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We are in an era where Artificial Intelligence has been applied in many businesses and brings many values from AI tools. With so many benefits, there are abundant companies looking for AI experts who can provide these values.
Do you want to be one of these AI experts? Well, you can do it now. For Free!
There are many courses from top universities, such as Stanford University that are open for access.
So, what are these AI free courses from Stanford University? Let’s get into it.
StanfordOnline: Statistical Learning with Python
To start with Artificial Intelligence in the modern era, you should understand the statistics methodology and Python programming.
Statistics would be important as the concepts are used in many AI foundational tools, and it’s an important field to understand the mechanisms of AI. Effectively, statistical knowledge would lead you to build a better AI.
On the other hand, Python is the programming language used to build modern AI tools. So, it’s important to learn them as well.
Statistical Learning with Python from Stanford University course would teach you basic statistical methods and supervised learning while still devoting the usage of Python. You would become familiar with how statistical modeling works, and it would help you understand the next course as well.
Stanford also provides free book material to accompany this course, which you can access on their website.
CS229: Machine Learning
Machine Learning might be considered the subset of Artificial Intelligence, but modern AI tools require a strong Machine Learning foundation. To develop a great AI, we need machine learning knowledge as it allows us to drive where the AI would go and enhance the output.
You would learn many Machine Learning foundations in the CS229 Machine Learning course at Stanford University. These include:
- Supervised Learning
- Unsupervised Learning
- Learning Theory
- Reinforcement Learning
- Adaptive Theory
- Machine Learning Applications
This course would strengthen your Machine Learning foundation and, in turn, Artificial Intelligence.
Intro to Artificial Intelligence
Let’s learn the basics of Artificial Intelligence with the Intro to Artificial Intelligence course from Stanford University. This course could initiate your AI learning as all the foundation you need is one course.
From 22 lessons and 9 practice exams, you would learn several concepts, including:
- Probability
- Machine Learning
- Game Theory
- Computer Vision
- Robotics
- Natural Language Processing
These lessons would give you the confidence to explore artificial intelligence in depth.
CS221: Artificial Intelligence: Principles and Techniques
The next course is more in-depth learning about AI, as we would explore much more than the foundational in the CS221: Artificial Intelligence: Principles and Techniques by Stanford University.
The course would provide you with many Artificial Intelligence techniques for implementing various AI systems you would need to know, including:
- Search
- Markov decision processes
- Game playing
- Constraint satisfaction
- Graphical models
- Logic
It’s quite an advanced course, so you might want to refresh many of the foundational courses recommended by Stanford before following this course.
The AI Awakening: Implications for the Economy and Society
Lastly, we need to learn about the impact of AI on becoming a great AI expert. We might understand the technical aspects, but knowing how to make a difference with AI separates us from other talents.
The AI Awakening: Implications for the Economy and Society by Stanford University course would provide a different perspective for a technical person. Instead of learning how to develop them, the course would touch more about the impact and risks.
It’s a short course you can finish in a day, but it would be important for an AI expert.
Conclusion
This collection from Stanford University will help you learn about AI and prepare you to become that expert.
If you are more interested in data science, read the 5 Free Stanford University Courses to Learn Data Science.
Cornellius Yudha Wijaya is a data science assistant manager and data writer. While working full-time at Allianz Indonesia, he loves to share Python and data tips via social media and writing media. Cornellius writes on a variety of AI and machine learning topics.
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