AI+ Developer™

# AT-310

Master AI Development: From Fundamentals to Advanced Tools
The AI+ Developer™ certification provides a comprehensive learning path into core AI development concepts. Designed for aspiring developers, this program covers key areas like Python programming, data processing, deep learning, and algorithm optimization. Participants will gain hands-on experience in Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning, enabling them to solve real-world challenges effectively. The curriculum includes advanced modules on time series analysis, model explainability, and cloud-based deployment strategies. Upon completion, learners will hold the expertise to tackle complex AI system design and deployment, making them industry-ready.

$495.00

What’s included?
One-year subscription (with all updates):

  • High-Quality Videos and E-Book
  • AI Mentor for Personalized Guidance
  • Quizzes, Assessments, and Course Resources
  • Proctored Exam with One Free Retake
  • Exam Study Guide
  • Hands-on labs

Prerequisites

  • Basic Math Knowledge: High-school-level algebra and statistics are desirable.
  • Computer Science Fundamentals: Familiarity with variables, functions, loops, and data structures like lists and dictionaries.
  • Programming Skills: A foundational understanding of coding is recommended.

Exam Details

What Will You Learn?

Python Programming Proficiency
Gain a strong foundation in Python for building AI algorithms, processing data, and creating scalable AI applications.
Cloud Computing in AI Development
Explore cloud-based solutions using AWS, Google Cloud, and Microsoft Azure for deploying scalable AI systems.
Deep Learning Techniques
Master deep learning frameworks for challenges in image recognition, natural language processing, and predictive analytics.
Project Management in AI
Acquire skills to manage AI projects, including planning, resource allocation, and stakeholder communication.

Certification Modules

Foundations of Artificial Intelligence
  • Introduction to AI, neural networks, and applications across various industries. 
  • Why it matters: Provides a solid foundation for building advanced AI systems and real-world applications. 
Mathematical Concepts for AI
  • Linear algebra, calculus, probability, and statistics. 
  • Why it matters: Essential mathematical concepts to understand and optimize AI models effectively. 
Python for AI Development
  • Python fundamentals and libraries for AI, such as NumPy, Pandas, and TensorFlow. 
  • Why it matters: Python is the primary programming language for AI development, and proficiency is key to building AI models. 
Mastering Machine Learning
  • Supervised and unsupervised machine learning algorithms, model evaluation, and selection. 
  • Why it matters: Provides the necessary tools to create intelligent models and make data-driven decisions. 
Deep Learning
  • Neural networks, optimization algorithms, and hands-on experience in improving AI models. 
  • Why it matters: Deep learning powers much of the modern AI applications, from computer vision to NLP. 
Computer Vision
  • Image processing, object detection, image segmentation, and GANs. 
  • Why it matters: Equip yourself with the skills to develop AI models for visual data, enabling smarter systems.
Natural Language Processing (NLP)
  • Text preprocessing, classification, named entity recognition, and question answering. 
  • Why it matters: NLP techniques enable AI systems to understand and process human language, leading to powerful conversational AI. 
Reinforcement Learning
  • Introduction to reinforcement learning, Q-learning, and policy gradient methods. 
  • Why it matters: Reinforcement learning helps build autonomous systems that learn from experience, with applications in gaming, robotics, and more.
Cloud Computing in AI Development
  • Cloud-based machine learning services and their integration with AI models. 
  • Why it matters: Leverage cloud infrastructure for scalable and efficient AI model deployment. 
Large Language Models (LLMs)
  • Understanding and fine-tuning LLMs for various AI tasks. 
  • Why it matters: LLMs like GPT are revolutionizing fields such as content generation and AI-driven text analysis. 
Cutting-Edge AI Research
  • Explore topics like neuro-symbolic AI, explainable AI (XAI), and federated learning. 
  • Why it matters: Stay ahead of the curve with the latest AI advancements and research trends.
AI Communication and Documentation
  • Communicating AI projects effectively and documenting AI systems with a focus on ethics. 
  • Why it matters: Clear communication and proper documentation ensure the successful implementation and ethical application of AI technologies. 

Industry Opportunities after Certification Completion

Median Salaries
$77,311
With AI+ Developer™
$125,439
% Difference
62

Learner Success Stories

Recommended Certifications

Frequently Asked Questions

Upon completion, you'll receive an AI+ Developer™ certification, showcasing your proficiency in AI. You'll have the skills to tackle real-world AI challenges and implement advanced AI solutions in various domains.
While prior AI knowledge is not mandatory, a fundamental understanding of Python programming and basic math and statistics will help you grasp the advanced concepts covered in this course.
Yes, the course includes various hands-on projects and practical exercises to help you apply theoretical concepts to real-world scenarios, reinforcing your learning through practical experience.
You cannot choose a specialization in this course. However, you will be trained in areas such as Natural Language Processing (NLP), computer vision, and reinforcement learning.
Your progress will be evaluated through a combination of quizzes, hands-on exercises, and a final assessment. These evaluations are designed to test your understanding and application of the material.
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