Syllabus
Competition Syllabus
Comprehensive topics and areas covered in BdAIO and international rounds.
Network and Deep Learning
+Programming Fundamentals
Variables, data types, control flow, functions, loops, basic data structures (lists, dictionaries), file I/O, and Python programming essentials required for AI problem solving.
+Supervised Learning
Regression, classification, linear models, decision trees, ensemble methods, model training, validation, and evaluation metrics.
+Unsupervised Learning
Clustering (K-means, hierarchical), dimensionality reduction (PCA), anomaly detection, and unsupervised feature learning.
+Data Science Fundamentals
Data collection, cleaning, preprocessing, exploratory data analysis, feature engineering, and working with tabular and structured data.
+Natural Language Processing (NLP)
Text preprocessing, tokenization, embeddings, sequence models, sentiment analysis, and language model basics.
+Neural Networks
Perceptrons, activation functions, backpropagation, loss functions, optimization, and building basic neural network architectures.
+Deep Learning
Convolutional neural networks, recurrent neural networks, transfer learning, regularization, and modern deep learning frameworks.
+Computer Vision
Image processing, convolution operations, object detection basics, image classification, and visual feature extraction.
+Evaluation of ML Models
Cross-validation, precision/recall, F1 score, ROC-AUC, confusion matrices, overfitting/underfitting, and model selection.
+IOAI International Round Syllabus
Topics aligned with the International Olympiad in Artificial Intelligence (IOAI) including theoretical AI knowledge and practical Python-based problem solving.
Competition
+Basic AI Knowledge
Fundamental concepts of artificial intelligence, machine learning theory, probability, statistics, and algorithmic thinking.
+Python Programming
Python syntax, NumPy, Pandas, Matplotlib, Scikit-learn, and writing efficient code for ML competitions on Kaggle.
+Books
Recommended reading includes introductory ML texts, online resources (d2l.ai, mlcourse.ai), and competition-specific documentation.
Preparing for the International Olympiad?
The national contest syllabus is aligned with the International Olympiad on Artificial Intelligence (IOAI) and International AI Olympiad (IAIO) benchmarks. Make sure to review previous years' Kaggle competition datasets.