The Future Of Software engineering and AI: What YOU can do about it
Webinar starts in
Lessons
Explore all newline lessons
lesson
Vector Databases and Query OptimizationAI BootcampExplore vector databases, chunking, and query optimization (HyDE, reranking, filtering) using contrastive learning and cosine similarity.
lesson
RAG Pipeline OverviewAI BootcampUnderstand the RAG pipeline (pre-retrieval, retrieval, post-retrieval) and compare term-based vs embedding-based retrieval (TF-IDF, BM25 vs vector search).
lesson
Advanced Multimodal TasksAI BootcampExperiment with visual question answering (VQA), image captioning, and compare multimodal architectures (CLIP, ViLT, ViT-GPT2).
lesson
Prompt Engineering with ImagesAI BootcampPractice prompt engineering with images, explore wording’s impact on retrieval, and build text-to-image/image-to-image retrieval systems using cosine similarity.
lesson
Introduction to CLIP and Multimodal EmbeddingsAI BootcampUnderstand CLIP’s joint image-text representations via contrastive learning and run similarity queries in shared embedding space.
lesson
Multimodal Embeddings for RetrievalAI BootcampConduct retrieval and classification tasks with image/audio embeddings (CLIP, Wav2Vec2) and explore emerging architectures like Byte Latent Transformers.
lesson
Working with EmbeddingsAI BootcampLearn how embedding vectors represent meaning, manipulate Word2Vec-style embeddings (vector math, dot product similarity), and apply to multimodal models (CLIP, ViLT, ViT-GPT2).
lesson
Text to Tokens to EmbeddingsAI BootcampUnderstand the journey from raw text to tokens to embeddings, compare tokenizers (word-based, BPE, LLaMA, GPT-2, T5), and analyze tokenization’s impact on loss and inference.
lesson
Advanced Prompting with Context EngineeringAI BootcampExplore multi-turn prompts, rubric-based human alignment, A/B testing, and experiment with `dspy` for structured prompting.
lesson
Building and Evaluating PromptsAI BootcampBuild evaluators to measure LLM output quality, write “LLM-as-a-judge” prompts, and iterate based on analysis-feedback loops.
lesson
Foundational Prompt EngineeringAI BootcampLearn prompt styles (vague vs specific, structured, XML-tagging), practice prompt design with Pydantic for JSON outputs, and identify LLM failure modes (hallucinations, format issues).