CS50’s Introduction to Artificial Intelligence with Python
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CS50’s Introduction to Artificial Intelligence with Python: Take the first step toward solving important real-world problems & future-proofing your career.
Introduction
In this course on CS50’s Introduction to Artificial Intelligence with Python, you will learn to use machine learning in Python.
About this course on CS50’s Introduction to Artificial Intelligence with Python:
AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.
CS50’s Introduction to Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation.
Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By the end of the course, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
Enroll now to gain expertise in one of the fastest-growing domains of computer science from the creators of one of the most popular computer science courses ever, CS50. You will learn the theoretical frameworks that enable these new technologies while gaining practical experience in how to apply these powerful techniques in your work.
What you will learn from:
CS50’s Introduction to Artificial Intelligence with Python.
- graph search algorithms
- adversarial search
- knowledge representation
- logical inference
- probability theory
- Bayesian networks
- Markov models
- constraint satisfaction
- machine learning
- reinforcement learning
- neural networks
- natural language processing
Prerequisites
- CS50 or prior programming experience in Python.
Syllabus for CS50’s Introduction to Artificial Intelligence with Python:
0. Search
Finding a solution to a problem, like a navigator app that finds the best route from your origin to the destination, or like playing a game and figuring out the next move.
1. Knowledge
Representing information and drawing inferences from it.
2. Uncertainty
Dealing with uncertain events using probability.
3. Optimization
Finding not only a correct way to solve a problem but a better—or the best—way to solve it.
4. Learning
Improving performance based on access to data and experience. For example, your email is able to distinguish spam from non-spam mail based on past experience.
5. Neural Networks
A program structure inspired by the human brain that is able to perform tasks effectively.
6. Language
Processing natural language, which is produced and understood by humans.
Note: Your review matters
If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.
FAQ
Description
Introduction
In this course on CS50’s Introduction to Artificial Intelligence with Python, you will learn to use machine learning in Python.
About this course on CS50’s Introduction to Artificial Intelligence with Python:
AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.
CS50’s Introduction to Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation.
Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By the end of the course, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
Enroll now to gain expertise in one of the fastest-growing domains of computer science from the creators of one of the most popular computer science courses ever, CS50. You will learn the theoretical frameworks that enable these new technologies while gaining practical experience in how to apply these powerful techniques in your work.
What you will learn from:
CS50’s Introduction to Artificial Intelligence with Python.
- graph search algorithms
- adversarial search
- knowledge representation
- logical inference
- probability theory
- Bayesian networks
- Markov models
- constraint satisfaction
- machine learning
- reinforcement learning
- neural networks
- natural language processing
Prerequisites
- CS50 or prior programming experience in Python.
Syllabus for CS50’s Introduction to Artificial Intelligence with Python:
0. Search
Finding a solution to a problem, like a navigator app that finds the best route from your origin to the destination, or like playing a game and figuring out the next move.
1. Knowledge
Representing information and drawing inferences from it.
2. Uncertainty
Dealing with uncertain events using probability.
3. Optimization
Finding not only a correct way to solve a problem but a better—or the best—way to solve it.
4. Learning
Improving performance based on access to data and experience. For example, your email is able to distinguish spam from non-spam mail based on past experience.
5. Neural Networks
A program structure inspired by the human brain that is able to perform tasks effectively.
6. Language
Processing natural language, which is produced and understood by humans.
Note: Your review matters
If you have already done this course, kindly drop your review in our reviews section. It would help others to get useful information and better insight into the course offered.
FAQ
Specification:
- EDX
- Harvard University
- Online Course
- Instructor-led
- Beginner
- 1-3 Months
- Free Course (Affordable Certificate)
- English
- Artificial intelligence Deep learning Harvard Computer Science 50 (CS50) Machine learning Natural language processing
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