Spécialisation Learn Generative AI with LLMs

Throughout the specialization, you'll have access to course materials, lecture videos, and discussion forums to address any questions or concerns you may have.

Throughout the course, you'll primarily be working with programming languages such as Python and utilizing tools like TensorFlow, PyTorch, Jupyter Notebook , Midjourney , Dall-E , Bard , Hugging Face, Tome , Write Sonic and GitHub Copilot for implementing Generative AI models. Additionally, familiarity with the Python Coding and its environment will be advantageous.

This specialization is suitable for a wide range of individuals, including beginners looking to enter the field of Generative AI and NLP, as well as seasoned professionals such as business analysts, data scientists, and IT professionals seeking to enhance their skills in this domain.

The specialization emphasizes practical application, with hands-on projects and assignments designed to reinforce learning and provide real-world experience. You'll have the opportunity to work on projects that simulate scenarios encountered in industry, allowing you to apply the concepts learned in the course.

Participants will develop an extensive range of skills in both foundational and advanced Generative AI approaches.

1. Python & Machine Learning Fundamentals: Improve your Python programming skills while learning key ML topics for AI applications.

2. Natural Language Processing (NLP): Understand text mining, preprocessing, categorization, and other fundamental NLP techniques.

3. LLM Architecture & Ethics: Learn about how large language models work, their internal architectures, performance tweaking, and ethical issues for biases and data privacy.

4. Generative AI Implementation: Learn how to use Autoencoders and GANs to produce text, code, graphics, and other content.

This specialization uniquely blends an in‑depth exploration of LLM architecture, performance tuning, and data ethics into a cohesive 4‑course sequence

It also covers hands‑on demonstrations using tools like LangChain, RAG, ChatGPT, MidJourney, OpenCV, and RASA to ensure real‑world generative AI experience

Absolutely. This specialization has multiple practical demonstrations which will help you understand and implement the generative AI concepts into practice.

This specialization is designed for anyone from aspiring AI newcomers to seasoned professionals. Beginners need to have a foundational understanding of Python.

Generative AI refers to algorithms that can generate new content (text, images, and audio) by learning patterns from previously collected data. When combined with Large Language Models (LLMs), such as transformer-based architectures, the system can predict and generate the next word or token in a sequence, allowing it to compose coherent essays, code snippets, or even draft poems.

LLMs provide complex text generation by exploiting enormous datasets and attention techniques, making them the foundation for modern Gen AI applications.

Learners can pursue roles as LLM Engineer, Prompt Engineer, NLP/Deep Learning Engineer, Data Scientist, AI Research Scientist, or AI Product Manager.

This specialization is perfect for software developers looking to deepen their Python, ML, and NLP skillsets through real‑world projects, and for product managers who need the technical insight to architect, evaluate, and guide AI‑powered product roadmaps.

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.