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Catalog > All Topics

AI+ Developer (AI+ Developer)

AI CERTS
  • Course Summary
  • Schedule
5 Days
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$3,995.00
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    • T87182
    • 5 days
    • 06/23/2025 - 06/27/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
    • Presented via WebEx
      • VC
        Virtual Classroom
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    • T87183
    • 5 days
    • 07/14/2025 - 07/18/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
    • Presented via WebEx
      • VC
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    • T87184
    • 5 days
    • 08/18/2025 - 08/22/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
    • Presented via WebEx
      • VC
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    • T87185
    • 5 days
    • 09/15/2025 - 09/19/2025*
    • 9:00 AM
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    • T87186
    • 5 days
    • 10/06/2025 - 10/10/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
    • Presented via WebEx
      • VC
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    • T87187
    • 5 days
    • 11/17/2025 - 11/21/2025*
    • 9:00 AM
    • (GMT -06:00) Central Standard Time
    • Presented via WebEx
      • VC
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    • T87188
    • 5 days
    • 12/15/2025 - 12/19/2025*
    • 9:00 AM
    • (GMT -06:00) Central Standard Time
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      • VC
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Course Summary
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Description

Elevate your skills with the AI Developer Course, which covers everything from Python for AI development to advanced machine learning techniques. Learn to build intelligent solutions with hands-on projects and real-world applications in this AI development course. Join us and earn your AI Developer certification today! Gain practical skills with AI developer Certification Course and become a leader in AI development.

AI+ Developer course equips you with essential skills in Python programming, mathematics, and data science for AI development. Master Python basics and advanced concepts, including object-oriented programming and performance optimization. Dive into mathematics for machine learning with linear algebra, calculus, and probability. This course prepares you to excel in AI development, offering practical knowledge in AI+ Developer Training to build, test, and optimize AI models and applications.

 

Objectives

  • Understand the essentials of AI and gain proficiency in Python for AI development.
  • Learn the architectures of deep learning and neural networks and their applications.
  • Explore various specialized AI applications across different industry sectors.
  • Acquire knowledge about large language models, including GPT, and master the art of prompt engineering.
  • Develop the skills to utilize AI tools, manage AI operations, and effectively deploy AI models in real-world scenarios.

Prerequisites

Required

  • Familiarity with high school-level algebra and basic statistics is desirable.
  • Understanding the basic programming concepts (variables, functions, and loops) and data structures (lists and dictionaries).
  • Fundamental knowledge of programming skills.

Recommended

  • AI+ Everyone
  • AI+ Executive

Who Should Attend

  • AI Engineer
  • Software Developer
  • Programmer

Outline

Foundations of Artificial Intelligence

  • Introduction to AI
  • Types of Artificial Intelligence
  • Branches of Artificial Intelligence
  • Applications and Business Use Cases

Mathematical Concepts for AI

  • Linear Algebra
  • Calculus
  • Probability and Statistics
  • Discrete Mathematics

Python for Developer

  • Python Fundamentals
  • Python Libraries

Mastering Machine Learning

  • Introduction to Machine Learning
  • Supervised Machine Learning Algorithms
  • Unsupervised Machine Learning Algorithms
  • Model Evaluation and Selection

Deep Learning

  • Neural Networks
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)

Computer Vision

  • Image Processing Basics
  • Object Detection
  • Image Segmentation
  • Generative Adversarial Networks (GANs)

Natural Language Processing

  • Text Preprocessing and Representation
  • Text Classification
  • Named Entity Recognition (NER)
  • Question Answering (QA)

Reinforcement Learning

  • Introduction to Reinforcement Learning
  • Q-Learning and Deep Q-Networks (DQNs)
  • Policy Gradient Methods

Cloud Computing in AI Development

  • Cloud Computing for AI
  • Cloud-Based Machine Learning Services

Large Language Models

  • Understanding LLMs
  • Text Generation and Translation
  • Question Answering and Knowledge Extraction

Cutting-Edge AI Research

  • Neuro-Symbolic AI
  • Explainable AI (XAI)
  • Federated Learning
  • Meta-Learning and Few-Shot Learning

AI Communication and Documentation

  • Communicating AI Projects
  • Documenting AI Systems
  • Ethical Considerations

Optional Module: AI Agents for Developers

  • Understanding AI Agents
  • Case Studies
  • Hands-On Practice with AI Agents

 

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