- modules: 12
- Examination: 1
- Examination Time: 50 MCQs, 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.
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 Introduction to AI
- 1.2 Types of Artificial Intelligence
- 1.3 Branches of Artificial Intelligence
- 1.4 Applications and Business Use Cases
- 2.1 Linear Algebra
- 2.2 Calculus
- 2.3 Probability and Statistics
- 2.4 Discrete Mathematics
- 3.1 Python Fundamentals
- 3.2 Python Libraries
- 4.1 Introduction to Machine Learning
- 4.2 Supervised Machine Learning Algorithms
- 4.3 Unsupervised Machine Learning Algorithms
- 4.4 Model Evaluation and Selection
- 5.1 Neural Networks
- 5.2 Convolutional Neural Networks (CNNs)
- 5.3 Recurrent Neural Networks (RNNs)
- 6.1 Image Processing Basics
- 6.2 Object Detection
- 6.3 Image Segmentation
- 6.4 Generative Adversarial Networks (GANs)
- 7.1 Text Preprocessing and Representation
- 7.2 Text Classification
- 7.3 Named Entity Recognition (NER)
- 7.4 Question Answering (QA)
- 8.1 Introduction to Reinforcement Learning
- 8.2 Q-Learning and Deep Q-Networks (DQNs)
- 8.3 Policy Gradient Methods
- 9.1 Cloud Computing for AI
- 9.2 Cloud-Based Machine Learning Services
- 10.1 Understanding LLMs
- 10.2 Text Generation and Translation
- 10.3 Question Answering and Knowledge Extraction
- 11.1 Neuro-Symbolic AI
- 11.2 Explainable AI (XAI)
- 11.3 Federated Learning
- 11.4 Meta-Learning and Few-Shot Learning
- 12.1 Communicating AI Projects
- 12.2 Documenting AI Systems
- 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.