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    • AI+ Developer™

    • Core AI Foundations: Covers Python, deep learning, data processing, and algorithm design
    • Hands-on Projects: Focus on NLP, computer vision, and reinforcement learning
    • Advanced Modules: Includes time series, model explainability, and cloud deployment
    • Industry-Ready Skills: Prepares learners to design and deploy complex AI systems
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    AI+ Developer™
    Price: USD $450.00

    At a Glance: Course + Exam Overview

    Category AI Development
    AI Technical
    Program Name AI+ Developer™
    Duration
    • Instructor-Led: 5 Days
    • Self-Paced: 30 hours of content
    Prerequisites
      • Basic math, including familiarity with high school-level algebra and basic statistics, is desirable. 
      • Understanding basic programming concepts such as variables, functions, loops, and data structures like lists and dictionaries is essential. 
      • A fundamental knowledge of programming skills is required. 
    Exam Format 50 questions, 70% passing, 90 Minutes

    What You'll Learn

    • Python Programming Proficiency
      Students will gain a solid foundation in Python programming, a crucial skill for implementing AI algorithms, processing data, and building AI applications effectively.
    • Deep Learning Techniques
      Learners will master machine learning and deep learning techniques to address challenges in classification, regression, image recognition, and natural language processing.
    • Cloud Computing in AI Development
      Students will get hands-on experience in cloud-based AI application development and learn how to use AWS, Azure, and Google Cloud for scalable AI systems.
    • Project Management in AI
      Participations will master the skills necessary to manage AI projects effectively, from initiation to completion, including planning, resource allocation, risk management, and stakeholder communication.

    Certification Modules

    Course Overview

    1. Course IntroductionPreview

    Module 1: Foundations of Artificial Intelligence

    1. 1.1 Introduction to AI Preview
    2. 1.2 Types of Artificial Intelligence Preview
    3. 1.3 Branches of Artificial Intelligence
    4. 1.4 Applications and Business Use Cases

    Module 2: Mathematical Concepts for AI

    1. 2.1 Linear Algebra Preview
    2. 2.2 Calculus Preview
    3. 2.3 Probability and Statistics Preview
    4. 2.4 Discrete Mathematics

    Module 3: Python for Developer

    1. 3.1 Python Fundamentals Preview
    2. 3.2 Python Libraries

    Module 4: Mastering Machine Learning

    1. 4.1 Introduction to Machine Learning
    2. 4.2 Supervised Machine Learning Algorithms
    3. 4.3 Unsupervised Machine Learning Algorithms
    4. 4.4 Model Evaluation and Selection

    Module 5: Deep Learning

    1. 5.1 Neural Networks
    2. 5.2 Improving Model Performance
    3. 5.3 Hands-on: Evaluating and Optimizing AI Models

    Module 6: Computer Vision

    1. 6.1 Image Processing Basics
    2. 6.2 Object Detection
    3. 6.3 Image Segmentation
    4. 6.4 Generative Adversarial Networks (GANs)

    Module 7: Natural Language Processing

    1. 7.1 Text Preprocessing and Representation
    2. 7.2 Text Classification
    3. 7.3 Named Entity Recognition (NER)
    4. 7.4 Question Answering (QA)

    Module 8: Reinforcement Learning

    1. 8.1 Introduction to Reinforcement Learning
    2. 8.2 Q-Learning and Deep Q-Networks (DQNs)
    3. 8.3 Policy Gradient Methods

    Module 9: Cloud Computing in AI Development

    1. 9.1 Cloud Computing for AI
    2. 9.2 Cloud-Based Machine Learning Services

    Module 10: Large Language Models

    1. 10.1 Understanding LLMs
    2. 10.2 Text Generation and Translation
    3. 10.3 Question Answering and Knowledge Extraction

    Module 11: Cutting-Edge AI Research

    1. 11.1 Neuro-Symbolic AI
    2. 11.2 Explainable AI (XAI)
    3. 11.3 Federated Learning
    4. 11.4 Meta-Learning and Few-Shot Learning

    Module 12: AI Communication and Documentation

    1. 12.1 Communicating AI Projects
    2. 12.2 Documenting AI Systems
    3. 12.3 Ethical Considerations

    Optional Module: AI Agents for Developers

    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 Machine Learning Developer
      AI Machine Learning Developer
      Design, implement, and optimize algorithms and models to enable systems to learn from data and make predictions or decisions.
    • AI Solutions Architect
      AI Solutions Architect
      Design and implement AI systems that integrate seamlessly with existing infrastructure to address business needs effectively and enhance system capabilities.
    • AI Application Developer
      AI Application Developer
      Build, design, and maintain AI-driven applications that solve real-world problems, integrating AI technologies for enhanced functionality.
    • AI System Programmers
      AI System Programmers
      Develop and maintain AI systems, including programming algorithms and software components that enable intelligent behavior in machines and applications.

    Frequently Asked Questions

    Upon completion, you will receive an AI+ Developer™ certification, showcasing your proficiency in AI. You'll have the skills to tackle real-world AI challenges and implement advanced AI solutions in various domains.

    While prior AI knowledge is not mandatory, a fundamental understanding of Python programming and basic math and statistics will help you grasp the advanced concepts covered in this course.

    Yes, the course includes various hands-on projects and practical exercises to help you apply theoretical concepts to real-world scenarios, reinforcing your learning through practical experience.

    You cannot choose a specialization in this course. However, you will be trained in areas such as Natural Language Processing (NLP), computer vision, and reinforcement learning.

    Your progress will be evaluated through a combination of quizzes, hands-on exercises, and a final assessment. These evaluations are designed to test your understanding and application of the material.

    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 (AI) 5%
    Mathematical Concepts for AI 5%
    Python for AI Development 10%
    Mastering Machine Learning 15%
    Deep Learning 10%
    Computer Vision 10%
    Natural Language Processing (NLP) 15%
    Reinforcement Learning 5%
    Cloud Computing in AI Development 10%
    Large Language Models (LLMs) 5%
    Cutting-Edge AI Research 5%
    AI Communication and Documentation 5%
    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