The Future Of Software engineering and AI: What YOU can do about it
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Lessons
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CLIP Finetuning for InsuranceAI BootcampFine-tune CLIP for car damage classification, use Google Custom Search API for collecting datasets, and apply LoRA with Optuna for optimization.
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RAG Evaluation and OptimizationAI BootcampEvaluate RAG outputs (recall, MRR, qualitative), optimize retriever+generator coordination for enterprise use cases.
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Advanced RAG SystemsAI BootcampAnalyze production-grade RAG case studies (Relari, Evidently), understand bottlenecks (chunking, reranking), and compare embedding models.
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Monkeywrenching into LLaMAAI BootcampEdit layers in a pre-trained model, understand a state-of-the-art model and monkey patching cutom layers in State of the art model.
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Debugging & Testing TransformersAI BootcampUse sanity checks and test loss to debug, observe transformer behavior on structured prompts/simple sequences.
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Building a Full TransformerAI BootcampConnect embeddings, attention, feedforward, and normalization; implement skip connections and positional encodings manually.
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Mini-Project: Generating Synthetic Data & Finetuning for EvaluationAI BootcampMini Projects: Generating Different Synthetic Data & Fine-Tuning for Evaluation-Centric Applications w.r.t Building synthetic data for non-reasoning, Building synthetic data for reasoning, and Building synthetic data for diversity.
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Advanced Multimodal ApplicationsAI BootcampApply domain-specific LoRA tuning, explore regression/classification heads, and understand diffusion models for text-to-image/video generation.
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Multimodal Finetuning with CLIPAI BootcampFine-tune CLIP for classification/regression (e.g., pizza types, solar prediction), add heads on embeddings, and compare zero-shot vs fine-tuned accuracy.
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FFN Components & TrainingAI BootcampExplore dropout, LayerNorm, positional encoding, skip connections, and build intuition for transformer depth and context encoding.
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Feedforward Networks in TransformersAI BootcampUnderstand linear/nonlinear layers, implement FFNs in PyTorch, and compare activation functions (ReLU, GELU, SwiGLU).
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Finetuning Case StudiesAI BootcampApply fine-tuning for HTML generation, resume scoring, financial tasks, and compare base vs instruction-tuned model performance.