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AI+ Engineer
Innovate Engineering: Leverage AI-Driven Smart Solutions
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Full AI Stack: Learn AI architecture, LLMs, NLP, and neural networks
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Tool Proficiency: Includes Transfer Learning with Hugging Face and GUI design
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Deployment Focus: Build real AI systems and manage communication pipelines
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Practical Mastery: Gain the skills to engineer scalable AI solutions for innovation
Why This Certification Matters
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Master AI System Design: Develop the skills to design, implement, and optimize advanced AI systems for real-world applications.
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Build Scalable AI Solutions: Learn how to create scalable AI solutions for industries like technology, finance, and healthcare.
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Tackle Complex Engineering Challenges: This certification ensures you’re equipped to solve challenges in AI architecture, neural networks, and NLP.
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Contribute to AI-Driven Innovations: Certified AI+ Engineers develop cutting-edge AI solutions that enhance business operations and drive future innovations.
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Advance Your Career in AI Engineering: As demand for skilled AI engineers rises, this certification offers a competitive advantage in the job market.
At a Glance: Course + Exam Overview
Program Name
Included
Duration
Prerequisites
Exam Format
Delivery
Outcome
AI+ Engineer
Instructor-led OR Self-paced course + Official exam + Digital badge
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Instructor-Led: 5 days (live or virtual)
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Self-Paced: 40 hours of content
AI+ Data™ or AI+ Developer™ course should be completed, basic math, computer science fundamentals, Python familiarity
50 questions, 70% passing, 90 minutes, online proctored exam
Online labs, projects, case studies
Industry-recognized credential + hands-on experience
Who Should Enroll?
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AI & Software Engineers: Enhance your development skills by mastering AI techniques and designing advanced AI systems.
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Machine Learning Enthusiasts: Apply deep learning, neural networks, and NLP techniques to real-world AI challenges.
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Data Scientists: Strengthen your AI toolkit with engineering techniques for building and deploying scalable AI solutions.
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IT Specialists & System Architects: Integrate AI solutions into existing infrastructures, optimizing performance and scalability.
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Students & New Graduates: Develop in-demand AI engineering skills and prepare for a successful career in the rapidly growing AI field.
Job Roles & Industry Outlook
Executive Leader
Oversee AI initiatives, align them with business objectives, and drive innovation across departments using AI technologies.
Chief Officer
Set AI strategy, direct implementation, and ensure alignment with business goals to enhance operations, products, and services.
Executive Director
Guide AI strategy, oversee implementation and foster collaboration across departments to support organizational goals.
Corporate Strategy Leader
Develop AI strategies aligned with corporate goals, identify AI integration opportunities and guide decision-making for businesses.
Industry Growth: Powering Next-Gen Infrastructure with AI-First Engineering
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By 2027, 80% of the engineering workforce will need to upskill due to the rise of generative AI (GenAI) technologies. (Gartner)
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AI adoption is accelerating across industries, creating high demand for professionals with advanced AI skills.
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Companies seek AI+ Engineers to develop cutting-edge solutions for AI-driven automation and decision-making.
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As the demand for AI engineering expertise grows, high-paying job opportunities are expanding globally, particularly for those skilled in AI system design and deployment.
What You'll Learn
Tools You'll Explore
TensorFlow
Hugging Face Transformers
Jenkins
TensorFlow Hub
Prerequisites
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AI+ Data™ or AI+ Developer™ course should be completed.
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Basic understanding of Python programming is mandatory for hands-on exercises and project work.
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Familiarity with high school-level algebra and basic statistics is required.
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Understanding basic programming concepts such as variables, functions, loops, and data structures like lists and dictionaries is essential.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
Exam Blueprint:
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Foundations of Artificial Intelligence - 5%
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Introduction to AI Architecture - 10%
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Fundamentals of Neural Networks - 15%
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Applications of Neural Networks - 7%
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Significance of Large Language Models (LLM) - 8%
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Application of Generative AI - 8%
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Natural Language Processing - 15%
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Transfer Learning with Hugging Face - 15%
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Crafting Sophisticated GUIs for AI Solutions - 10%
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AI Communication and Deployment Pipeline - 7%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates):
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High-Quality Videos, E-book (PDF & Audio), and Podcasts
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AI Mentor for Personalized Guidance
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Quizzes, Assessments, and Course Resources
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Online Proctored Exam with One Free Retake
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Comprehensive Exam Study Guide
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Access for Tablet & Phone
Instructor-Led (Live Virtual/Classroom)
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5 days of intensive training with live demos
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Real-time Q&A, peer collaboration, and hands-on labs
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Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
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~40 hours of on-demand video lessons, e-book, podcasts, and interactive labs
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Learn anywhere, anytime, with modular quizzes to track progress
Frequently Asked Questions