AI+ Developer™

Get hands-on with the tools and technologies that power the AI ecosystem.
  • Core AI Foundations: Covers Python, deep learning, data processing, and algorithm design
  • Hands-on Projects: Focus on NLP, computer vision, and reinforcement learning
  • Advanced Modules: Includes time series, model explainability, and cloud deployment
  • Industry-Ready Skills: Prepares learners to design and deploy complex AI systems

Módulos

  • Course Overview:
    1. Course IntroductionPreview
  • Module 1: Foundations of Artificial Intelligence:
    1. 1.1 Introduction to AI Preview
    2. 1.2 Types of Artificial Intelligence Preview
    3. 1.3 Branches of Artificial Intelligence
    4. 1.4 Applications and Business Use Cases
  • Module 2: Mathematical Concepts for AI:
    1. 2.1 Linear Algebra Preview
    2. 2.2 Calculus Preview
    3. 2.3 Probability and Statistics Preview
    4. 2.4 Discrete Mathematics
  • Module 3: Python for Developer :
    1. 3.1 Python Fundamentals Preview
    2. 3.2 Python Libraries
  • Module 4: Mastering Machine Learning:
    1. 4.1 Introduction to Machine Learning
    2. 4.2 Supervised Machine Learning Algorithms
    3. 4.3 Unsupervised Machine Learning Algorithms
    4. 4.4 Model Evaluation and Selection
  • Module 5: Deep Learning:
    1. 5.1 Neural Networks
    2. 5.2 Improving Model Performance
    3. 5.3 Hands-on: Evaluating and Optimizing AI Models
  • Module 6: Computer Vision:
    1. 6.1 Image Processing Basics
    2. 6.2 Object Detection
    3. 6.3 Image Segmentation
    4. 6.4 Generative Adversarial Networks (GANs)
  • Module 7: Natural Language Processing:
    1. 7.1 Text Preprocessing and Representation
    2. 7.2 Text Classification
    3. 7.3 Named Entity Recognition (NER)
    4. 7.4 Question Answering (QA)
  • Module 8: Reinforcement Learning:
    1. 8.1 Introduction to Reinforcement Learning
    2. 8.2 Q-Learning and Deep Q-Networks (DQNs)
    3. 8.3 Policy Gradient Methods
  • Module 9: Cloud Computing in AI Development:
    1. 9.1 Cloud Computing for AI
    2. 9.2 Cloud-Based Machine Learning Services
  • Module 10: Large Language Models:
    1. 10.1 Understanding LLMs
    2. 10.2 Text Generation and Translation
    3. 10.3 Question Answering and Knowledge Extraction
  • Module 11: Cutting-Edge AI Research:
    1. 11.1 Neuro-Symbolic AI
    2. 11.2 Explainable AI (XAI)
    3. 11.3 Federated Learning
    4. 11.4 Meta-Learning and Few-Shot Learning
  • Module 12: AI Communication and Documentation:
    1. 12.1 Communicating AI Projects
    2. 12.2 Documenting AI Systems
    3. 12.3 Ethical Considerations
  • Optional Module: AI Agents for Developers:
    1. 1. Understanding AI Agents
    2. 2. Case Studies
    3. 3. Hands-On Practice with AI Agents

Herramientas de IA

  • GitHub Copilot
  • Lobe
  • H2O.ai
  • Snorkel
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