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AI Engineering

AI301: Introduction to Modern Artificial Intelligence

Course Description
Welcome to AI301: Intro to Modern Artificial Intelligence. The course is designed to provide technical individuals with basic knowledge of mathematics and programming, skills to build, maintain, and serve AI powered tools. We will start our exploration in the field of AI by diving into the history of the field so participants can develop an intuitive understanding of the technology before starting hands-on exploration. We will create a simple neural network as a starting point building up to participants building (or finetuning) their very own small language model. The business applications part of the course will consist of emulating real world business problems and solving them using modern AI tools and techniques. The course will culminate into a deep dive into AI agents. Participants will learn to create AI agents that operate autonomously, perceive their environment, persist over a prolonged time, adapt to change, and create and pursue goals.

Course Outcome
Participants after completing the course will be well versed in modern AI technologies and will be able to solve real world business problems using AI. Participants will be well versed in the following topics:
  • History of AI
  • Basic of deep learning
  • Pytorch for Deep learning
  • The Transformers Architecture
  • Pre-training of LLMs
  • Training a Small Language Model
  • Large Language Models
  • Vision Language Models
  • Speech Models
  • Huggingface Transformers Library
  • How to use open-source AI models Fine-tuning open-source AI models
  • Supervised finetuning
  • Unsupervised Finetuning
  • Reinforcement learning though Human Feedback
  • Direct Preference Optimization
  • Parameter efficient fine-tuning
  • Prompt Tuning
  • Prefix Tuning
  • Low Rank Adaptation (LoRA) Serving LLMs using inference libraries.
  • Inference optimization:
  • Distilling LLMs Quantization Agentic AI
  • Simple reflex agents
  • Model-based reflex agents
  • Goal-based agents
  • Utility-based agents
  • Learning agents AI orchestration using multi-agent systems Cloud AI-ops for serving AI systems
  • AWS AI solutions
  • Azure AI solutions

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