BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Course Overview
Phoenix TS’ 5-day, instructor – led AI+ Engineer training and certification course in Washington, DC Metro, Columbia, MD, or Live Online offers a structured journey through the foundational principles, advanced techniques, and practical applications of Artificial Intelligence (AI). Beginning with the Foundations of AI, participants progress through modules covering AI Architecture, Neural Networks, Large Language Models (LLMs), Generative AI, Natural Language Processing (NLP), and Transfer Learning using Hugging Face. With a focus on hands-on learning, students develop proficiency in crafting sophisticated Graphical User Interfaces (GUIs) tailored for AI solutions and gain insight into AI communication and deployment pipelines. Upon completion, graduates are equipped with a robust understanding of AI concepts and techniques, ready to tackle real-world challenges and contribute effectively to the ever-evolving field of Artificial Intelligence.
As an AI CERTs Silver Tier Partner, Phoenix TS delivers official AI CERTs certification programs and offers self-paced learning options at competitive pricing, making it easier than ever for individuals and teams to stay ahead in today’s AI-driven workplace.
Schedule
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Why the AI+Engineer Certification Matters
- Master AI System Design: Develop the skills to design, implement, and optimize advanced AI systems for real-world applications.
- Build Scalable AI Solutions: Learn how to create scalable AI solutions for industries like technology, finance, and healthcare.
- Tackle Complex Engineering Challenges: This certification ensures you’re equipped to solve challenges in AI architecture, neural networks, and NLP.
- Contribute to AI-Driven Innovations: Certified AI+ Engineers develop cutting-edge AI solutions that enhance business operations and drive future innovations.
- 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™
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
Prerequisites:
- AI+ Data™ or AI+ Developer™ 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
What You’ll Learn
- Foundations of Artificial Intelligence
- Introduction to AI Architecture
- Fundamentals of Neural Networks
- Applications of Neural Networks
- Significance of Large Language Models (LLM)
- Application of Generative AI
- Natural Language Processing
- Transfer Learning with Hugging Face
- Crafting Sophisticated GUIs for AI Solutions
- AI Communication and Deployment Pipeline
Who Should Enroll?
- AI & Software Engineers: Enhance your development skills by mastering AI techniques and designing advanced AI systems.
- Machine Learning Enthusiasts: Apply deep learning, neural networks, and NLP techniques to real-world AI challenges.
- Data Scientists: Strengthen your AI toolkit with engineering techniques for building and deploying scalable AI solutions.
- IT Specialists & System Architects: Integrate AI solutions into existing infrastructures, optimizing performance and scalability.
- 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 Architecture
- Neural Networks
- Large Language Models (LLMs)
- Generative AI
- Natural Language Processing (NLP)
- Transfer Learning using Hugging Face
- AI Deployment Pipelines
Course Outline
Course Overview
Module 1: Foundations of Artificial Intelligence
- Introduction to AI
- Core Concepts and Techniques in AI
- Ethical Considerations
Module 2: Introduction to AI Architecture
- Overview of AI and its Various Applications
- Introduction to AI Architecture
- Understanding the AI Development Lifecycle
- Hands-on: Setting up a Basic AI Environment
Module 3: Fundamentals of Neural Networks
- Basics of Neural Networks
- Activation Functions and Their Role
- Backpropagation and Optimization Algorithms
- Hands-on: Building a Simple Neural Network Using a Deep Learning Framework
Module 4: Applications of Neural Networks
- Introduction to Neural Networks in Image Processing
- Neural Networks for Sequential Data
- Practical Implementation of Neural Networks
Module 5: Significance of Large Language Models (LLM)
- Exploring Large Language Models
- Popular Large Language Models
- Practical Finetuning of Language Models
- Hands-on: Practical Finetuning for Text Classification
Module 6: Application of Generative AI
- Introduction to Generative Adversarial Networks (GANs)
- Applications of Variational Autoencoders (VAEs)
- Generating Realistic Data Using Generative Models
- Hands-on: Implementing Generative Models for Image Synthesis
Module 7: Natural Language Processing
- NLP in Real-world Scenarios
- Attention Mechanisms and Practical Use of Transformers
- In-depth Understanding of BERT for Practical NLP Tasks
- Hands-on: Building Practical NLP Pipelines with Pretrained Models
Module 8: Transfer Learning with Hugging Face
- Overview of Transfer Learning in AI
- Transfer Learning Strategies and Techniques
- Hands-on: Implementing Transfer Learning with Hugging Face Models for Various Tasks
Module 9: Crafting Sophisticated GUIs for AI Solutions
- Overview of GUI-based AI Applications
- Web-based Framework
- Desktop Application Framework
Module 10: AI Communication and Deployment Pipeline
- Communicating AI Results Effectively to Non-Technical Stakeholders
- Building a Deployment Pipeline for AI Models
- Developing Prototypes Based on Client Requirements
- Hands-on: Deployment
Optional Module: AI Agents for Engineering
Frequently Asked Questions
What topics are covered in the AI+ Engineer™ Certification?
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.
Who is the target audience for this certification?
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.
What practical skills will I gain from this course?
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.
What type of learning experience can I expect from this course?
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.
How does this certification benefit my career?
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.
BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Phoenix TS is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints re-garding registered sponsors may be submitted to the National Registry of CPE Sponsors through its web site: www.nasbaregistry.org
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