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AT-310
AI+ Developer Practitioner™
Formerly known as AI+ Developer™
Get hands-on with the tools and technologies that power the AI ecosystem.
Get hands-on with the tools and technologies that power the AI ecosystem.
AI Agent DeveloperAI DevelopmentAI System EngineerAI Technical
Enquire about this certificationAt a glance
What is included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Recommended background
Basic math, computer science fundamentals, fundamental programming skills
Examination
50 questions, 70% passing, 90 minutes, online proctored exam
About this certification
- 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
Curriculum
Course Overview+
- Course IntroductionPreview
Module 1: Foundations of Artificial Intelligence+
Module 2: Mathematical Concepts for AI+
Module 3: Python for Developer +
- 3.1 Python Fundamentals Preview
- 3.2 Python Libraries
Module 4: Mastering Machine Learning+
- 4.1 Introduction to Machine Learning
- 4.2 Supervised Machine Learning Algorithms
- 4.3 Unsupervised Machine Learning Algorithms
- 4.4 Model Evaluation and Selection
Module 5: Deep Learning+
- 5.1 Neural Networks
- 5.2 Improving Model Performance
- 5.3 Hands-on: Evaluating and Optimizing AI Models
Module 6: Computer Vision+
- 6.1 Image Processing Basics
- 6.2 Object Detection
- 6.3 Image Segmentation
- 6.4 Generative Adversarial Networks (GANs)
Module 7: Natural Language Processing+
- 7.1 Text Preprocessing and Representation
- 7.2 Text Classification
- 7.3 Named Entity Recognition (NER)
- 7.4 Question Answering (QA)
Module 8: Reinforcement Learning+
- 8.1 Introduction to Reinforcement Learning
- 8.2 Q-Learning and Deep Q-Networks (DQNs)
- 8.3 Policy Gradient Methods
Module 9: Cloud Computing in AI Development+
- 9.1 Cloud Computing for AI
- 9.2 Cloud-Based Machine Learning Services
Module 10: Large Language Models+
- 10.1 Understanding LLMs
- 10.2 Text Generation and Translation
- 10.3 Question Answering and Knowledge Extraction
Module 11: Cutting-Edge AI Research+
- 11.1 Neuro-Symbolic AI
- 11.2 Explainable AI (XAI)
- 11.3 Federated Learning
- 11.4 Meta-Learning and Few-Shot Learning
Module 12: AI Communication and Documentation+
- 12.1 Communicating AI Projects
- 12.2 Documenting AI Systems
- 12.3 Ethical Considerations
Optional Module: AI Agents for Developers+
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Who should enrol
Software Developers: Enhance your coding expertise by mastering AI algorithms and deep learning techniques.
Data Enthusiasts: Apply AI-driven data analysis, machine learning models, and deep learning to solve complex problems.
Computer Vision & NLP Researchers: Dive into specialized AI fields, including computer vision and natural language processing.
IT Specialists & System Architects: Integrate AI solutions into existing systems and optimize performance.
Students & Fresh Graduates: Build a strong foundation in AI development and prepare for future opportunities in tech.
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