Introduction
Today Generative AI is the technology behind basically everything from creating realistic images to composing music and is rapidly transforming various fields. Wondering where to start with this cool technology? Or how to learn about it without spending too much time or signing up for long courses? If that’s you, you’ve found the right blog.
This guide offers a meticulously curated learning path through a series of short courses provided by DeepLearning.ai. From grasping the fundamental concepts to crafting your own generative AI applications, we will lead you step-by-step into the world of artificial intelligence. Let’s embark on exploring 30+ free generative AI short courses.
Table of contents
Free Generative AI Short Courses by Deeplearning.ai
These free generative AI short courses are divided category wise, from beginner to advanced. Let us have a look on all the free generative AI short courses by Deeplearning.ai:
1. Building Your Foundation (Beginners)
The journey starts with establishing a strong foundation. Here are the crucial first steps:
- Open Source Models with Hugging Face: This course introduces you to Hugging Face, a popular toolkit that serves as the backbone for working with many generative models. Mastering Hugging Face will unlock a vast ecosystem of tools and resources. (Click here to explore this course)
- Generative AI with Large Language Models (LLMs): Dive into the world of LLMs, a powerful type of generative model capable of generating human-quality text, translating languages, and writing different kinds of creative content. This course equips you with a solid understanding of LLM capabilities. (Click here to explore this course)
- Preprocessing Unstructured Data for LLM Applications: Generative models thrive on clean data. This course teaches you the essential techniques for preparing unstructured data, like text or images, for optimal use with LLMs. (Click here to explore this course)
- Prompt Engineering with Llama 2 (or Prompt Engineering for Vision Models): The magic lies in the “prompt.” This course empowers you with the art of prompt engineering, the skill of crafting specific instructions that guide LLMs towards generating the desired outputs. Choose the course that aligns with your focus: Prompt Engineering with Llama 2 for text-based applications or Prompt Engineering for Vision Models if you’re interested in generating images.(Click here to explore this course)
Optional Exploration (Beginners)
After building a solid foundation, consider expanding your knowledge with this optional course:
- How Diffusion Models Work: Generative AI encompasses different approaches. This course explores the inner workings of diffusion models, another powerful generative model type with unique capabilities. (Click here to explore this course)
2. Building Generative AI Applications (Intermediate)
Now that you have the fundamentals, let’s get hands-on! These courses equip you with the skills to build your own generative AI applications:
- Building Generative AI Applications with Gradio: Learn how to create user-friendly interfaces for your generative models, allowing users to interact with them seamlessly. (Click here to explore this course)
- Knowledge Graphs RAG: Take your Retrieval-Augmented Generation (RAG) models to the next level! This course explores how knowledge graphs can enhance the accuracy and context of your generated outputs. (Click here to explore this course)
- JavaScript RAG Web Apps with Llama: Build interactive web applications powered by LLMs. This course equips you with the skills to leverage JavaScript and Llama to create engaging user experiences. (Click here to explore this course)
- Large Language Models for Semantic Search: Unlock the potential of LLMs for semantic search tasks. This course teaches you how to leverage LLMs to find relevant information within vast amounts of data. (Click here to explore this course)
3. Advanced Topics (Intermediate/Advanced)
Ready to delve deeper? These courses tackle more advanced aspects of generative AI:
- Evaluating and Debugging Generative AI: Building generative models is just the beginning. This course equips you with the skills to evaluate and troubleshoot your models, ensuring they perform optimally. (Click here to explore this course)
- Automated Testing for LLMs: Streamline your development process by learning how to automate testing procedures for your LLM applications. (Click here to explore this course)
- LLMOps (Large Language Model Operations): As your generative AI applications grow in complexity, managing their deployments becomes crucial. This course introduces LLMOps practices to efficiently manage your LLM deployments. (Click here to explore this course)
- MLOps Tools for Managing Generative AI: Leverage MLOps tools to streamline the development, deployment, and management of your generative AI applications. (Click here to explore this course)
4. Specialization (Focus may vary)
Once you have a strong foundation in core concepts, you can specialize in a particular area that interests you. Here are some examples:
- Fine-Tuning Large Language Models: Dive deeper into an advanced technique for customizing LLMs to your specific needs. (Click here to explore this course)
- Large Language Models Semantic Search (Deeper dive): Further refine your knowledge of LLM semantic search with this advanced course. (Click here to explore this course)
- Microsoft Semantic Kernel: Focus on a specific component within LLMs with this specialized course. Depending on your chosen focus from section IV, you might also consider. (Click here to explore this course)
- Building Systems with ChatGPT: Gain hands-on experience building systems with a specific LLM like ChatGPT. (Click here to explore this course)
5. Deployment Considerations (Advanced)
While not immediately essential, these courses provide valuable knowledge for future deployment needs:
- Getting Started with Mistral: This course introduces a deployment tool that can be helpful when you’re ready to deploy your generative AI applications in real-world scenarios. (Click here to explore this course)
- Quantization Fundamentals with Hugging Face: Learn techniques to optimize your generative models for efficiency, making them faster and lighter to run on deployment. (Click here to explore this course)
Click here to explore the list of all the Deeplearning.ai courses!
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Conclusion
DeepLearning.ai’s guide offers a structured learning path for beginners, intermediate learners, and advanced practitioners in Generative AI. The free courses cater to various skill levels, from creating realistic images to composing music. The guide provides a gateway to a world where imagination meets technology, allowing anyone to explore the fascinating realm of Generative AI and develop the knowledge and skills to craft their own AI-driven innovations. In this article we explored 30+ Free Generative AI Short Courses (along with the sequence) which will help you in upgrading your skill.
I’m a data lover who enjoys finding hidden patterns and turning them into useful insights. As the Manager - Content and Growth at Analytics Vidhya, I help data enthusiasts learn, share, and grow together.
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