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AI Careers & Workforce Development

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
Price
NZ $1468.89

All prices are in NZD, ex GST (15%).

At a Glance: Course + Exam Overview

Category AI Careers & Workforce Development Program Name: AI+ Developer™
Exam Format 50 questions, 70% passing, 90 Minutes Duration:
  • Instructor-Led: 5 Days
  • Self-Paced: 40 hours of content

🤝 You’re never on your own — Parasol Concierge Support provides integration guidance and expert VA assistance so you can focus on mastering skills while we handle the setup details.

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

  1. Course IntroductionPreview

  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

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

  1. 3.1 Python Fundamentals Preview
  2. 3.2 Python Libraries

  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

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

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

  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)

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

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

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

  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

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

  1. 1. Understanding AI Agents
  2. 2. Case Studies
  3. 3. Hands-On Practice with AI Agents

Industry opportunities

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

    Design and implement AI systems that integrate seamlessly with existing infrastructure to address business needs effectively and enhance system capabilities.

AI Application Developer

    Build, design, and maintain AI-driven applications that solve real-world problems, integrating AI technologies for enhanced functionality.

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

  • 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 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%

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

Instructor-Led Course

🚀 Learn directly from certified AI trainers in live, interactive sessions. Get real-time guidance, practical exercises, and the accountability of a structured classroom experience. Perfect for professionals who want expert support and a clear path to certification.

✨ At Parasol Virtual, we go beyond certification. Our team supports your learning journey with guidance, resources, and local assistance to ensure your success. You’re not learning alone — you’re part of a global community with local support.

Request Virtual Training

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

Self-Paced Course

🌐 Study anytime, anywhere with 24/7 access to course materials, practice tests, and resources. Move at your own speed while still working towards globally recognized certification. Designed for busy learners who value flexibility without compromising quality.

✨ At Parasol Virtual, we go beyond certification. Our team supports your learning journey with guidance, resources, and local assistance to ensure your success. You’re not learning alone — you’re part of a global community with local support.

Purchase Self-Paced Course

TECHNOLOGIES USED

GitHub Copilot
GitHub Copilot
Lobe
Lobe
H2O.ai
H2O.ai
Snorkel
Snorkel