Artificial Intelligence is rapidly changing the way we live and work. From self-driving cars to personalized healthcare, AI is transforming almost every aspect of our lives. As the demand for AI technology continues to grow, so does the demand for skilled professionals who can design, develop, and implement these systems.
If you’re interested in AI, there’s no better time to start learning. The good news is that there are plenty of free AI courses available online that you can take at your own pace. In this article, we’ve compiled a list of the top 15 free AI courses on Coursera, based on feedback and recommendations from experts in the field. Whether you’re a complete beginner or an experienced professional looking to up-skill, these courses will provide you with a solid foundation in AI concepts, tools, and techniques.
How to Access AI Courses for Free
Coursera offers several payment models for its courses. Some courses are available to audit for free, which means you can access the course materials and lectures without paying, but you won’t receive a certificate upon completion. Other courses require payment to enroll and receive a certificate. Coursera also offers subscription models, such as Coursera Plus, which provides unlimited access to thousands of courses and specializations for a monthly fee. Additionally, some courses offer financial aid to learners who cannot afford to pay for the course.
Essentially, you can view the course content for free, but you are required to pay if you want to receive a certification. So, without further ado, let’s dive into the world of AI and explore the top free courses available on Coursera.
The Best Introductory Courses on Artificial Intelligence
1.Introduction to Artificial Intelligence
Go here: Coursera Introduction to AI by IBM
This course provides a comprehensive overview of artificial intelligence and its practical applications. It covers topics such as search algorithms, machine learning, and natural language processing. Suitable for beginners with no prior programming experience.
2.Supervised Machine Learning
Go here: Coursera Supervised Machine Learning by Stanford
This course teaches the basics of machine learning, including supervised and unsupervised learning, decision trees, and clustering. Suitable for beginners with some prior programming experience. Real-world applications include predictive modeling, recommendation systems, and anomaly detection.
3.Neural Networks and Deep Learning
Go here: Coursera Neural networks and Machine Learning by Deeplearning.AI
This course covers the fundamentals of neural networks and deep learning, including convolutional and recurrent neural networks. Suitable for beginners with some prior programming experience. Real-world applications include image and speech recognition, natural language processing, and game playing.
4.Python for Data Science and AI
Go here: Coursera Python for Data Science and AI by IBM
This course covers the basics of Python programming for data analysis and AI, including data manipulation, visualization, and machine learning. Suitable for beginners with no prior programming experience. Real-world applications include data analysis, predictive modeling, and natural language processing.
5.Applied Data Science with Python
Go here: Coursera Applied Data Science with Python by University of Michigan
This course covers the basics of data science, including data manipulation, visualization, and machine learning using the Python programming language. Suitable for beginners with some prior programming experience. Real-world applications include fraud detection, recommendation systems, and image recognition.
6.Data Science Math Skills
Go here: Coursera Data Science with Maths by Duke University
This course covers the mathematical foundations of data science, including probability, statistics, linear algebra, and calculus. Suitable for beginners with no prior mathematical background. Real-world applications include predictive modeling, natural language processing, and recommendation systems.
7.IBM AI Engineering
Go Here: Coursera AI Engineering by IBM
This course covers the basics of AI engineering, including machine learning, deep learning, and neural networks. Suitable for beginners with some prior programming experience. Real-world applications include predictive modeling, image recognition, and natural language processing.
8.Python Data Structures
Go here: Coursera Python Data Structures by Univerisity of Michigan
This course covers the basics of Python programming and data structures, including lists, tuples, and dictionaries. Suitable for beginners with no prior programming experience. Real-world applications include data analysis, predictive modeling, and natural language processing.
9.Statistics for Data Science with Python
This course covers the basics of statistics for data science, including probability distributions, hypothesis testing, and regression analysis. Suitable for beginners with some prior programming experience. Real-world applications include predictive modeling, recommendation systems, and natural language processing.
https://www.coursera.org/learn/statistics-for-data-science-python
10.AI for Everyone
This course provides a broad overview of AI and its impact on society and business. Suitable for beginners with no prior programming experience. Real-world applications include predictive modeling, recommendation systems, and natural language processing.
https://www.coursera.org/learn/ai-for-everyone
11.Reinforcement Learning by University of Alberta
This course covers the basics of reinforcement learning, which is a type of machine learning that focuses on taking actions to maximize rewards. It’s suitable for learners with some prior knowledge of machine learning and programming. This course can be applied to various fields, such as robotics and game development.
https://www.coursera.org/learn/reinforcement-learning-in-finance
12.Machine Learning with Python by IBM
This course covers the fundamentals of machine learning using Python programming. It’s suitable for learners with some basic programming knowledge. This course can be applied in various fields, such as finance and healthcare.
https://www.coursera.org/learn/machine-learning-with-python
13.Deep Learning by deeplearning.ai
This course covers deep learning, a type of machine learning that uses artificial neural networks to model complex patterns. It’s suitable for learners with some prior knowledge of machine learning and programming. This course can be applied in various fields, such as image and speech recognition.
https://www.coursera.org/specializations/deep-learning
14.Mathematics for Machine Learning by Imperial College London
This course covers the mathematical foundations of machine learning, such as linear algebra and calculus. It’s suitable for learners with some prior knowledge of mathematics and programming. This course can be applied in various fields, such as data analysis and artificial intelligence research.
https://www.coursera.org/specializations/mathematics-machine-learning
15.Applied Data Science with Python by IBM
This course covers the fundamentals of data science using Python programming. It’s suitable for learners with some basic programming knowledge. This course can be applied in various fields, such as business and healthcare.
https://www.coursera.org/specializations/data-science-python
Get Started Today
Whether you’re interested in learning the basics of AI or developing advanced skills in machine learning, natural language processing, or computer vision, the free courses on Coursera offer a wealth of knowledge and resources to help you succeed. With options for beginners and experts alike, there’s no better time to dive into the exciting world of artificial intelligence.