The Third Iran Annual AI Award (iAAA)
Comprehensive AI Course & Competition, with a one-billion-Toman prize for each challenge
240+ hours of training
12 weeks
Online / Offline
Summer & Autumn 2025
$50,000 in prizes
31 provinces
The Iran Annual AI Award (iAAA) is a national platform for nurturing and promoting AI skills and innovation. Since 2022, two editions have been held, advancing the growth of Iran's AI ecosystem. iAAA centers on problem-solving competitions and prepares participants to tackle real challenges faced by industries and organizations.
Comprehensive AI Course
With more than 240 hours of educational content, the iAAA AI course is considered the most comprehensive AI course in the country.
Specialized mentoring and Q&A
Throughout the course, participants stay in touch with experienced mentors and resolve their learning challenges by attending online Q&A sessions.
Recognized Certificate
Upon completing the course, participants receive a recognized certificate reflecting their knowledge and skills in artificial intelligence.
Job & Internship Opportunities
In addition to cash prizes, iAAA winners are introduced to the country’s top companies and gain internship and collaboration opportunities with leading industries.
$50,000 in prizes
The top ranks in each challenge receive a combined one billion Tomans in cash prizes.
International-level Competition
In the third iAAA edition, compete with international teams and put your abilities to the test.
Solving Real Industry Problems
Participants work on real challenges from industries and organizations and gain access to real-world data.
Teamwork & Networking
After completing the training, participants enter the competition stage and design solutions to the challenges in teams.
Mr. Reza Bagheri Asl
Mr. Hamid Banaeian
Mr. Arasb Ahmadian
Mohammad Akbari
Speaker
AI researcher
Visiting professor, University of London
Researcher, New York University
Visiting professor, Iran University of Science and Technology
PhD, Amirkabir University of Technology
Rashad Hosseini
Deep Learning
Faculty member, School of Electrical and Computer Engineering, University of Tehran
Former head of the AI Headquarters, Vice-Presidency for Science and Technology
PhD in AI, Technical University of Berlin
Chairman of the Board, Hoosh Afzar Rahbar Ariaman
Ali Zarezadeh
Speaker
Machine Learning Team Lead, Yektanet
Team Lead, Mofid Brokerage
Postdoc, a German university
AI researcher and practitioner
Machine Learning instructor
Sepehr Akbarzadeh
Deep Learning / Computer Vision
Senior AI Engineer, Irancell
Software Engineer, Iranian Hospital Qatar
Elite AI student
Instructor, Sharif University of Technology
Zeinab Barzegar
Speaker
Head of the Scientific Committee of the third iAAA
Faculty member, Tehran University of Medical Sciences
PhD in AI, Sharif University of Technology
AI advisor, Hamrah Fund (MCI)
Amin Babadi
Speaker
AI and game-animation programmer
AI specialist at Bugbear, Finland
Mohammadreza Beikzadeh
Speaker
AI instructor in the UK
Senior advisor at AIENAI, London
Dr. Asheri
Foundations of Machine Learning Mathematics
CEO of Hoosh Afzar Rahbar Ariaman
Member of the AI Commission of the ICT Guild
AI instructor and practitioner
Masoud Mazloum
Speaker
CEO of the Data Science Innovation Center
PhD and Postdoc, University of Amsterdam, Netherlands
Visiting professor, University of Amsterdam
Data science instructor and researcher
Aliakbar Kiaei
Machine Learning
Faculty member, Malek-Ashtar University of Technology
Postdoc in AI
AI instructor and practitioner
Soheil Tehranipour
Computer Vision
CEO of Saeeyan Ertebat
Head of the AI team at Fakher Holding
Former instructor, Sharif University of Technology
AI researcher
Masoud Kaviani
Data Science
Machine Learning Engineer, Zebracat, Berlin
Senior Data Scientist, Saba Idea (Aparat, Filimo, SabaVision)
Visiting professor, Computer Department, Shahid Rajaee University
Visiting instructor, ACECR, Sharif University of Technology
Faculty member, Data Governance Group, Data Science Innovation Center
Recipient of an entrepreneurship medal from Google
Top rank at Iran Startup Weekend
Elnaz Amanzadeh
Speaker
Head of the AI department, Brain Research Center
AI researcher in medical sciences, Shahid Beheshti University
AI instructor and practitioner, University of Medical Sciences
Fatemeh Razavi
Python Basics
PhD in AI, University of Tehran
AI instructor and practitioner
Mohammad Fotouhi
Python
LLM Engineer, Sharif Research Institute
AI researcher and instructor
Mobin Nesari
Mentor
MSc in Computer Science and AI
Scientific advisor and instructor of the second iAAA
Instructor, Shahid Beheshti University
Siamak Farshidi
Speaker
Visiting professor, University of Amsterdam, Netherlands
Visiting professor, Utrecht University, Netherlands
Mohammadmehdi Begmaz
Mentor
MSc in Computer Science and AI.
AI instructor, Shahid Beheshti University
Foundations
Topic
- Introduction to AI and Competitions
Description
- Install Python, Jupyter Notebook, Overview of AI tools and platforms
Python for AI
Topic
- Introduction to Programming
- Basic Syntaxes
- Conditional Blocks
- Loops
- Data Structures & Strings
- Functions
- Files
- Object-Oriented Programming
- Lambda Functions
- Use of Frameworks and Packages
- Practical Project
Description
- Basics of Python, IDEs, and basic programming exercises
- Variables, operators, and basic Python syntax
- if-elif-else conditions and logical operators
- For and While loops, control statements
- Lists, tuples, dictionaries, and string operations
- Defining functions, arguments, and recursion
- File handling, reading, writing, and appending
- Classes, objects, inheritance, and encapsulation
- Anonymous functions, map, filter, and reduce
- Installing and using NumPy, Pandas, and Matplotlib
- Build an attendance tracker application
Mathematics for Machine Learning
Topic
- Linear Algebra
- Probability and Statistics
- Calculus
- Optimization Techniques
Description
- Vectors, matrices, PCA, and practical exercises with NumPy
- Distributions, Bayes’ theorem, and practical exercises with NumPy
- Derivatives, gradients, and gradient descent
- Convex optimization and advanced techniques
Data Science for AI
Topic
- Data Preprocessing
- Exploratory Data Analysis (EDA)
- Feature Engineering
- Data Visualization
Description
- Handle missing data, scaling, normalization, encoding categorical variables
- Visualize data distributions and compute descriptive statistics
- Feature selection, creation, and scaling
- Advanced visualizations using Matplotlib, Seaborn, and Plotly
Digital Image Processing
Topic
- Introduction to Images
- Basic Image Operations
- Histograms in Image Processing
- Convolution and Fourier Transform
- Noise Reduction
- Edge Detection
- Binary Image Processing
- Segmentation
- Image Registration
Description
- Basic concepts, formats, and Python setup
- Cropping, resizing, color spaces, and practical exercises
- Understanding and plotting histograms
- Filters and frequency domain transformations
- Noise types and denoising techniques
- Sobel and Canny edge detection
- Thresholding, morphology, and contours
- Watershed algorithm for image segmentation
- Align images using keypoints and transformations
Machine Learning
Topic
- Introduction to Machine Learning
- Supervised Learning (Regression)
- Supervised Learning (Classification)
- Unsupervised Learning (Clustering)
- Unsupervised Learning (Dimensionality Reduction)
- Model Evaluation and Tuning
- Ensemble Learning
- Real-World Applications and Project
Description
- Overview of ML types and pipelines
- Linear and polynomial regression with Scikit-learn
- Logistic regression, KNN, decision trees
- K-Means and hierarchical clustering
- PCA and feature selection
- Cross-validation and hyperparameter optimization
- Random Forest, Gradient Boosting, and XGBoost
- End-to-end ML pipeline for a dataset
Deep Learning
Topic
- Introduction to Deep Learning
- Fundamentals of Neural Networks
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs) and LSTMs
- Transformers and Attention Mechanisms
- Generative Models (GANs and VAEs)
- Model Evaluation and Tuning
- Real-World Project
Description
- Concepts, applications, and PyTorch setup
- Building and training basic neural networks
- Implement CNNs and fine-tune pretrained models
- Sequence modeling and time series forecasting
- Transformers and fine-tuning BERT
- Implementing GANs and VAEs
- Evaluation metrics and regularization
- Build an end-to-end Deep Learning project in PyTorch
End
In the Competition section of the iAAA, your theoretical knowledge is put to a practical test — a unique opportunity to showcase your abilities and skills in the applied world of AI.
In the third iAAA edition, participants from across the country compete to provide AI-based solutions to real challenges drawn from the problems of various national industries. The challenges are designed in important and diverse fields such as healthcare and banking to test participants' technical, analytical, and innovative capabilities.
Taking part in this competition is not only about gaining experience; the final winners have the chance to receive cash prizes worth a total of $50,000.
Stay tuned for the official announcement of the challenges — form your team, practice, and shine.
If you're looking for a real leap in learning and a professional entry into the world of AI, the iAAA course and competition is a unique opportunity for you. Smooth your path by learning from expert mentors, taking part in real challenges, and earning a recognized certificate.
Join hundreds of future-shaping enthusiasts and experts, and get ready to compete in one of the country's biggest AI events.
Register now and take a serious step toward building your future.
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Frequently Asked Questions
What is iAAA?
The Iran Annual AI Competition (iAAA) is a national event to promote skills and innovation in artificial intelligence. Participants benefit from comprehensive training while taking part in real-world challenges based on the problems of various industries, and compete with one another to win the competition's prizes.
Who can take part in the competition?
Anyone interested in artificial intelligence, at any level of knowledge or experience, is welcome to take part in the competition.
Is the iAAA course enough to prepare for the competition?
Yes. Even those with no prior background in AI can, by completing the comprehensive zero-to-hero iAAA course, reach a level of skill that enables them to solve the competition's challenges.
Does the course and competition require in-person attendance?
No. All training and competition processes are held entirely online, with no need for physical attendance.
Is group registration possible?
Yes. Group registration is possible, and special benefits are offered for registered teams.
Are there any prerequisites for the course?
No. The course is designed to require no prior knowledge, and anyone interested can take part.
What topics does the course cover?
The training covers specialized AI topics, soft skills, team building, problem solving, and readiness to enter the job market.
What is the course schedule?
The course begins in early July and continues through late September.
On which days are the classes held?
Classes are held on even days from 6 to 9 p.m., and include two teaching sessions and one practice session per week.
Is a certificate issued after the course?
If a participant has viewed at least 60% of the course content and completed the related exercises, an electronic certificate will be issued for them.
Is a physical copy of the certificate available?
No. Currently the certificate is issued electronically only.
What are the competition prizes?
The competition includes five challenges, with a $10,000 prize for each challenge, divided among the top three teams as follows:
First team: $7,000
Second team: $2,000
Third team: $1,000
Can the course fee be paid in installments?
Yes. The course tuition can be paid in installments.
Is the competition also held online?
Yes. All stages of the competition are held online.
How many members can a team have?
Teams can consist of 1 to 6 members.
Can members be added to or removed from a team?
Yes. Participants can add or remove team members during the registration process.
How can I use the course support services?
You can reach the support team through the Contact Us section of the website or via the support email.
What is the role of sponsor companies in this event?
By providing financial and scientific resources, sponsor companies play an important role in raising the quality and scientific level of iAAA.
How can I take part as a sponsor of this competition?
Those interested in sponsoring this event can contact the secretariat of the Iran Annual AI Award through the Contact Us section.
The iAAA course was exactly what I had been looking for! A hands-on program whose real projects make it applicable in the real world, with no unnecessary complexity. This course truly brought me closer to the real world of AI.