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AI+ Engineer™

# AT-330

Innovate Engineering: Unlock the Potential of AI-Driven Solutions

The AI+ Engineer™ certification equips participants with a comprehensive understanding of Artificial Intelligence (AI) principles, advanced engineering techniques, and practical applications. The program covers AI architecture, neural networks, Large Language Models (LLMs), Generative AI, and Natural Language Processing (NLP). It also introduces cutting-edge tools like Transfer Learning using frameworks such as Hugging Face. Learners will develop expertise in designing Graphical User Interfaces (GUIs) for AI systems, managing communication pipelines, and deploying AI applications. With hands-on experience and practical projects, graduates emerge as proficient AI engineers ready to tackle complex industry challenges and contribute to innovation in the ever-evolving AI landscape.

$495.00

What’s included?

One-year subscription (with all updates):

High-Quality Videos and E-Book
AI Mentor for Personalized Guidance
Quizzes, Assessments and Course Resources
Proctored Exam With 1 Free Retake
Exam Study Guide
Hands-on labs

Prerequisites

AI+ Data™ or AI+ Developer™ Certification: Completion is recommended for foundational knowledge.
Python Programming Proficiency: Hands-on experience in Python is essential for project work.
Mathematics Basics: High-school-level algebra and statistics are desirable.
Computer Science Fundamentals: Familiarity with programming concepts like variables, functions, loops, and data structures.

Exam Details

What Will You Learn?

GUI Development for AI Solutions

Design intuitive, user-friendly interfaces for AI applications through interface usability testing and integration techniques.

AI Communication and Deployment Pipelines

Master the processes of developing AI systems, managing their deployment, and communicating their value to stakeholders.

AI Problem-Solving Skills

Apply AI methodologies to solve real-world challenges, interpret results, and enhance problem-solving strategies.

AI-Specific Project Management

Learn to manage AI projects from planning and resource allocation to stakeholder management and delivery.

Certification Modules

Certification Overview

Course Introduction Preview

Module 1: Foundations of Artificial Intelligence

1.1 Introduction to AI
1.2 Core Concepts and Techniques in AI
1.3 Ethical Considerations

Module 2: Introduction to AI Architecture

2.1 Overview of AI and its Various Applications
2.2 Introduction to AI Architecture
2.3 Understanding the AI Development Lifecycle
2.4 Hands-on: Setting up a Basic AI Environment

Module 3: Fundamentals of Neural Networks

3.1 Basics of Neural Networks
3.2 Activation Functions and Their Role
3.3 Backpropagation and Optimization Algorithms
3.4 Hands-on: Building a Simple Neural Network Using a Deep Learning Framework

Module 4: Applications of Neural Networks

4.1 Introduction to Neural Networks in Image Processing
4.2 Neural Networks for Sequential Data
4.3 Practical Implementation of Neural Networks

Module 5: Significance of Large Language Models (LLM)

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

Module 6: Application of Generative AI

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

Module 7: Natural Language Processing

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

Module 8: Transfer Learning with Hugging Face

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

Module 9: Crafting Sophisticated GUIs for AI Solutions

9.1 Overview of GUI-based AI Applications
9.2 Web-based Framework
9.3 Desktop Application Framework

Module 10: AI Communication and Deployment Pipeline

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

Industry Opportunities after Certification Completion

Median Salaries

$67,583

With AI+ Engineer™

$134,143

% Difference

AI Developer

Utilize algorithms to create tailored AI systems for intelligent automation and enhanced operational efficiency.

Technology Engineer

Implement advanced algorithms for machine learning applications, driving innovation in competitive industries.

Infrastructure Architect

Design scalable systems to optimize architecture for AI workflows and robust deployments.

Systems Engineer

Combine hardware and software expertise to develop reliable, high-performing AI systems for emerging technologies.

Learner Success Stories

AI+ Executive™ Instructor Guide Certificate. Today, I am part of the team of #CompuEducación instructors to teach the #AICerts AI+Executive certification course . This 8-hour course is a new standard for business leaders…

Doug F,

Company Owner

AI+ Executive™

As VP Operations, my recent completion of the AI+ Executive exam through AI CERTs was a pivotal step in advancing my AI skill set as we embrace an AI-driven future. This certification not only deepened my understanding of AI’s broad…

Georgia L,

Training Director

AI+ Executive™

Happy to share I’ve completed the AI+ Executive Certification from AI CERTs! This program has sharpened my skills in strategic AI application + implementation, further equipping me to lead AI-driven organizational transformation.

Marc H,

AI+ Executive™

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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.

AI+ Engineer™

# AT-330

Prerequisites

Exam Details

What Will You Learn?

Certification Modules

Industry Opportunities after Certification Completion

Learner Success Stories

Recommended Certifications

AI+ Security Level 1™

AI+ Robotics™

AI+ Security Compliance™

AI+ Government™

AI+ Researcher™

AI+ Ethical Hacker™

AI+ Customer Service™

AI+ Healthcare™

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