AI+ Engineer

– Foundations of Artificial Intelligence
• Introduction to AI
• Core Concepts and Techniques in AI
• Ethical Considerations

– Introduction to AI Architecture
• Overview of AI and its Various Applications
• Introduction to AI Architecture
• Understanding the AI Development Lifecycle
• Hands-on: Setting up a Basic AI Environment

– Fundamentals of Neural Networks
• Basics of Neural Networks
• Activation Functions and Their Role
• Backpropagation and Optimization Algorithms
• Hands-on: Building a Simple Neural Network Using a Deep Learning Framework

– Applications of Neural Networks
• Introduction to Neural Networks in Image Processing
• Neural Networks for Sequential Data
• Practical Implementation of Neural Networks

– Significance of Large Language Models (LLM)
• Exploring Large Language Models
• Popular Large Language Models
• Practical Finetuning of Language Models
• Hands-on: Practical Finetuning for Text Classification

– Application of Generative AI
• Introduction to Generative Adversarial Networks (GANs)
• Applications of Variational Autoencoders (VAEs)
• Generating Realistic Data Using Generative Models
• Hands-on: Implementing Generative Models for Image Synthesis

– Natural Language Processing
• NLP in Real-world Scenarios
• Attention Mechanisms and Practical Use of Transformers
• In-depth Understanding of BERT for Practical NLP Tasks
• Hands-on: Building Practical NLP Pipelines with Pretrained Models

– Transfer Learning with Hugging Face
• Overview of Transfer Learning in AI
• Transfer Learning Strategies and Techniques
• Hands-on: Implementing Transfer Learning with Hugging Face Models for Various Tasks

– Crafting Sophisticated GUIs for AI Solutions
• Overview of GUI-based AI Applications
• Web-based Framework
• Desktop Application Framework

– AI Communication and Deployment Pipeline
• Communicating AI Results Effectively to Non-Technical Stakeholders
• Building a Deployment Pipeline for AI Models
• Developing Prototypes Based on Client Requirements
• Hands-on: Deployment