DeepLearning.AI

Launching today: The Data Analytics Professional Certificate! With data playing a central role in industries from technology to healthcare to business, the ability to analyze and interpret information is more valuable than ever. Taught by Sean Barnes, Data Science & Engineering Leader at Netflix, this five-course program will help you build job-ready analytics skills—even if you’re starting from scratch. Starting today, you can enroll in: ✔ Data Analytics Foundations – Learn to organize, analyze, and visualize data. ✔ Applied Statistics for Data Analytics – Use statistical techniques to make real-world decisions. The demand for data professionals is growing fast. Ready to start? Enroll here: https://bit.ly/4iynxUv

Kyutai introduced MoshiVis, an upgraded version of the Moshi voice-to-voice model that can now accept image inputs. By adding a pretrained vision encoder, users can now ask the model about uploaded images, and the model responds with voice outputs. While it’s not as accurate as text-prompted vision-language models like PaliGemma, MoshiVis remains highly responsive in conversation with low latency and smooth transitions between visual and conversational topics. MoshiVis demonstrates a lightweight and fairly straightforward way to integrate vision and other modalities into speech-first systems. The model’s weights are also freely available under a permissive license. Learn more in The Batch: https://hubs.la/Q03fPwB60

What do eigenvalues and eigenvectors really mean? Luis Serrano makes it visual and intuitive—no linear algebra background needed. This is just a glimpse of what you’ll explore in the Mathematics for Machine Learning Specialization. Learn more: https://bit.ly/3PKd3or

This week, in The Batch, Andrew Ng explores when and how to use “lazy prompting” — a technique where experienced users first give LLMs minimal context in a prompt, then add more only if needed. Plus: 🗞️ MoshiVis adds vision to voice AI 🗞️ Cloudflare fights AI scrapers with fake pages 🗞️ Studies explore ChatGPT’s emotional impact Read The Batch: https://hubs.la/Q03fNjCG0

Freeform LLM outputs are great for chat. But if you're building software? You need structure—something your system can reliably read and use. In this new short course, Getting Structured LLM Output, built with .txt, taught by Will Kurt and Cameron Pfiffer, you’ll learn how to guide LLMs to produce structured outputs using: ✨ OpenAI’s structured output API 🔁 The Instructor library for output validation and re-prompting 🧩 DotTxt’s Outlines library for token-level control using regular expressions (regex) to enforce structure One of the hands-on projects of the course is a social media analysis agent. It reads user posts, identifies sentiment, checks if a reply is needed, and, if there's an issue, automatically generates a support ticket. All output as clean, structured JSON that other tools can process. Start learning today: https://hubs.la/Q03fxVjY0

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by DeepLearning.AI on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here! https://lnkd.in/g5F6PZ5p

Stanford researchers developed Tutor CoPilot, a GPT-4-powered tool that helps online tutors provide real-time support to students. The system offers tutors a selection of pedagogically sound strategies—like asking questions or giving hints—and generates tailored responses based on those strategies and students' responses. In a study of over 1,700 students, those supported by tutors using the tool performed better on lesson tests than those whose tutors didn't use the tool, especially when the tutors were less experienced. While long-term effects remain unclear, the results show that large language models can support both student learning and tutor training at a low cost. Learn more in The Batch: https://hubs.la/Q03fjZQC0

📺 How does Netflix know which shows you’ll binge next? 🍿 How do they decide which content gets greenlit? It’s more science than art. In fact, it’s data analytics. Sean Barnes, Data Science & Engineering Leader at Netflix, and the instructor for the Data Analytics Professional Certificate, has been working at the heart of it. With experience in both academia and industry, Sean will guide you through: 🔹 How to extract key insights from datasets and apply them to business problems. 🔹 Using numbers to make informed decisions—from hypothesis testing to probability. 🔹 See how generative AI can help automate tasks, summarize trends, and enhance your workflow. 🔹 Build compelling visualizations with Tableau and Google Sheets that communicate insights effectively. 🔗 Enroll now: https://lnkd.in/gaYnQVju

Just ahead of NVIDIA GTC on March 14, Nebius was featured as a Luminary Sponsor at AI Dev 2025. Captured here at our booth are Nebius’ CBO Roman Chernin and Andrew Ng — thanks for stopping by! Roman also joined a main stage panel, “Building AI Applications in 2025,” with leaders from Hugging Face, Stanford University, Replit, Arm and more. You can watch the session here: https://lnkd.in/ezPg4CVi Finally, we teamed up with Bryan Catanzaro, Vice President of Applied Deep Learning Research at NVIDIA, for the talk on accelerating AI development, where our Head of Product in ML/AI Aleksandr Patrushev shared how Nebius is helping developers move faster, from experiments to production. Huge thanks to DeepLearning.AI for bringing us all together! #AI #conferences #networking #talks

Missed our talk at DeepLearning.AI’s Dev 25? Catch the recording of “Building and Deploying Agentic Workflows with Haystack” with our Developer Relations Engineer, Bilge Yücel 👉 https://lnkd.in/dpsw9w2u Big thanks to the DeepLearning.AI team for this event, and to everyone who stopped by to learn and say hello! #AIEngineering #Haystack #AIAgents #DeepLearningAI #OpenSource #deepset