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    • AI+ Engineer™

    • 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
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    AI+ Engineer™
    Price: USD $450.00

    At a Glance: Course + Exam Overview

    Category AI Development
    AI Technical
    Program Name AI+ Engineer™
    Duration
    • Instructor-Led: 5 Days
    • Self-Paced: 40 hours of content
    Prerequisites
      • AI+ Data™  or AI+ Developer™ 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 Format 50 questions, 70% passing, 90 Minutes

    What You'll Learn

    • GUI Develop for AI Solutions
      Students will learn to develop user-friendly AI GUIs. Interface design, usability testing, and AI integration into GUIs will be covered to build intuitive and engaging user experiences.
    • AI Communication and Deployment Pipeline
      Learners will gain knowledge of AI solution communication and deployment, including developing and managing deployment pipelines for efficient AI system rollout and maintenance, as well as explaining the value and utility of AI solutions to stakeholders and end-users.
    • AI Problem-Solving
      Students will apply AI principles from the course to real-world issues, enhancing their skills in identifying AI methodologies, constructing models, and interpreting results to address complex problems across disciplines.
    • AI-Specific Project Management
      Learners will build AI-specific project management abilities by engaging with AI project workflows. This involves developing, implementing, and managing AI initiatives, managing resources, schedules, and stakeholder expectations for success.

    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

    Finish the course and get certified

    Certificate 1

    Industry Opportunities

    • AI Engineer
      AI Engineer
      Design, develop, and optimize AI systems, working on neural networks, deep learning, and NLP to solve complex challenges.
    • AI Solutions Architect
      AI Solutions Architect
      Create scalable AI architectures and integrate AI solutions into various business systems to drive innovation and efficiency.
    • Machine Learning Engineer
      Machine Learning Engineer
      Develop machine learning models and algorithms, focusing on predictive analytics, deep learning, and data-driven solutions.
    • AI Systems Integrator
      AI Systems Integrator
      Implement AI technologies into existing infrastructures, ensuring seamless integration and scalability of AI solutions.
    • AI Project Manager
      AI Project Manager
      Lead AI-driven projects, managing timelines, resources, and stakeholder expectations to ensure successful deployment of AI solutions.

    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.

    Prerequisites

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    Exam Details

    Duration

    90 Minutes

    Passing Score

    70%

    Format

    50 multiple-choice/multiple-response questions

    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%
    Course Price: USD $450.00
    Self-Paced Online
    • ~30 hours of on-demand video lessons, e-book, podcasts, and interactive labs
    • Learn anywhere, anytime, with modular quizzes to track progress
    Purchase Self-Paced Course
    Instructor-Led (Live Virtual/Classroom)
    • 5 days of intensive training with live demos
    • Real-time Q&A, peer collaboration, and hands-on labs
    • Led by AI Certified Trainers and delivered through Authorized Training Partners