It is Casino Royale: MI6 has sent their top agent, James Bond, to face Le Chiffre, a private banker to terrorist organizations. In a high-stakes poker game, as Bond places significant bets, we are left to wonder: can he outmaneuver this criminal mastermind? What is the likelihood that he will win? How should he play to ensure that he wins?
While dramatized for cinema, this scenario prompts complex questions about probability and game theory. Beyond the cinematic tension lie rich mathematical concepts that govern not only poker strategy but also form the foundation of modern computer science and artificial intelligence.
In this hands-on course, we will take a deep dive into exactly these questions. Mathematical Foundations of Computer Science focuses on four core areas that form the bedrock of modern computational thinking and artificial intelligence: Probability Theory, Game Theory, Algorithmic Thinking, and Artificial Intelligence.
The course culminates in an exciting capstone project: developing an AI poker player. This project will synthesize all the course concepts, showcasing how probability theory informs decision-making under uncertainty, game theory guides strategic choices, algorithmic thinking optimizes performance and AI techniques bring it all together into a cohesive system.
You can choose between two tailored learning tracks based on your backgrounds and interests. If you have a programming background and have applied interest, you will engage in a hands-on coding project throughout the course, implementing the mathematical concepts and ultimately developing the AI poker player.* If you are a non-programmer and have theoretical interest, you will engage in problem-solving techniques, exploring open problems and using the AI poker project as a case study for understanding advanced applications of course concepts.
*Students interested in programming track must be reasonably familiar with coding in Python.
Enroll Now Existing User? Log InThis course is for high schoolers who want to build a foundational understanding of mathematics and programming, and develop practical skills in programming and AI development.
By the end of the programme, you will:
Week | Lecture Module | Project Module |
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Week 1 | Probability Theory
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Poker Hand Probability Simulation
Create a program that simulates various poker hands, calculate the probabilities of each hand being dealt, and analyze outcomes based on different scenarios. |
Week 2 | Game Theory
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Nash Equilibrium Analysis Model a simplified poker game to identify and analyze Nash equilibria for optimal strategies, and create a strategy guide based on the findings, outlining how different strategies affect outcomes. |
Week 3 | Algorithmic Thinking
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Search Algorithms
Implement a graph of game states, and develop a backtracking based algorithm to search for winning strategies. |
Week 4 | Artificial Intelligence
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AI Poker Bot Development Integrate previous concepts to develop an AI poker bot based on the minimax algorithm, capable of evaluating game states and making strategic decisions. |
Week 5 | Counseling:
Get a chance to ask questions to the faculty and the mentor and get their answers and perspective. You are encouraged to ask questions to the faculty around the following aspects: ● What are some related fields that can be explored based on this course topic? ● What are the future trends in the related fields? ● How can the course learning help the student enhance their college applications? |
Mentoring:
You are encouraged to ask questions to the mentor around the following aspects:
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As your project, you will develop an AI poker player based on the minimax algorithm, capable of evaluating game states and making strategic decisions. This project will synthesize all the course concepts, showcasing how probability theory informs decision-making under uncertainty, game theory guides strategic choices, algorithmic thinking optimizes performance, and AI techniques bring it all together into a cohesive system.
Aalok Thakkar is currently an Assistant Professor of Computer Science at Ashoka University. His research focuses on integrating formal methods and artificial intelligence, with particular emphasis on applying formal methods in programming-by-examples for relational queries, synthesis of reactive programs, bounded model checking, verification of smart contracts, and text generation.
He completed his PhD in Computer and Information Science from the University of Pennsylvania in May 2023, with a thesis on “Example-guided Synthesis of Relational Queries” under advisors Rajeev Alur and Mayur Naik. Prior to his academic appointment, Aalok worked with Movement Labs and Aptos Labs on verification of smart contracts. His research has been published in top-tier conferences such as VLDB, SPLASH, and PLDI.
Ashoka Horizons Achievers Programme offers a certificate on satisfactory completion of the course.
Class participation will be assessed based on your active engagement in live sessions, contributions to discussion forums, and involvement in Teaching Fellow-led activities.
Achieve More…with Horizons Achievers Programme:
*For select students, subject to discretion of the faculty
This programme is administered through an online platform. Students are expected to have a foundational understanding of computer usage, including but not limited to sending emails and conducting Internet searches. Consistent access to the Internet and a computer that aligns with the recommended minimum specifications are also requisite for participation in the programme.
Have a question about Ashoka Horizons Achievers Programme? Write to us on horizons@ashoka.edu.in
Of course, having completed an Ashoka Horizons course will be of great value when filling out an application to college. It has given me relevant skills and knowledge in data science and shown me to be a learner and capable of handling alternative subjects. This will greatly enhance my application and place me in a league of my own for consideration.
Yes, the Horizons course will definitely help me with my college applications. Many universities abroad, particularly in the US, value students who demonstrate a strong interest in their chosen majors.