Stage 00

Foundations & Environment

Set up your environment, understand transformers from scratch, and master data preparation fundamentals.

7notebooks
4hestimated
0030 min

Environment Setup

Configure your GPU environment, install PyTorch and HuggingFace libraries, verify CUDA, and set up HuggingFace authentication.

CUDAPyTorchHuggingFaceGPU Setup+1
StudyColab
0145 min

Transformer Basics

Build multi-head self-attention from scratch, implement positional encodings, and understand why Attention is All You Need.

Self-AttentionMulti-Head AttentionPositional EncodingTransformer Architecture
StudyColab
0240 min

Tokenization Deep Dive

Explore BPE, WordPiece, and SentencePiece tokenization. Compare GPT-2 and BERT tokenizers side-by-side.

BPEWordPieceSentencePieceVocabulary+1
StudyColab
0335 min

Dataset Preparation Basics

Load, split, and preprocess NLP datasets with HuggingFace Datasets. Train/val/test splitting strategies.

HuggingFace DatasetsTrain/Val/Test SplitTokenizationDataLoader
StudyColab
0435 min

Data Quality Analysis

Detect duplicates, class imbalance, outliers, and PII in datasets. Build reusable EDA pipelines.

EDADuplicate DetectionPIIClass Imbalance+1
StudyColab
0530 min

Handling Class Imbalance

Oversampling, undersampling, class weights, focal loss, and WeightedRandomSampler techniques.

Class WeightsFocal LossWeightedRandomSamplerSMOTE+1
StudyColab
0635 min

Data Augmentation for NLP

Synonym replacement, back-translation, random deletion/swap, and synthetic data generation.

Back-TranslationSynonym ReplacementEDA AugmentationSynthetic Data
StudyColab
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Full Model Fine-Tuning