AI+ Engineer™

Módulos

• Course Overview:
  1. Course Introduction Preview
• Module 1: Foundations of Artificial Intelligence :
  1. 1.1 Introduction to AI Preview
  2. 1.2 Core Concepts and Techniques in AI Preview
  3. 1.3 Ethical Considerations
• Module 2: Introduction to AI Architecture :
  1. 2.1 Overview of AI and its Various ApplicationsPreview
  2. 2.2 Introduction to AI Architecture Preview
  3. 2.3 Understanding the AI Development Lifecycle Preview
  4. 2.4 Hands-on: Setting up a Basic AI Environment
• Module 3: Fundamentals of Neural Networks:
  1. 3.1 Basics of Neural Networks Preview
  2. 3.2 Activation Functions and Their Role Preview
  3. 3.3 Backpropagation and Optimization Algorithms
  4. 3.4 Hands-on: Building a Simple Neural Network Using a Deep Learning Framework
• Module 4: Applications of Neural Networks:
  1. 4.1 Introduction to Neural Networks in Image Processing
  2. 4.2 Neural Networks for Sequential Data
  3. 4.3 Practical Implementation of Neural Networks
• Module 5: Significance of Large Language Models (LLM):
  1. 5.1 Exploring Large Language Models
  2. 5.2 Popular Large Language Models
  3. 5.3 Practical Finetuning of Language Models
  4. 5.4 Hands-on: Practical Finetuning for Text Classification
• Module 6: Application of Generative AI :
  1. 6.1 Introduction to Generative Adversarial Networks (GANs)
  2. 6.2 Applications of Variational Autoencoders (VAEs)
  3. 6.3 Generating Realistic Data Using Generative Models
  4. 6.4 Hands-on: Implementing Generative Models for Image Synthesis
• Module 7: Natural Language Processing :
  1. 7.1 NLP in Real-world Scenarios
  2. 7.2 Attention Mechanisms and Practical Use of Transformers
  3. 7.3 In-depth Understanding of BERT for Practical NLP Tasks
  4. 7.4 Hands-on: Building Practical NLP Pipelines with Pretrained Models
• Module 8: Transfer Learning with Hugging Face :
  1. 8.1 Overview of Transfer Learning in AI
  2. 8.2 Transfer Learning Strategies and Techniques
  3. 8.3 Hands-on: Implementing Transfer Learning with Hugging Face Models for Various Tasks
• Module 9: Crafting Sophisticated GUIs for AI Solutions :
  1. 9.1 Overview of GUI-based AI Applications
  2. 9.2 Web-based Framework
  3. 9.3 Desktop Application Framework
• Module 10: AI Communication and Deployment Pipeline :
  1. 10.1 Communicating AI Results Effectively to Non-Technical Stakeholders
  2. 10.2 Building a Deployment Pipeline for AI Models
  3. 10.3 Developing Prototypes Based on Client Requirements
  4. 10.4 Hands-on: Deployment
• Optional Module: AI Agents for Engineering:
  1. 1. Understanding AI Agents
  2. 2. Case Studies
  3. 3. Hands-On Practice with AI Agents

Herramientas de IA

• TensorFlow
• Hugging Face Transformers
• Jenkins
• TensorFlow Hub