All courses
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.
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.
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.
Laurence MoroneyDeepLearning.AI
In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data and retrain deployed models with user data while maintaining data privacy. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, 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.
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.
Frank KaneUdemy
In an era where Machine Learning (ML) and Artificial Intelligence (AI) are revolutionizing industries across the globe, understanding how giants like Google, Amazon, and Udemy leverage these technologies to extract meaningful insights from vast data sets is more critical than ever. Whether you're aiming to join the ranks of top-tier AI specialists or you're driven by the fascinating challenges this field offers, our course is your gateway to an exciting new career trajectory. Designed for individuals with programming or scripting backgrounds, this course goes beyond the basics, preparing you to stand out in the competitive tech industry. Our curriculum, enriched with over 145 lectures and 20+ hours of video content, is crafted to provide hands-on experience with Python, guiding you from the fundamentals of statistics to the cutting-edge advancements in generative AI.
Richmond AlakeDeepLearning.AI
In this course, you will learn how to use pre-filtering, post-filtering, and projection techniques to optimize query processing and output. You will also explore prompt compression techniques to handle long and expensive prompts in large-scale applications. Additionally, you will learn to combine vector search capabilities with traditional database operations to build efficient and cost-effective RAG applications. This course is ideal for Python developers, database enthusiasts, and AI practitioners looking to enhance their skills in these areas.
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.
Andrew NgDeepLearning.AI
In this Machine Learning in Production course, you will build intuition about designing a production ML system end-to-end: project scoping, data needs, modeling strategies, and deployment patterns and technologies. You will learn strategies for addressing common challenges in production like establishing a model baseline, addressing concept drift, and performing error analysis. You’ll follow a framework for developing, deploying, and continuously improving a productionized ML application.
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.
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.
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.
Bryan D. Eldridge, M.Ed.Maven
This course will enable life science practitioners with no prior experience in building AI-driven applications to leverage their subject matter expertise and existing capabilities around data and statistical models - in tandem with easily accessible support and resources - to design and execute their first AI project. You will understand how AI has impacted the traditional data lifecycle, master the basics of the AI lifecycle, develop a comprehensive understanding of the contemporary AI landscape, and explain how each major type of AI model is applicable to life sciences.
Amit RawalMaven
By the end of the course, you'll become adept at using AI to turn 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 that were previously unimaginable. You’ll get step-by-step guidance and 50+ prompts to go from identifying the right questions to weaving data into an impactful narrative.
João AscensãoOne Month PM
This course covers everything from the basics of AI and data science to advanced product management techniques. You will learn how to frame AI problems, develop AI products, and strategize using data. The course also includes live Q&A sessions with industry leaders, providing practical insights into managing AI-driven products.
