Become an AI Engineer

Courses under this program:
Course 1: Python for Data Science and Machine Learning Essential Training Part 1
-Learn Python programming skills for data science and machine learning. Discover how to clean, transform, analyze, and visualize data, as you build a practical, real-world project.

Course 2: Python for Data Science and Machine Learning Essential Training Part 2
-In the second half of this two-part course, explore the essentials of using Python for data science and machine learning.

Course 3: Generative AI: Introduction to Large Language Models
-Gain a foundational knowledge of how large language models and other Generative AI models work.

Course 4: The AI Ecosystem for Developers: Models, Datasets, and APIs
-This is a comprehensive guide to understanding key components of the AI ecosystem: models, datasets, and APIs.

Course 5: LLM Foundations: Vector Databases for Caching and Retrieval Augmented Generation (RAG)
-Learn about the basics of vector databases and how to use them in LLM caching and retrieval-augmented generation.

Course 6: Advanced LLMs with Retrieval Augmented Generation (RAG): Practical Projects for AI Applications
-Discover the core concepts of successful AI applications using LLMs to achieve high levels of performance and accuracy.

Course 7: Fine-Tuning for LLMs: from Beginner to Advanced
-Gain the expertise you need in Large Language Models (LLMs), a rapidly evolving field in AI, including hands-on practice.

Course 8: Understanding Generative AI in Cloud Computing: Services and Use Cases
-Learn how to get started using cloud-based generative AI services and tools.

Course 9: GenAIOps Foundations
-Leverage GenAIOps in your enterprises for effective development, deployment, and management of GenAI applications.

Course 10: Foundations of Responsible AI
-Explore a practical framework for implementing AI practices in a way that bridges the gap between high-level AI ethics principles and day-to-day technical decisions.