2026 Skills Trends Learning Path

An extensive course on advanced Retrieval Augmented Generation (RAG) techniques using Llama Index and LangChain, created in collaboration with Llama Index. It covers industry-specific projects and features like Deep Memory for improved retrieval accuracy.

Generative AI: Prompt Engineering Basics

Learn 99% Of People STILL Don't Know The Basics Of Prompting (ChatGPT, Gemini, Claude)

ChatGPT & OpenAI API Development Masterclass

Learn Functions, Tools and Agents with LangChain

LangChain Agent Development Mastery

This course provides a comprehensive overview of how machine learning functions in embedded systems. It teaches students how to train neural networks and deploy them to microcontrollers, a field also known as TinyML. The course is designed for beginners with no prior machine learning experience, but some familiarity with Arduino and microcontrollers is recommended.

Offered by Vanderbilt University, this course teaches how to write effective prompts for large language models like ChatGPT. You'll learn prompt patterns to unlock powerful capabilities and create complex prompt-based applications.

This specialization from Vanderbilt University teaches how to leverage ChatGPT's free AI tools for various professional tasks including planning, project management, writing, data analytics, and marketing. It also covers Anthropic Claude.

This specialization by Vanderbilt University covers prompt engineering from fundamentals to advanced skills. It teaches how to use large language models for various applications, including writing, summarization, and problem-solving, through a series of practical courses.

This course from Harvard University introduces the field of Tiny Machine Learning (TinyML), which involves running machine learning models on low-power microcontrollers. It covers the fundamentals of deep learning, data collection, and model deployment on embedded devices, with a focus on applications like keyword spotting and image classification.

This intermediate-level course explores advanced prompting techniques such as chain-of-thought, tree-of-thought, and directional stimulus prompting to get more out of large language models.

LLM Application Development with LangChain

Prompt Engineering Masters VIP

LangChain for LLM Application Development

The first course in this specialization is an excellent entry point for practical computer vision. You will learn to build and deploy models in the browser using TensorFlow.js, including creating a real-time object detector that runs on a webcam feed.

This course provides an introduction to generative AI, covering topics like machine learning, virtual environments, and responsible AI.

This course covers the end-to-end process of building and maintaining production ML systems. It includes modules on data needs and modeling strategies, which touch upon the importance of choosing the right data storage and handling evolving data, a key consideration when deciding between row, columnar, and vector-based storage.

This specialization from Google Cloud on Coursera teaches how to build and deploy ML models on Google Cloud Platform. It covers Vertex AI, AutoML, Big Query ML, and TensorFlow, preparing learners for a career in cloud-based machine learning.

This course teaches you how to use open-source models from the Hugging Face Hub for various tasks like NLP, audio, and image processing. You will learn to use the transformers library to perform these tasks with just a few lines of code and deploy your applications using Gradio and Hugging Face Spaces.