| Category | AI Agent Developer, AI Development, AI System Engineer, AI Technical, All Courses, Available Now, Cloud Architect, Data Engineer, Data Science & AI Specialist, English, Language, Machine Learning Scientist, Quantum Computing Specialist, Robotics Engineer, Software Developer |
|---|---|
| Program Name | AI+ Engineer™ |
| Duration | Instructor-Led:5 days (live or virtual) | Self-Paced:40 hours (5 Days) |
| Prerequisites | AI+ Data™ or AI+ Developer™ course should be completed. Basic understanding of Python programming is mandatory for hands-on exercises and project work. Familiarity with high school-level algebra and basic statistics is required. Understanding basic programming concepts such as variables, functions, loops, and data structures like lists and dictionaries is essential. |
| Exam Format | 50 questions, 70% passing, 90 minutes, online proctored exam |
Students will learn to develop user-friendly AI GUIs. Interface design, usability testing, and AI integration into GUIs will be covered to build intuitive and engaging user experiences.
Learners will gain knowledge of AI solution communication and deployment, including developing and managing deployment pipelines for efficient AI system rollout and maintenance, as well as explaining the value and utility of AI solutions to stakeholders and end-users.
Students will apply AI principles from the course to real-world issues, enhancing their skills in identifying AI methodologies, constructing models, and interpreting results to address complex problems across disciplines.
Learners will build AI-specific project management abilities by engaging with AI project workflows. This involves developing, implementing, and managing AI initiatives, managing resources, schedules, and stakeholder expectations for success.
Design, develop, and optimize AI systems, working on neural networks, deep learning, and NLP to solve complex challenges.
Create scalable AI architectures and integrate AI solutions into various business systems to drive innovation and efficiency.
Develop machine learning models and algorithms, focusing on predictive analytics, deep learning, and data-driven solutions.
Implement AI technologies into existing infrastructures, ensuring seamless integration and scalability of AI solutions.
Lead AI-driven projects, managing timelines, resources, and stakeholder expectations to ensure successful deployment of AI solutions.
The certification covers a wide range of topics including Foundations of AI, AI Architecture, Neural Networks, Large Language Models (LLMs), Generative AI, Natural Language Processing (NLP), and Transfer Learning using Hugging Face.
This certification is ideal for individuals seeking to gain a deep understanding of AI concepts and techniques, whether they are beginners or have some prior knowledge of AI.
Participants will gain hands-on experience in building and deploying AI solutions. Skills include developing neural networks, fine-tuning large language models, implementing generative AI models, and crafting sophisticated GUIs for AI applications. Additionally, participants will learn to navigate AI communication and deployment pipelines.
The course emphasizes hands-on learning, enabling participants to develop practical skills in creating Graphical User Interfaces (GUIs) for AI solutions and understanding AI communication and deployment pipelines.
The AI+ Engineer™ Certification enhances your professional profile by demonstrating proficiency in AI fundamentals and advanced applications. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities in tech, healthcare, finance, and other industries.
70%
50 multiple-choice/multiple-response questions
