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Create your own Sudoku Solver using AI and Python
Ahmed Elhelow
Ahmed Elhelow
In this 1-hour long project-based course, you will create a Sudoku game solver using Python. This problem is an example of what is called a Constraint Satisfaction Problem (CSP) in the field of Artificial Intelligence. CSP is a mathematical problem that must...
Read more
In this 1-hour long project-based course, you will create a Sudoku game solver using Python. This problem is an example of what is called a Constraint Satisfaction Problem (CSP) in the field of Artificial Intelligence. CSP is a mathematical problem that must...
Read more
In this 1-hour long project-based course, you will create a Sudoku game solver using Python. This problem is an example of what is called a Constraint Satisfaction Problem (CSP) in the field of Artificial Intelligence. CSP is a mathematical problem that must satisfy a number of constraints or limitations all the time.
In this project, You will use the Backtracking algorithm to solve CSPs, in a Sudoku game. Backtracking is a recursive algorithm that tries to build a solution incrementally, removing solutions that fail to satisfy the constraints. Eventually, you will be able to use the knowledge acquired from this project on far more complex projects that employ these technologies.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/iad0cd/create
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches Backtracking and CSPs, which are used in various AI applications, particularly in problem solving
Provides a hands-on approach through a project-based structure, allowing learners to apply the concepts practically
Requires no prior knowledge of AI or Sudoku, making it accessible to beginners
Taught by an experienced instructor, Ahmed Elhelow, who is recognized for his expertise in AI and problem solving
May not delve deeply into advanced AI concepts or more complex Sudoku puzzles
Limited to Python programming language, which may not be suitable for learners with experience in other programming environments
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Reviews summary
Intro to sudoku solver with python and ai
Overall, this 1-hour course teaches learners how to create a Sudoku game solver using Backtracking and Python. The course is best suited for intermediate Python learners. Although the content is not complex, the course is functional and provides clear explanations.
Easy to follow and practical course
"This has been the best Python guided project I have taken so far"
"It is a really good coursera project. You just need a basic understanding of python syntax, lists, dictionaries and functions."
"Nice example of using recursion implemented in Python to solve Soduko"
Instructor's speech mannerisms
"You have to 'listen through' the instructor's speech mannerisms"
Lacks AI and complexity
"It very basic course. Nothing challenging in this course"
"There is no AI here in this project, it's simply recursion. Misleading."
Activities
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We're preparing activities for
Create your own Sudoku Solver using AI and Python.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Create your own Sudoku Solver using AI and Python will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, build, test, and deploy artificial intelligence (AI) systems. As an AI Engineer, you may work to create Sudoku game-solving AI, utilizing the knowledge of constraint satisfaction problems and backtracking algorithms acquired from this course. This course provides a foundation for developing and improving AI systems that can solve complex problems like Sudoku.
Software Engineer
Software Engineer
Software Engineers apply engineering principles to design, develop, test, and deploy computer software. Building a Sudoku game solver involves applying software development skills, and this course provides practical experience in solving constraint satisfaction problems using backtracking algorithms. These skills are essential for Software Engineers working on AI projects.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop, test, and deploy machine learning models. Understanding constraint satisfaction problems and backtracking algorithms is crucial for designing AI systems that can solve complex problems. This course provides a foundation for Machine Learning Engineers interested in building AI solvers for Sudoku and similar problems.
Computer Scientist
Computer Scientist
Computer Scientists conduct research in various areas of computing. This course provides insights into constraint satisfaction problems and backtracking algorithms, fundamental concepts in Computer Science. It can help Computer Scientists advance their research in the field of artificial intelligence.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. This course provides a practical understanding of constraint satisfaction problems and backtracking algorithms, which are valuable for Data Scientists working on AI projects. It can help Data Scientists develop better AI solutions for various business scenarios.
AI Researcher
AI Researcher
AI Researchers explore new techniques and algorithms in artificial intelligence. This course provides a hands-on experience in solving constraint satisfaction problems using backtracking algorithms, which are essential for AI research. It can help AI Researchers develop innovative AI solutions for complex problems.
Game Developer
Game Developer
Game Developers design and develop video games. This course provides practical insights into solving constraint satisfaction problems and using backtracking algorithms, which are valuable for Game Developers working on AI-powered games. It can help Game Developers build more challenging and engaging AI opponents.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, and test robots. Understanding constraint satisfaction problems and backtracking algorithms is crucial for developing AI systems that can navigate complex environments. This course provides a foundation for Robotics Engineers interested in building AI-powered robots.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course provides a practical understanding of constraint satisfaction problems and backtracking algorithms, which are useful for Data Analysts working on AI-driven data analysis projects. It can help Data Analysts develop better AI solutions for data-driven decision-making.
Business Analyst
Business Analyst
Business Analysts identify and analyze business needs and develop solutions to improve processes. This course provides insights into constraint satisfaction problems and backtracking algorithms, which are helpful for Business Analysts working on AI-powered business process optimization projects. It can help Business Analysts develop more efficient and effective AI solutions for business problems.
Software Tester
Software Tester
Software Testers ensure that software meets quality standards. This course provides a foundation for understanding constraint satisfaction problems and backtracking algorithms, which are valuable for Software Testers working on AI-powered software testing. It can help Software Testers develop better testing strategies for AI-driven software systems.
Technical Writer
Technical Writer
Technical Writers create documentation for software, hardware, and other technical products. This course may be useful for Technical Writers who need to explain constraint satisfaction problems and backtracking algorithms in their documentation. It can help Technical Writers produce more accurate and informative documentation for AI-related technologies.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course may be useful for Project Managers working on AI-related projects. It can help Project Managers better understand the technical aspects of AI, including constraint satisfaction problems and backtracking algorithms, and effectively manage AI projects.
Sales Manager
Sales Manager
Sales Managers lead and motivate sales teams to achieve sales goals. This course may be useful for Sales Managers selling AI products or services. It can help Sales Managers understand the technical benefits of AI, including constraint satisfaction problems and backtracking algorithms, and effectively communicate these benefits to potential customers.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns to promote products or services. This course may be useful for Marketing Managers promoting AI products or services. It can help Marketing Managers understand the technical capabilities of AI, including constraint satisfaction problems and backtracking algorithms, and effectively communicate these capabilities in marketing campaigns.
For more career information including salaries, visit:
OpenCourser.com/course/iad0cd/create
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Create your own Sudoku Solver using AI and Python.
Provides a comprehensive overview of constraint satisfaction problems (CSPs), including the backtracking algorithm used in this course. It covers advanced topics such as constraint propagation and search heuristics, making it a valuable reference for those interested in delving deeper into CSPs.
Provides a comprehensive overview of artificial intelligence, including a chapter on constraint satisfaction problems. It covers advanced topics such as probabilistic reasoning and natural language processing, making it a valuable resource for those interested in exploring AI beyond this course.
Provides a foundation in logical reasoning, which is essential for understanding the backtracking algorithm. It covers topics such as propositional logic, predicate logic, and inference, providing a solid theoretical basis for the course.
Provides a comprehensive introduction to artificial intelligence, including a chapter on constraint satisfaction problems. It covers basic concepts and techniques, making it a good starting point for those new to the field.
Save
Contains a large collection of challenging Sudoku puzzles, providing ample practice opportunities for applying the backtracking algorithm learned in this course.
Contains a collection of Sudoku puzzles of varying difficulty levels. It provides a fun and engaging way to practice solving Sudoku puzzles and reinforce the concepts learned in this course.
Contains a large collection of Sudoku puzzles of varying difficulty levels. It provides a fun and engaging way to practice solving Sudoku puzzles and improve one's problem-solving skills.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/iad0cd/create
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Ahmed Elhelow
Good to know
Teaches Backtracking and CSPs, which are used in various AI applications, particularly in problem solving
Provides a hands-on approach through a project-based structure, allowing learners to apply the concepts practically
Requires no prior knowledge of AI or Sudoku, making it accessible to beginners
Taught by an experienced instructor, Ahmed Elhelow, who is recognized for his expertise in AI and problem solving
May not delve deeply into advanced AI concepts or more complex Sudoku puzzles
Limited to Python programming language, which may not be suitable for learners with experience in other programming environments
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