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Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs What you'll learn - The course provides the entire toolbox you need to become an AI Engineer - Understand key Artificial Intelligence concepts and build a solid foundation - Start coding in Python and learn how to use it for NLP and AI - Impress interviewers by showing an understanding of the AI field - Apply your skills to real-life business cases - Harness the power of Large Language Models - Leverage LangChain for seamless development of AI-driven applications by chaining interoperable components - Become familiar with Hugging Face and the AI tools it offers - Use APIs and connect to powerful foundation models - Utilize Transformers for advanced speech-to-text Requirements No prior experience is required. We will start from the very basics You’ll need to install Anaconda. We will show you how to do that step by step The Problem AI Engineers are best suited to thrive in the age of AI. It helps businesses utilize Generative AI by building AI-driven applications on top of their existing websites, apps, and databases. Therefore, it’s no surprise that the demand for AI Engineers has been surging in the job marketplace. Supply, however, has been minimal, and acquiring the skills necessary to be hired as an AI Engineer can be challenging. So, how is this achievable? Universities have been slow to create specialized programs focused on practical AI Engineering skills. The few attempts that exist tend to be costly and time-consuming. Most online courses offer ChatGPT hacks and isolated technical skills, yet integrating these skills remains challenging. The Solution AI Engineering is a multidisciplinary field covering AI principles and practical applications Python programming Natural Language Processing in Python Large Language Models and Transformers Developing apps with orchestration tools like LangChain Vector databases using PineCone Creating AI-driven application