All courses
Manisha AroraMaven
This course offers a dynamic blend of technical expertise and real-world business challenges. Through a series of interactive sessions, discussions, and hands-on projects, you will learn how to scope machine learning projects effectively, lead discussions with stakeholders, navigate the entire data science workflow from data exploration to model deployment, and communicate project insights and business impact to stakeholders.
Robert MonarchDeepLearning.AI
In this specialization, you will master a step-by-step framework for developing AI projects. You will analyze data and build AI models for projects focused on air quality, wind energy, biodiversity monitoring, and disaster management. Through real-world case studies, you will explore public health, climate change, and disaster management, and develop practical skills to make a positive impact using AI.
Sebastian WitalecDeepLearning.AI
In this course, you will gain the knowledge to make informed decisions about when to apply vector databases to your applications. You will explore how to use vector databases and LLMs to gain deeper insights into your data, build labs that show how to form embeddings, and use several search techniques to find similar embeddings. Additionally, you will explore algorithms for fast searches through vast datasets and build applications ranging from RAG to multilingual search.
Jay AlammarDeepLearning.AI
In this course, you will learn how to implement basic keyword search, enhance it with the rerank method, and use embeddings for dense retrieval. You will gain hands-on practice with large amounts of data and learn to overcome challenges like varying search results and accuracy. By the end of the course, you will be able to implement language model-powered search into your website or project.
Doug TurnbullMaven
In this course, you'll learn how to enhance your search engine's relevance using Large Language Models. You'll gain skills in query and content understanding, and learn to deploy LLMs in production efficiently. The course is designed to help you sidestep traditionally complex processes and achieve structured, well-formed queries, ultimately improving your team's search outcomes.
Luis SerranoDeepLearning.AI
In this specialization, you will gain a deep understanding of the mathematical principles that underpin machine learning algorithms. You will learn how to apply statistical techniques to enhance your data analysis, and acquire skills that are highly sought after by employers. By the end of the course, you will be able to implement and optimize machine learning algorithms, making you a valuable asset in the field of AI and data science.
Sung KimDeepLearning.AI
This course provides a comprehensive understanding of pretraining large language models. You'll learn to prepare data, configure models, and assess performance, with a focus on cost-effective strategies. The course covers creating high-quality datasets, using the Hugging Face library, and evaluating model performance with benchmark tasks.
Sharon ZhouDeepLearning.AI
In this specialization, you will learn to understand GAN components, build basic and advanced GANs using PyTorch, and control your GAN to build conditional GANs. You will compare generative models, use the FID method to assess GAN fidelity and diversity, and learn to detect bias in GANs. Additionally, you will explore GAN applications in data augmentation and privacy preservation, and implement Pix2Pix and CycleGAN for image translation.
Sean BarnesDeepLearning.AI
This comprehensive program equips you with the skills to manage the entire data lifecycle, from defining problems to delivering insights. You'll learn foundational analysis and visualization, statistical techniques, Python for automation, and data extraction from various sources. The course also covers AI integration in analytics, preparing you for the growing demand in data-centric roles.
Pranav RajpurkarDeepLearning.AI
In this Specialization, you will learn to diagnose diseases from x-rays and 3D MRI brain images, predict patient survival rates using tree-based models, estimate treatment effects using data from randomized trials, and automate the labeling of medical datasets using natural language processing. The course covers model interpretation, image segmentation, natural language extraction, and more.
Younes Bensouda MourriDeepLearning.AI
In the Natural Language Processing Specialization, you will learn to use logistic regression, naïve Bayes, and word vectors for sentiment analysis, analogies, and translations. You will also explore dynamic programming, hidden Markov models, and word embeddings for autocorrect, autocomplete, and part-of-speech tagging. Advanced topics include dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks for sentiment analysis, text generation, named entity recognition, and question identification. Finally, you will delve into encoder-decoder, causal, and self-attention models for machine translation, text summarization, question-answering, and chatbot creation.
Adrian Gonzalez SanchezDeepLearning.AI
In Building Your Own Database Agent, you will learn to interact with tabular data and SQL databases using natural language, enabling more efficient and accessible data analysis. You will gain hands-on experience with the Azure OpenAI Service, implementing techniques like Retrieval Augmented Generation (RAG) and function calling. By the end of the course, you’ll be equipped with the technical knowledge and practical experience to implement similar systems in your own projects or organizations, enabling more efficient and accessible data interaction and analysis.
Carey PhelpsDeepLearning.AI
In this course, you will learn to instrument a Jupyter notebook, manage hyperparameter configurations, log run metrics, collect artifacts for dataset and model versioning, and log experiment results. Additionally, you will learn to trace prompts and responses to LLMs over time in complex interactions. By the end of the course, you will have a systematic workflow to boost your productivity and accelerate your journey toward breakthrough results.
Matt RobinsonDeepLearning.AI
This course will teach you how to preprocess data for LLM application development, focusing on working with different document types. You will learn to extract and normalize various documents into a common JSON format, enrich it with metadata, and apply techniques for document image analysis to preprocess PDFs, images, and tables. By the end of the course, you will be able to build a RAG bot capable of ingesting different documents and apply these skills to real-world scenarios.
Tim TullyDeepLearning.AI
In this course, you will explore the implementation of six applications using vector databases. You will learn how to create a semantic search tool, enhance LLM applications with RAG, develop a recommender system, build a hybrid search app, create a facial similarity app, and implement an anomaly detection app. By the end of the course, you will have new ideas for building applications with any vector database.
Amit RawalMaven
By the end of this course, you'll be adept at using AI to transform complex data into compelling stories that drive action and impact. You'll learn how AI can augment your analytical capabilities, automate tedious tasks, and provide deeper insights. The course offers step-by-step guidance and over 50 prompts to help you craft impactful narratives using data.
