The course provided me with a solid understanding of IT service desk operations and troubleshooting techniques. It has improved my ability to handle user issues with confidence and professionalism.
AI+ Engineer Practitioner™
AT-330
Formerly known as AI+ Engineer™ Innovate Engineering: Leverage AI-Driven Smart Solutions
Full AI Stack: Learn AI architecture, LLMs, NLP, and neural networks
Tool Proficiency: Includes Transfer Learning with Hugging Face and GUI design
Deployment Focus: Build real AI systems and manage communication pipelines
Practical Mastery: Gain the skills to engineer scalable AI solutions for innovation
- High-Quality Video, E-book & Audiobook
- Modules Quizzes
- AI Mentor
- Access for Tablet & Phone
- Online Proctored Exam with One Free Retake
- Hands-on Practices
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+ Engineer Practitioner™ 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
AI+ Engineer Practitioner™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Prerequisites
AI+ Data Practitioner™ or AI+ Developer Practitioner™ course should be completed, basic math, computer science fundamentals, Python familiarity
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
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.
Skills You'll Gain
AI ArchitectureNeural NetworksLarge Language Models (LLMs)Generative AINatural Language Processing (NLP)Transfer Learning using Hugging FaceAI Deployment Pipelines
What You'll Learn
- Full AI Stack: Learn AI architecture, LLMs, NLP, and neural networks
- Tool Proficiency: Includes Transfer Learning with Hugging Face and GUI design
- Deployment Focus: Build real AI systems and manage communication pipelines
- Practical Mastery: Gain the skills to engineer scalable AI solutions for innovation
- Course Introduction Preview
- 1.1 Introduction to AI Preview
- 1.2 Core Concepts and Techniques in AI Preview
- 1.3 Ethical Considerations
- 2.1 Overview of AI and its Various ApplicationsPreview
- 2.2 Introduction to AI Architecture Preview
- 2.3 Understanding the AI Development Lifecycle Preview
- 2.4 Hands-on: Setting up a Basic AI Environment
- 3.1 Basics of Neural Networks Preview
- 3.2 Activation Functions and Their Role Preview
- 3.3 Backpropagation and Optimization Algorithms
- 3.4 Hands-on: Building a Simple Neural Network Using a Deep Learning Framework
- 4.1 Introduction to Neural Networks in Image Processing
- 4.2 Neural Networks for Sequential Data
- 4.3 Practical Implementation of Neural Networks
- 5.1 Exploring Large Language Models
- 5.2 Popular Large Language Models
- 5.3 Practical Finetuning of Language Models
- 5.4 Hands-on: Practical Finetuning for Text Classification
- 6.1 Introduction to Generative Adversarial Networks (GANs)
- 6.2 Applications of Variational Autoencoders (VAEs)
- 6.3 Generating Realistic Data Using Generative Models
- 6.4 Hands-on: Implementing Generative Models for Image Synthesis
- 7.1 NLP in Real-world Scenarios
- 7.2 Attention Mechanisms and Practical Use of Transformers
- 7.3 In-depth Understanding of BERT for Practical NLP Tasks
- 7.4 Hands-on: Building Practical NLP Pipelines with Pretrained Models
- 8.1 Overview of Transfer Learning in AI
- 8.2 Transfer Learning Strategies and Techniques
- 8.3 Hands-on: Implementing Transfer Learning with Hugging Face Models for Various Tasks
- 9.1 Overview of GUI-based AI Applications
- 9.2 Web-based Framework
- 9.3 Desktop Application Framework
- 10.1 Communicating AI Results Effectively to Non-Technical Stakeholders
- 10.2 Building a Deployment Pipeline for AI Models
- 10.3 Developing Prototypes Based on Client Requirements
- 10.4 Hands-on: Deployment
- 1. Understanding AI Agents
- 2. Case Studies
- 3. Hands-On Practice with AI Agents
Tools You'll Master
Prerequisites
- AI+ Data Practitioner™ or AI+ Developer Practitioner™ 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 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:
- Foundations of Artificial Intelligence - 5%
- Introduction to AI Architecture - 10%
- Fundamentals of Neural Networks - 15%
- Applications of Neural Networks - 7%
- Significance of Large Language Models (LLM) - 8%
- Application of Generative AI - 8%
- Natural Language Processing - 15%
- Transfer Learning with Hugging Face - 15%
- Crafting Sophisticated GUIs for AI Solutions - 10%
- AI Communication and Deployment Pipeline - 7%
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Instructor-Led (Live Virtual/Classroom)
- 5 days (live or virtual) Self-Paced: 40 hours of content
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- 40 hours of content
- Learn anywhere, anytime, with modular quizzes to track progress
Need More Flexibility?
To help you along your way, we can help you set up a customizable payment plan. Just book a call, we’ll provide you with the details!
Let's Arrange a Call9/10 of our learners achieve their learning objectives after successful completionProcess Advisors
The course gave me a clear understanding of network security concepts and practical exposure. It helped me build confidence in handling real-world security tasks.
My path to cloud architecture had its hurdles, but Fortray was there every step of the way. They provided valuable insights into cloud technologies and architectural design. With their guidance, I turned challenges into opportunities, and today, as a Cloud Architect, I help organizations leverage the cloud for their growth and success.
The path to becoming a Cybersecurity Engineer felt like decrypting an impossible algorithm—until Fortray provided the key. Their mentorship was like a robust IPS, detecting and eliminating my weaknesses while optimizing my strengths. Now, I stand as a protector in the ever-evolving IT landscape, proud to carry their legacy forward.
This course strengthened my full-stack development skills and practical understanding. I am more confident in building and managing complete web applications.
This course improved my understanding of project management methodologies and workflows. I gained practical skills to plan and execute projects effectively.
The course provided valuable hands-on experience in data analysis tools and techniques. It enhanced my ability to extract meaningful insights from data.
The training helped me build strong analytical skills and understand how to work with real-world data science problems effectively.
The course helped me understand automation testing frameworks and best practices. I gained practical experience in writing and executing automated test cases.
Frequently Asked Questions
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 Practitioner™ 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.
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