31 Courses on Artificial Intelligence by DeepLearning.AI
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Quality and Safety for LLM Applications
Monitor and enhance security measures over time to safeguard your LLM applications.
Preprocessing Unstructured Data for LLM Applications
Learn to extract and normalize content from a wide variety of document types, such as PDFs, PowerPoints, Word, and HTML files, tables, and images to expand the information accessible to your LLM.
LLMOps
Adapt an open source pipeline that applies supervised fine-tuning on an LLM to better answer user questions.
Neural Networks and Deep Learning
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning.
AI Agents in LangGraph
Learn about LangGraph’s components and how they enable the development, debugging, and maintenance of AI agents.
Natural Language Processing in TensorFlow
This course is part of the DeepLearning.AI TensorFlow Developer Professional Certificate. When you enroll in this course, you'll also be enrolled in this Professional Certificate.
Natural Language Processing with Attention Models
Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, build chatbots & question-answering.
Natural Language Processing with Classification and Vector Spaces
Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies & translate words.
Natural Language Processing with Probabilistic Models
Use dynamic programming, hidden Markov models, and word embeddings to implement autocorrect, autocomplete & identify part-of-speech tags for words.
Natural Language Processing with Sequence Models
Use recurrent neural networks, LSTMs, GRUs & Siamese networks in Trax for sentiment analysis, text generation & named entity recognition.