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

High-Quality Video, E-book & Audiobook
Modules Quizzes
AI Mentor
Access for Tablet & Phone
Certificate of Completion
LABs Practices

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

Exam Blueprint

ModulesPercentage
Foundations of Artificial Intelligence 5
Introduction to AI Architecture 10
Fundamentals of Neural Networks15
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 Face15
Crafting Sophisticated GUIs for AI Solutions10
AI Communication and Deployment Pipeline 7

Self Study Materials Included

Videos
Engaging visual content to enhance understanding and learning experience.
Podcasts
Insightful audio sessions featuring expert discussions and real-world cases.
Audiobooks
Listen and learn anytime with convenient audio-based knowledge sharing.
E-Books
Comprehensive digital guides offering in-depth knowledge and learning support.
Labs
Interactive lab sessions to apply concepts and strengthen technical skills.
Module Wise Quizzes
Interactive assessments to reinforce learning and test conceptual clarity.
Additional Resources
Listen and learn anytime with convenient audio-based knowledge sharing.

Tools You'll Master

TensorFlow
Hugging Face Transformers
Jenkins
TensorFlow Hub

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

Course Overview
  1. Course Introduction Preview
Module 1: Foundations of Artificial Intelligence
  1. 1.1 Introduction to AI Preview
  2. 1.2 Core Concepts and Techniques in AI Preview
  3. 1.3 Ethical Considerations
Module 2: Introduction to AI Architecture
  1. 2.1 Overview of AI and its Various ApplicationsPreview
  2. 2.2 Introduction to AI Architecture Preview
  3. 2.3 Understanding the AI Development Lifecycle Preview
  4. 2.4 Hands-on: Setting up a Basic AI Environment
Module 3: Fundamentals of Neural Networks
  1. 3.1 Basics of Neural Networks Preview
  2. 3.2 Activation Functions and Their Role Preview
  3. 3.3 Backpropagation and Optimization Algorithms
  4. 3.4 Hands-on: Building a Simple Neural Network Using a Deep Learning Framework
Module 4: Applications of Neural Networks
  1. 4.1 Introduction to Neural Networks in Image Processing
  2. 4.2 Neural Networks for Sequential Data
  3. 4.3 Practical Implementation of Neural Networks
Module 5: Significance of Large Language Models (LLM)
  1. 5.1 Exploring Large Language Models
  2. 5.2 Popular Large Language Models
  3. 5.3 Practical Finetuning of Language Models
  4. 5.4 Hands-on: Practical Finetuning for Text Classification
Module 6: Application of Generative AI
  1. 6.1 Introduction to Generative Adversarial Networks (GANs)
  2. 6.2 Applications of Variational Autoencoders (VAEs)
  3. 6.3 Generating Realistic Data Using Generative Models
  4. 6.4 Hands-on: Implementing Generative Models for Image Synthesis
Module 7: Natural Language Processing
  1. 7.1 NLP in Real-world Scenarios
  2. 7.2 Attention Mechanisms and Practical Use of Transformers
  3. 7.3 In-depth Understanding of BERT for Practical NLP Tasks
  4. 7.4 Hands-on: Building Practical NLP Pipelines with Pretrained Models
Module 8: Transfer Learning with Hugging Face
  1. 8.1 Overview of Transfer Learning in AI
  2. 8.2 Transfer Learning Strategies and Techniques
  3. 8.3 Hands-on: Implementing Transfer Learning with Hugging Face Models for Various Tasks
Module 9: Crafting Sophisticated GUIs for AI Solutions
  1. 9.1 Overview of GUI-based AI Applications
  2. 9.2 Web-based Framework
  3. 9.3 Desktop Application Framework
Module 10: AI Communication and Deployment Pipeline
  1. 10.1 Communicating AI Results Effectively to Non-Technical Stakeholders
  2. 10.2 Building a Deployment Pipeline for AI Models
  3. 10.3 Developing Prototypes Based on Client Requirements
  4. 10.4 Hands-on: Deployment
Optional Module: AI Agents for Engineering
  1. 1. Understanding AI Agents
  2. 2. Case Studies
  3. 3. Hands-On Practice with AI Agents

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Industry Opportunities after Certification Completion

Median Salaries
$67,583
With AI+ Engineer™
$134,143
% Difference
98

Trusted Reviews by Our Learners

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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™ 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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