AI+ Developer™

Get hands-on with the tools and technologies that power the AI ecosystem.

  • 12 Modules
  • 1 Examination
  • 50 Multiple Choice Questions, 90 Minutes
  • Passing Score: 70%

About Certification

AI+ Developer™ certification program offers a tailored journey in key AI domains for developers. Master Python, advanced concepts, math, stats, optimization, and deep learning. The curriculum covers data processing, exploratory analysis, and allows specialization in NLP, computer vision, or reinforcement learning. The program includes time series analysis, model explainability, and deployment intricacies. Upon completion, you'll receive a certification, showcasing your AI proficiency for real-world challenges.

Certification Prerequisites

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

Certification Modules

  1. 1.1 Introduction to AI
  2. 1.2 Types of Artificial Intelligence
  3. 1.3 Branches of Artificial Intelligence
  4. 1.4 Applications and Business Use Cases

  1. 2.1 Linear Algebra
  2. 2.2 Calculus
  3. 2.3 Probability and Statistics
  4. 2.4 Discrete Mathematics

  1. 3.1 Python Fundamentals
  2. 3.2 Python Libraries

  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

  1. 5.1 Neural Networks
  2. 5.2 Convolutional Neural Networks (CNNs)
  3. 5.3 Recurrent Neural Networks (RNNs)

  1. 6.1 Image Processing Basics
  2. 6.2 Object Detection
  3. 6.3 Image Segmentation
  4. 6.4 Generative Adversarial Networks (GANs)

  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)

  1. 8.1 Introduction to Reinforcement Learning
  2. 8.2 Q-Learning and Deep Q-Networks (DQNs)
  3. 8.3 Policy Gradient Methods

  1. 9.1 Cloud Computing for AI
  2. 9.2 Cloud-Based Machine Learning Services

  1. 10.1 Understanding LLMs
  2. 10.2 Text Generation and Translation
  3. 10.3 Question Answering and Knowledge Extraction

  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

  1. 12.1 Communicating AI Projects
  2. 12.2 Documenting AI Systems
  3. 12.3 Ethical Considerations

Certification Outcome

This certification program provides a thorough exploration of artificial intelligence's core domains, tailored specifically for developers. It covers everything from fundamental Python mastery to advanced topics, including mathematics, statistics, optimization techniques, and deep learning. Participants delve into data pre-processing, exploratory data analysis, feature engineering, selection, and dimensionality reduction. They can specialize in NLP, computer vision, or reinforcement learning. The program also includes time series analysis, model explainability, and model deployment intricacies. Upon completion, participants receive certification, affirming their expertise in pivotal AI areas, priming them for real-world challenges and innovations.

Market Insight
As artificial intelligence becomes increasingly pervasive across various industries, there is a growing demand for AI developers who possess the skills to harness it's transformative potential. This specialized AI developer certification program has been meticulously crafted to align with the evolving needs of established tech giants and emerging AI startups in this dynamic field.
Value Proposition
Participants in this program will not only gain proficiency in fundamental AI concepts but also acquire advanced technical skills essential for the successful implementation of AI solutions in real-world applications. This certification empowers AI developers with the knowledge and expertise needed to excel in the competitive world of AI development.
Additional Features
Interactive Sessions: Engage in discussions with industry experts and peers. Hands-on Exercises: Practical tasks to apply learned concepts in real-world scenarios. Case Studies: Dive deep into real business challenges and AI-driven solutions. Post-Certification Support: Access to a community of AI experts and enthusiasts for continuous learning and networking.


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