AI in Gambling Course

Master Online Blackjack Card-Counting with Predictive AI in 1 Week & Improve Your Odds of Winning.

PREORDER

Join students from top institutions

Before AI people used to card-counting in their heads.

Ever watched the movie 21? Mastering card counting like that usually takes tons of practice or a near-photographic memory to track cards and thus boost your odds of winning.

Before AI people used to card-counting in their heads.

Ever watched the movie 21? Mastering card counting like that usually takes tons of practice or a near-photographic memory to track cards and thus boost your odds of winning.

But what would happen if we trained an AI to card-count for us?

Well... legalities aside, if you were to play online blackjack and not strictly monitored by dozens of cameras, then having an AI assistant monitoring could actually improve your winnings.

But what would happen if we trained an AI to card-count for us?

Well... legalities aside, if you were to play online blackjack and not strictly monitored by dozens of cameras, then having an AI assistant monitoring could actually improve your winnings.

Use the power of predictive AI to win.

With the advancement of AI, we have a lot of tools at our disposal...

♠️ Object detection algorithms like YOLOv8-10 can identify cards in real-time, even estimating the number of decks used in a game, for accurate input data.
♣️ Reinforcement learning models leverage past gameplay data to make optimal betting and playing decisions, mastering online blackjack strategies over time.
❤️ Vast databases store extensive gameplay records, acting as a memory for AI models, enabling them to learn from past experiences and adapt their strategies.
♦️ Predictive AI models analyze game situations, including the dealer's up-card and player's hand, to estimate winning probabilities and guide strategic decision-making.

Use the power of predictive AI to win.

With the advancement of AI, we have a lot of tools at our disposal...

♠️ Object detection algorithms like YOLOv8-10 can identify cards in real-time, even estimating the number of decks used in a game, for accurate input data.
♣️ Reinforcement learning models leverage past gameplay data to make optimal betting and playing decisions, mastering online blackjack strategies over time.
❤️ Vast databases store extensive gameplay records, acting as a memory for AI models, enabling them to learn from past experiences and adapt their strategies.
♦️ Predictive AI models analyze game situations, including the dealer's up-card and player's hand, to estimate winning probabilities and guide strategic decision-making.

The Solution

Enter the

AI for Gambling

Course

Code your own Online Blackjack Computer Vision + Predictive AI that can perform card-counting &

suggest actions to improve your odds of winning.

Explore the cutting-edge integration of AI in Gambling.

Module 1: Introduction to AI and Gambling

1. Evolution of AI in gambling

2. Ethical considerations and

3. Responsible gambling principles - never bet more than you can afford to lose.

4. Live versus online, why online is easier.

5. How we will build our winning model - Course overview

Module 2: Training the Computer Vision Model

1. The training process (Theory)

2. Gathering the data - Capturing video from source sites

3. Annotating the data with Roboflow, check out auto annotate tools

4. Data cleaning, transformation, and normalisation

5. Augmenting the dataset

6. Training the YOLOv8 or v9 model (ASOne v2 Library)

7. Model performance evaluation and testing - Get mAP, accuracy, precision, recall, F1-score, ROC curve

8. Fine-tuning the Model

9. Apply Object Tracking

10. Isolating Region of interests (ROI) for your cards, versus other peoples cards.

11. Displaying detected cards + sum of the cards on screen

Module 3: Card Counting Module

1. How BlackJack works(Theory)

2. How Card counting works(Theory)

3. What algorithms/open source repos can be used

4. Building the card counting algorithm

5. What happens when there is a reshuffle

6. Calculating the odds

Module 4: Predictive Modeling in Gambling [ Black-Jack Prediction]

1. Programming the game metrics and game strategy

2. Combine the Computer Vision with card counting module

3. Displaying card counts and probabilities onscreen

4. Get the outputs of whether to hit, stand, raise, split

5. Risk assessment

6. Game Strategy - Winning algorithm - When to intentionally lose to not raise suspicion or get banned

7. Optimize winnings

10+ hours of content

Code + Datasets

Beginner Friendly

Lifetime Access

PREORDER

MODULE 1

Introduction to AI & Gambling

1. Evolution of AI in gambling
2. Ethical considerations and
3. Responsible gambling principles - never bet more than you can afford to lose.
4. Live versus online, why online is easier.
5. How we will build our winning model - Course overview

MODULE 2

Training the Computer Vision Model

1. The training process (Theory)

2. Gathering the data - Capturing video from source sites

3. Annotating the data with Roboflow, check out auto annotate tools

4. Data cleaning, transformation, and normalisation

5. Augmenting the dataset

6. Training the YOLOv8 or v9 model (ASOne v2 Library)

7. Model performance evaluation and testing - Get mAP, accuracy, precision, recall, F1-score, ROC curve

8. Fine-tuning the Model

9. Apply Object Tracking

10. Isolating Region of interests (ROI) for your cards, versus other peoples cards.

11. Displaying detected cards + sum of the cards on screen

MODULE 3

Card Counting Module

1. How BlackJack works(Theory)

2. How Card counting works(Theory)

3. What algorithms/open source repos can be used

4. Building the card counting algorithm

5. What happens when there is a reshuffle

6. Calculating the odds

MODULE 4

Predictive Modeling in Gambling (Black-Jack Card Prediction)

1. Programming the game metrics and game strategy

2. Combine the Computer Vision with card counting module

3. Displaying card counts and probabilities onscreen

4. Get the outputs of whether to hit, stand, raise, split

5. Risk assessment

6. Game Strategy - Winning algorithm - When to intentionally lose to not raise suspicion or get banned

7. Optimize winnings

PREORDER

What do industry leaders say about our program?

Constantin Shafranski

Data Scientist at Cognyte

As someone who has not yet dealt with image segmentation, I found this course to be quite helpful. It emphasizes the background theory appropriately, which I believe is quite crucial to get some idea of the topic and not "dive" straight into the coding part without actually understanding how things should operate. In addition, the course is designed in such a way that even someone who is not an expert AI coder may follow along without wondering "what the F* is going on here?". The instructions are clear, and the information is well-organized. A lot of the information regarding the entire process of building and preprocessing a custom dataset is also applicable to a variety of different tasks in the image domain, thus the course is also a very valuable source of reference.

GitHub

Christopher Berry

Data Scientist at Alfred Health

You won't find courses with higher quality, I’ve done countless online courses from many different platforms and individuals but the courses produced by Ritesh and Augmented Startups are the best Computer Vision courses you’ll find. Their project ideas are extremely innovative, and they’re always implementing the latest state-of-the-art algorithms, so it’s no surprise that their models achieve elite results. My favorite project was the Heart Rate Detection and which achieved amazing FPS which is a testament to the quality of their code. I just enrolled in their YOLO+ course and I look forward to enrolling in future courses their team creates too.

Thank you, Ritesh, and Augmented Startups, all the best 😊

Chris

Emmanuel Oluga

Medical Design Innovations Lab at UTSA

Ritesh is truly one of the most Intelligent and resourceful Individuals I have ever met and collaborated on activities with. He is always enthusiastic about taking on challenges and providing actionable and effective solutions, whether it be in the field of Computer Vision, graphics, and Machine learning for practical applications or it is in any other field where an innovative approach to problem-solving is Indispensable. Most impressive and inspirational are his Communication, Interpersonal, and leadership skills that accentuate his technical expertise in the fields of Al and ML for Machine vision applications. These qualitative and quantitative skills and traits he possesses, position him well to thrive in any endeavor and environment.

What's Included?

One-on-one personal coaching

Exclusive to the Elite Plan: Get two, 15 minute private coaching sessions with Ritesh Kanjee, a thought leader in computer vision.

Access to private inner circle

Get access to a private online and WhatsApp community, where you can network with students and professionals, ask questions, and get feedback on your projects.

Monthly Hands-On AI challenges

Gain new skills in our Inner Circle, with additional monthly projects and challenges that provide hands-on experience.

VIP Tech Support - Fast Assistance

Get fast and reliable technical assistance with VIP Tech Support. Our expert technicians are available 24/7 to solve any issues, ensuring that your code runs smoothly and hassle-free.

Bonus 1

YOLO NAS + V8

Full-Stack Object Detection Course

Master computer vision with YOLO in 4 weeks with our YOLO-NAS course - a one-time learning experience that stays relevant forever!

Certification

Once you complete the course, you will graduate with an Official Certificate, which is embedded with a unique ID that you can share on LinkedIn.

Your Instructor

Ritesh Kanjee

117k+ Subscribers YouTube

71k Students Augmented Startups

M(Eng.) Electronic University of Joburg

54k+ Followers LinkedIn

Course Development Timeline

Development for our course began on June 1st 2024. The course will officially commence on August 2nd 2024. We anticipate full course completion by September 15th 2024.

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AI in Gambling Nano Course

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Module 1: Introduction to AI and Gambling
Module 2: Training the Computer Vision Model

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Module 1: Introduction to AI and Gambling
Module 2: Training the Computer Vision Model
Module 3: Card Counting Module
Module 4: Predictive Modeling in Gambling [Black-Jack Prediction]
- Programming the game metrics and game strategy
- Combine the Computer Vision with card counting module
- Displaying card counts and probabilities onscreen
- Get the outputs of whether to hit, stand, raise, split
- Risk assessment
- Game Strategy - Winning algorithm - When to intentionally lose to not raise suspicion or get banned
- Optimize winnings