Top Free Artificial Intelligence Courses to Sharpen your Analytical Mind

some of the popular free Artificial Intelligence courses from leading course providers like Coursera, edX, Udemy, etc. These courses will help you learn the intricacies of AI better than an average article or video does.

While there is an alarming situation globally with this COVID-19 pandemic, there is a brighter side to it too! You get to work from home, have plenty of time to take up new hobbies, or even better, upskill yourself! What can be better than utilizing your time by taking up a course that can help you explore the world of artificial intelligence and learn its intricacies? We have curated a list of the most trending free Artificial Intelligence Courses for you.

These free artificial intelligence courses target a broader audience, including the ones who wish to learn to design and code AI algorithms, use “DIY” AI tools and services, or even manage AI projects in their organizations.

Learn more – What is Artificial Intelligence?

Top Free Artificial Intelligence Courses

Taught by the top researchers and educationists of the best universities globally, these artificial intelligence courses are worth taking up. Let’s browse some of these free AI courses from the leading course providers. We hope to help you in making a wise decision.

Welcome to Artificial Intelligence by Udemy

Course Requisite – The course can be taken up by AI/ML/DL aspirants.
Course Description – It is a non-technical course that offers insights into the road map to AI. The course provides in-depth knowledge of Artificial Intelligence and Machine Learning.
Course Details
Rating – 4.2 Stars (1800 ratings)
Duration – 49 Minutes Video
Skill Level – Beginner
Course Curriculum
Section 1 – Introduction to Artificial Intelligence
Section 2 – Road Map for Artificial Intelligence and Machine Learning
Section 3 – Introduction to Machine Learning
Section 4 – Types of Machine Learning

Applied AI with Deep Learning by IBM on Coursera

Course Requisite – You must have prior coding knowledge, preferably python. You should also have a basic understanding of math, including linear algebra.
Course Description – The course will help you to understand different aspects of deep learning and models, and their usage by used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines.
Course Details
Rating – 4.4 Stars (715 ratings)
Duration – 22 Hours
Skill Level – Advanced
Course Curriculum
Week 1 – Introduction to deep learning
Week 2 – DeepLearning Frameworks
Week 3 – DeepLearning Applications
Week 4 – Scaling and Deployment

Must Read – Top Real-World Artificial Intelligence Applications

AI For Everyone by IBM on Coursera

Course Requisite – Nothing! It can be taken by professionals with both technical and non-technical backgrounds.
Course Description – The course gives detailed knowledge about common AI terminology, including neural networks, machine learning, deep learning, and data science, AI ethics, problem-solving in AI, building AI strategies, etc.
Course Details
Rating – 4.8 Stars (9459 ratings)
Duration – 6 Hours
Skill Level – Beginner
Course Curriculum
Week 1 – What is AI?
Week 2 – Building AI Projects
Week 3 – Building AI In Your Company
Week 4 – AI and Society

Knowledge-Based AI: Cognitive Systems by Udacity

Course Requisite – Preferred qualification to take up this course is an undergraduate degree in computer science or related field (typically mathematics, computer engineering, or electrical engineering).
Course Description – This is a core course in artificial intelligence and is a part of the Online Masters Degree (OMS), which is a nanodegree program. It covers structured knowledge representations, problem-solving methodologies, planning, decision-making, and learning methods. With the help of this course, you will get to learn how to design knowledge-based AI agents, build a relationship between knowledge-based artificial intelligence, and learn about human cognition.
Course Details
Duration – 7 Weeks
Skill Level – Advanced
Interactive Quizzes
Self-Paced Learning
Course Curriculum
Introduction to KBAI and Cognitive Systems
Fundamentals, Planning, & Learning
Common Sense Reasoning
Analogical Reasoning
Visuospatial Reasoning
Design & Creativity
Metacognition

Designing the Future of Work by the University of New South Wales on Coursera

Course Requisite – The course can be taken by professionals from any background.
Course Description – The course is a collaboration between UNSW Sydney Art & Design and AMP Amplify. It offers a unique and industry-relevant learning opportunity in the field of artificial intelligence (AI), robotics, and big data. The course offers access to current theory, industry examples, and expert advice from leaders in the field.
Course Details
Rating – 4.7 Stars (39 ratings)
Duration – 13 Hours
Skill Level – Beginner
Course Curriculum
Week 1 – What is the Future of Work?
Week 2 – The Importance of Being Human in a World of Automation
Week 3 – Designing the Future of Work
Week 4 – Industry and Academic Expert Video Profiles

 Also Explore – Machine Learning Courses

Intelligence Tools for the Digital Age by IE Business School on Coursera

Course Requisite – Anyone with a flair to sharpen their analytical skills can take up this course.
Course Description – This course explores new avenues of digital technologies through the usage of new tools like intelligence analysis, mental models, and practical frameworks developed by the US intelligence community. It will prepare the participants for the upcoming digital age and help them acquire sustainable business advantage through structured thinking.
Course Details
Rating – 4.7 Stars (205 ratings)
Duration – 8 Hours
Skill Level – Beginner
Language – English
Course Curriculum
Week 1 – A Toolkit for the Digital Future: Intelligence Analysis for the Business Professional
Week 2 – The Intelligence Analyst’s Mindset
Week 3 – Intelligence Methods: Analysis, Part One (Macro Actors) The Case of Chinese Rare Earth Elements
Week 4 – Intelligence Methods Analysis, Part Two: Micro actors (understanding people/organizations)

You might be interested in – Top 10 Machine Learning Algorithms for Beginners

Intro to Artificial Intelligence by Georgia Tech Masters on Udacity

Course Requisite – The course is designed for students with intermediate experience in Python, they may/may not have studied Machine Learning topics.
Course Description – The course covers the basics of AI and covers a number of topics like machine learning, probabilistic reasoning, robotics, computer vision, and natural language processing.
Course Details
Duration – 4 Months
Skill Level – Intermediate
Language – English
Course Curriculum
Chapter 1 – Fundamentals of AI
Chapter 2 – Applications of AI

Artificial Intelligence for Robotics by Georgia Tech Masters on Udacity

Course Requisite – No coding experience required. You should have a flair to learn AI.
Course Description – The artificial intelligence course is a part of Georgia Tech Masters in Computer Science and covers basic methods in Artificial Intelligence, including probabilistic inference, planning, and search, localization, tracking, and control, with a focus on robotics. The program also covers extensive programming examples and assignments in the context of building self-driving cars.
Course Details
Duration – 2 Months
Skill Level – Advanced
Course Curriculum
Lesson 1 – Localization
Lesson 2 – Kalman Filters
Lesson 3 – Particle Filters
Lesson 4 – Search
Lesson 5 – PID Control
Lesson 6 – SLAM (Simultaneous Localization and Mapping)
Lesson 7 – Runaway Robot Final Project

IBM Applied AI Professional Certificate by IBM on Coursera

Course Requisite – This course can be taken up by professionals from both non-technical and technical backgrounds. Engineers can also take this course to learn the business aspects of AI.
Course Description – This is a professional certificate from IBM and follows IBM Watson AI services and APIs to create smart applications with minimal coding. The course also requires the participants to complete several projects to understand the application of AI and build AI-powered solutions.
Course Details
Rating – 4.5 Stars (19,488 ratings)
Duration – 7 Months
Skill Level – Beginner
Course Curriculum
Course 1 – Introduction to Artificial Intelligence (AI)
Course 2 – Getting Started with AI using IBM Watson
Course 3 – Building AI-Powered Chatbots Without Programming
Course 4 – Python for Data Science and AI
Course 5- Building AI Applications with Watson APIs
Course 6 – Introduction to Computer Vision with Watson and OpenCV

Machine Learning with Python by IBM on Coursera

Course Requisite – This artificial intelligence course can be taken up by professionals from both non-technical and technical backgrounds.
Course Description – The course covers the basics of machine learning using Python, a popular programming language. It offers an overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.
Course Details

Duration – 21 hours
Skill Level – Intermediate
Course Curriculum

Week 1 – Introduction to Machine Learning
Week 2 – Regression
Week 3 – Classification
Week 4 – Clustering
Week 5 – Recommender Systems
Week 6 – Final Project

Fundamentals Of Artificial Intelligence by NPTEL

Course Requisite – This artificial intelligence course can be taken up by final Year B.Tech; M.Tech and Ph.D. students. They should have taken basic courses in Probability and Linear Algebra.

Course Description – The course covers the basics of machine learning using Python, a popular programming language. It offers an overview of the principles and practices of AI to address complex real-world problems like automatic scheduling or autonomous driving. The course is designed to develop a basic understanding of problem-solving, knowledge representation, reasoning, and learning methods of AI.
Course Details
Duration – 12 weeks
Skill Level – Intermediate
Course Curriculum

AI and AI Problem Solving
Problem Solving by Search – I
Problem Solving by Search – II
Knowledge Representation and Reasoning – I
Knowledge Representation and Reasoning – II
Knowledge Representation and Reasoning – III
Reasoning under Uncertainty
Planning
Planning and Decision Making
Machine Learning -I
Machine Learning – II
Machine Learning – III

All The Best!

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