Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products.
Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services.
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure thatthey protect the privacy of users.
Course Objectives:
• Specify a general approach to solve a given business problem that uses applied AI and
ML.
• Collect and refine a dataset to prepare it for training and testing.
• Train and tune a machine learning model.
• Finalize a machine learning model and present the results to the appropriate audience.
• Build linear regression models.
• Build classification models.
• Build clustering models.
• Build decision trees and random forests.
• Build support-vector machines (SVMs).
• Build artificial neural networks (ANNs).
• Promote data privacy and ethical practices within AI and ML projects.
Target Students:
The skills covered in this course converge on three areas—software development, applied math and statistics, and business analysis.
Target students for this course may be strong in one or two or these of these areas and looking to round out their skills in the other areas so they can apply artificial intelligence (AI) systems, particularly machine learning models, to business problems.
So the target student may be a programmer looking to develop additional skills to apply machine learning algorithms to business problems, or a data analyst who already has strong skills in applying math and statistics to business problems, but is looking to develop technology skills related to machine learning.
A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.
Pre-requisite:
To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing. You can obtain this level of knowledge by taking the CertNexus AIBIZTM (Exam AIZ- 110) course.
You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++. You can obtain this level of skills and knowledge by taking the following Logical Operations or comparable course:
• Database Design: A Modern Approach
• Python® Programming: Introduction
• Python® Programming: Advanced
At MIGC Australia, we are focused on your future career aspirations. It is Melbourne International Graduate College main priority to enhance your various skills so you can access a range of academic and employment pathways in Australia and reach your educational and professional goals.
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Our industry leading training with eLearning platform is addressing the national skills gap by delivering engaging and addictive learning programs to train them in every stage of their careers.
As artificial intelligence (AI) and automation become more prevalent across workplaces in all sectors, ensuring policies appropriately factor for the social and ethical implications of these technologies is increasingly important.
In a world that's changing faster than ever, don't get left behind. Step abroad our course tailored for the ambitious, the forward-thinkers, and the digital enthusiasts.
The majority of modern AI examples rely on deep learning and natural language processing, and these technologies enable computers to process large quantities of data and recognise patterns within that data to complete specific tasks and activities.
Welcome to the fourth industrial revolution, where artificial intelligence (AI) and machine learning increasingly shape the business landscape. As these technologies continue to evolve, organisations and service providers face increased risks around liability, consumer trust
Artificial Intelligence Training provides a comprehensive knowledge of Artificial Intelligence and Machine Learning from beginners to Intermediate Level.
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