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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...
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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.
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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

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Create your own Sudoku Solver using AI and Python with these activities:
Read 'Artificial Intelligence: A Modern Approach'
Gain a comprehensive understanding of AI principles and their applications, including constraint satisfaction problems.
View Melania on Amazon
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Review Basic Python
Refreshing your knowledge of Python basics will help you navigate the course material more easily.
Browse courses on Python Basics
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  • Review the Python documentation on data types, variables, and operators
  • Complete a few coding exercises to practice writing basic Python code
  • Read through a Python tutorial to refresh your understanding of the language's syntax and structure
Revise logical operators and boolean algebra
Familiarize yourself with logical operators and boolean algebra to reinforce your understanding of Constraint Satisfaction Problems (CSPs).
Browse courses on Logic
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  • Review notes or textbooks on propositional logic
  • Solve practice problems involving logical operators (e.g., AND, OR, NOT, XOR)
  • Study truth tables for boolean operators
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Follow online tutorials on constraint satisfaction problems (CSPs)
Expand your knowledge of CSPs and Backtracking through interactive tutorials.
Show steps
  • Search for online tutorials on CSPs and Backtracking
  • Follow the instructions in the tutorials
  • Attempt the exercises provided in the tutorials
Join a study group for the course
Collaborate with peers to discuss concepts, solve problems, and enhance your understanding of CSPs.
Show steps
  • Find or create a study group for the course
  • Attend study group meetings regularly
  • Actively participate in discussions and problem-solving
Create a Simple Sudoku Solver
Building a Sudoku solver from scratch will give you a practical understanding of the concepts taught in the course.
Browse courses on Sudoku
Show steps
  • Design the data structures and algorithms for the solver
  • Implement the solver in Python
  • Test the solver on a variety of Sudoku puzzles
Solve Sudoku puzzles with varying difficulty levels
Practice solving Sudoku puzzles to improve your understanding of CSPs and the Backtracking algorithm.
Show steps
  • Start with easy Sudoku puzzles
  • Gradually increase the difficulty level of puzzles
  • Analyze your solutions to identify areas for improvement
Solve Sudoku Puzzles
Solving Sudoku puzzles will help you develop your problem-solving skills and improve your understanding of the game's mechanics.
Browse courses on Sudoku
Show steps
  • Find Sudoku puzzles online or in puzzle books
  • Solve the puzzles using the techniques taught in the course
  • Analyze the puzzles to identify common patterns and strategies
Attend a workshop on Artificial Intelligence and CSPs
Deepen your understanding of AI and CSPs through hands-on workshops conducted by experts.
Show steps
  • Search for upcoming workshops on AI and CSPs
  • Register for a workshop that aligns with your interests
  • Attend the workshop and actively participate in discussions and exercises
Develop a Python script to solve Sudoku puzzles automatically
Apply your knowledge of Python and the Backtracking algorithm to build a tool that demonstrates your understanding of CSPs.
Browse courses on Python
Show steps
  • Implement the Backtracking algorithm in Python
  • Design the architecture of your Python script
  • Test your script with different Sudoku puzzles
Contribute to open-source projects related to CSPs or Backtracking
Apply your knowledge of CSPs and Backtracking by contributing to real-world projects that utilize these concepts.
Show steps
  • Research open-source projects related to CSPs or Backtracking
  • Identify ways to contribute to these projects
  • Submit your contributions for review

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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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.

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.
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.

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