NLP Bootcamp 2026: From Zero to Production NLP Engineer

About this course

Master Natural Language Processing in 2026 and become a production‑ready NLP engineer. This comprehensive NLP Bootcamp takes you from the fundamentals of text processing to the cutting edge of Large Language Models, Retrieval‑Augmented Generation (RAG), and multimodal AI.You will learn Python, NLTK, spaCy, Hugging Face Transformers, PyTorch, TensorFlow, Gensim, Scikit‑learn, FAISS, LangChain, LoRA, QLoRA, MLflow, Docker, and more. The course covers the complete NLP pipeline: tokenisation, text cleaning, stemming, lemmatisation, regular expressions, fuzzy matching, TF‑IDF, Word2Vec, GloVe, FastText, contextual embeddings (ELMo, BERT), document embeddings, Byte‑Pair Encoding, SentencePiece, vector databases, and semantic search. You will build classical machine learning models (Naive Bayes, Logistic Regression, SVMs, HMMs, CRFs, LDA, NMF) and modern deep learning architectures (RNNs, LSTMs, GRUs, Seq2Seq, Attention, Transformer, BERT, GPT, RoBERTa, DistilBERT).

With 20+ hands‑on projects, you will build spam detectors, sentiment analysers, custom NER models, news summarisers, question answering systems, chatbots, document classification systems, multilingual translation services, and a semantic search engine. You will fine‑tune LLMs using LoRA and QLoRA, deploy RAG pipelines with LangChain and LlamaIndex, and implement production‑grade MLOps practices including experiment tracking, CI/CD, monitoring, and drift detection. You will also explore advanced topics such as reinforcement learning from human feedback (RLHF), agentic AI with tool use, speech recognition (Whisper), text‑to‑speech, and multimodal NLP with vision‑language models.

The course includes dedicated sections on interview preparation with top NLP theory questions, coding challenges, and a full mock interview. You will complete a <

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