to build a machine learning model that is trained to use KNN algorithms to detect phishing website datasets. 

Project 4: Build an MNIST Classifier
The purpose of the project is to train a model on the MNIST image database to detect images with 5 digits.