1 00:00:00,000 --> 00:00:08,000 Welcome to this overview of the Professional Certificate in RAG and Agentic AI. 2 00:00:08,000 --> 00:00:13,000 AI is evolving beyond traditional models, enabling smarter applications. 3 00:00:13,000 --> 00:00:22,000 Retrieval Augmented Generation, or RAG, enhances AI's ability to provide accurate, context-aware responses by integrating real-time information retrieval. 4 00:00:22,000 --> 00:00:34,000 Multimodal AI is another advancement that allows systems to process and integrate various types of data – text, images, audio, and video – enabling more dynamic and interactive user experiences. 5 00:00:34,000 --> 00:00:42,000 Agentic AI represents a further shift, equipping systems with the ability to reason, plan, and autonomously execute tasks. 6 00:00:42,000 --> 00:00:49,000 While each of these approaches can work independently, they can also be combined to create more powerful and adaptable AI systems. 7 00:00:49,000 --> 00:00:58,000 Through this program, you'll gain the expertise to build and implement AI applications that combine these powerful techniques, preparing you for the next wave of AI-driven innovation. 8 00:00:58,000 --> 00:01:09,000 Whether you're looking to advance in software engineering, machine learning, or data science, mastering RAG, Multimodal, and Agentic AI will give you a competitive edge in the evolving job market. 9 00:01:09,000 --> 00:01:14,000 This RAG and Agentic AI program consists of several short courses that cover 10 00:01:14,000 --> 00:01:16,000 Generative AI Applications 11 00:01:16,000 --> 00:01:17,000 RAG Applications 12 00:01:17,000 --> 00:01:19,000 Vector Databases for RAG 13 00:01:19,000 --> 00:01:22,000 Advanced RAG with Vector Databases and Retrievers 14 00:01:22,000 --> 00:01:24,000 Multimodal Generative AI Applications 15 00:01:24,000 --> 00:01:25,000 AI Agents 16 00:01:25,000 --> 00:01:29,000 Agentic AI Fundamentals with Langchain and Langgraph 17 00:01:29,000 --> 00:01:30,000 and finally, 18 00:01:30,000 --> 00:01:36,000 Agentic AI with Langgraph, Crew AI, AG2, formerly Autogen, and BAI Framework. 19 00:01:36,000 --> 00:01:40,000 Each topic corresponds to an online course that you can complete independently. 20 00:01:40,000 --> 00:01:43,000 Each course consists of 2-3 modules. 21 00:01:43,000 --> 00:01:49,000 Completing courses covering different topics and the required projects will earn you the completion certificate. 22 00:01:49,000 --> 00:01:51,000 Let's look at the contents of each course. 23 00:01:51,000 --> 00:02:00,000 Your journey in the first course begins with the basics of Generative AI along with an in-depth look at prompt engineering, in-context learning, and prompt templates. 24 00:02:00,000 --> 00:02:04,000 You'll also be introduced to the Langchain Framework to build Generative AI Applications, 25 00:02:04,000 --> 00:02:09,000 which streamlines AI workflows by enabling more structured and efficient prompt chaining. 26 00:02:09,000 --> 00:02:14,000 In the second course, you'll be introduced to the key components of Retrieval Augmented Generation or RAG. 27 00:02:14,000 --> 00:02:17,000 You'll also learn how to implement RAG using Langchain. 28 00:02:17,000 --> 00:02:23,000 This course also introduces you to Gradio, helping you set up an interface to interact with AI models. 29 00:02:23,000 --> 00:02:26,000 Finally, you'll work with Llama Index as an alternative to Langchain, 30 00:02:26,000 --> 00:02:31,000 gaining hands-on experience building a bot with Llama Index and IBM's Granite model. 31 00:02:31,000 --> 00:02:37,000 The third course introduces you to the transformative role of vector databases in modern data management systems. 32 00:02:37,000 --> 00:02:46,000 You will gain insights into ChromaDB's architecture, common coding practices for its operations, and hands-on skills in performing basic vector operations. 33 00:02:46,000 --> 00:02:49,000 Similarity search is also explained with hands-on labs. 34 00:02:49,000 --> 00:02:54,000 Finally, you will build a recommendation system using a vector database and an embedding model. 35 00:02:54,000 --> 00:02:59,000 The next course provides a deep dive into advanced retrievers and retrieval patterns, 36 00:02:59,000 --> 00:03:04,000 equipping you with the skills to implement and optimize retrieval strategies within a RAG system. 37 00:03:04,000 --> 00:03:09,000 You will work with FAISS, a powerful vector database used for efficient similarity search. 38 00:03:09,000 --> 00:03:14,000 You will also build a RAG application using FAISS, Langchain, and Gradio. 39 00:03:14,000 --> 00:03:18,000 The fifth course begins with an in-depth introduction to Multimodal AI, 40 00:03:18,000 --> 00:03:22,000 focusing on how AI systems process and integrate multiple data types. 41 00:03:23,000 --> 00:03:28,000 You will evaluate speech recognition and text-to-speech technologies, along with computer vision. 42 00:03:28,000 --> 00:03:33,000 You will work with tools such as OpenAI Whisper and Mistral to develop multimodal applications. 43 00:03:33,000 --> 00:03:39,000 You'll also explore how models like DALI generate images and the fundamentals of image captioning. 44 00:03:39,000 --> 00:03:46,000 Finally, you will dive into multimodal retrieval and search and multimodal question answering and chatbots, 45 00:03:46,000 --> 00:03:51,000 learning how cross-modal retrieval techniques enhance search engines and recommendation systems. 46 00:03:51,000 --> 00:03:55,000 The sixth course provides a detailed foundation for building AI agents. 47 00:03:55,000 --> 00:03:58,000 It covers function calling, chaining, and tool orchestration 48 00:03:58,000 --> 00:04:03,000 to enable AI systems to interact with external tools and execute tasks effectively. 49 00:04:03,000 --> 00:04:08,000 You'll also learn how to manually handle tool calls by parsing the outputs of language models. 50 00:04:08,000 --> 00:04:14,000 Finally, you will leverage Langchain's built-in agents, including DataFrame and SQL agents, 51 00:04:14,000 --> 00:04:20,000 to analyze structured data, generate visualizations, and perform database queries through natural language. 52 00:04:20,000 --> 00:04:25,000 The seventh course helps you use Langgraph and Langchain to develop stateful workflows. 53 00:04:25,000 --> 00:04:31,000 You'll explore key architectures such as agents and React agents, applying them to real-world applications. 54 00:04:31,000 --> 00:04:36,000 Additionally, the course introduces multi-agent system design and agentic RAG architecture, 55 00:04:36,000 --> 00:04:40,000 equipping you with skills to build scalable, robust applications. 56 00:04:40,000 --> 00:04:45,000 The eighth and final course helps you design AI workflows using state-of-the-art design patterns 57 00:04:45,000 --> 00:04:48,000 and multi-agent orchestration frameworks. 58 00:04:48,000 --> 00:04:53,000 You will be introduced to agentic frameworks such as Crew AI and Langgraph. 59 00:04:53,000 --> 00:04:59,000 Finally, you will dive into alternative agentic frameworks, IBM's BAI framework, 60 00:04:59,000 --> 00:05:04,000 and AG2 to implement multi-agent collaboration and conversation-driven systems. 61 00:05:04,000 --> 00:05:08,000 This program presents you with practice and graded quizzes to evaluate your learning. 62 00:05:08,000 --> 00:05:12,000 The graded quizzes carry a weightage that contributes to the course completion. 63 00:05:12,000 --> 00:05:17,000 These courses have hands-on labs and projects that contribute to the course and program completion requirements. 64 00:05:17,000 --> 00:05:21,000 Finally, after you have successfully completed all of the courses, 65 00:05:21,000 --> 00:05:27,000 you will be awarded the completion certificate for this IBM program, a credential valued by many employers. 66 00:05:27,000 --> 00:05:30,000 We wish you the very best and hope you enjoy this journey.