Introduction to Artificial Intelligence and Machine Learning

Course Cover
compare button icon

Course Features

icon

Duration

3 weeks

icon

Delivery Method

Online

icon

Available on

Lifetime Access

icon

Accessibility

Mobile, Desktop

icon

Language

English

icon

Subtitles

English

icon

Level

Beginner

icon

Effort

6 hours per week

icon

Teaching Type

Self Paced

Course Description

Are you ready to make your first steps in your career as an artificial intelligence professional? This self-paced course combines engaging lectures with hands-on activities to give you an overview of AI and the future of software solutions. It also demonstrates how AI can be applied to real-world applications.

AI can be used in smart apps to improve efficiency and enrich the lives of people. Machine learning can be used for predictive models of AI. You'll also learn how software can be used for processing, analysing, and extracting meaning from natural language. Chatbots are able to communicate via text and speech between humans as well as AI systems.

Machine learning is an AI application that allows computers to learn from their experience and make improvements automatically. As the foundation of AI, you will learn about all aspects of machine-learning computer algorithms. Learn how AI uses machine learning along with deep learning to solve real-world problems.

How does artificial intelligence work to build better conversational user interfaces (CUIs), and how is conversation-as-a-platform (CaaP) providing new ways to interact directly with companies, important data and key services? This course will show you how intelligent applications, also known as interaction bots or chatbots provide richer, more personal and more human-like experience.

Microsoft has granted accreditation to this course

Course Overview

projects-img

Alumni Network

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Explored, prepared and cleaned data

Applied supervised machine learning techniques

Applied unsupervised machine learning techniques

Modeled performance improvement

Target Students

This course is ideal for, but not limited to, individuals with a basic knowledge of programming (Python would be an advantage, but is not essential) and those who have studied maths and statistics at a high-school level

Course Accreditations

Course Cover