AI CERTS® certification

AI+ Developer Practitioner™

Formerly known as AI+ Developer™ Get hands-on with the tools and technologies that power the AI ecosystem.

Enquire about this certificationCourse code: AT-310

AI+ Developer Practitioner™ certification badge

Course overview

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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

Included: Instructor-led OR Self-paced course + Official exam + Digital badge
Duration: Instructor-Led: 5 days (live or virtual)Self-Paced: 40 hours of content
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Prerequisites: Basic math, computer science fundamentals, fundamental programming skills

Course focus

Why this certification may be relevant.

Master Key AI Development Skills:

Learn Python, deep learning, advanced concepts, and optimization techniques to build robust AI solutions.

Specialize in Cutting-Edge AI Domains:

Gain expertise in NLP, computer vision, or reinforcement learning, alongside data processing, exploratory analysis, and time series analysis.

Stay Ahead in AI Development:

AI is transforming industries, and organizations seek developers with strong proficiency in deploying AI models to solve real-world problems.

Advance Your Career in AI Development:

With growing demand across tech, finance, and healthcare sectors, this certification positions you as a leader in AI-driven development.

Who it may suit

Check the intended audience against your experience and goals.

Software Developers : Enhance your coding expertise by mastering AI algorithms and deep learning techniques.
Data Enthusiasts : Apply AI-driven data analysis, machine learning models, and deep learning to solve complex problems.
Computer Vision & NLP Researchers : Dive into specialized AI fields, including computer vision and natural language processing.
IT Specialists & System Architects : Integrate AI solutions into existing systems and optimize performance.
Students & Fresh Graduates : Build a strong foundation in AI development and prepare for future opportunities in tech.

Course content

Modules supplied by AI CERTs.

Open each module to review the stated topics.

01Module 1: Foundations of Modern AI for Developers

1.1 Understanding Artificial Intelligence
1.2 Components of an AI Application
1.3 Beginner AI Development Workflow
1.4 AI Development Concepts and Limitations
1.5 Case Study: A Chatbot Prototype That Produced Unreliable Answers
1.6 Use Case: Selecting the Right AI Approach

02Module 2: Python Programming for AI

2.1 Python Foundations
2.2 Python Data Structures and File Handling
2.3 Beginner Software-Development Practices
2.4 Case Study: An Unstructured Python Script Becomes Difficult to Maintain
2.5 Use Case: Automated File Processing Utility

03Module 3: Data Handling and Visualization

3.1 Working with NumPy and Pandas
3.2 Data Cleaning
3.3 Exploratory Data Analysis
3.4 Case Study: Dirty Customer Data Produces Incorrect Sales Insights
3.5 Use Case: Retail Sales Data Preparation

04Module 4: Practical Mathematics and Statistics for AI

4.1 Essential Mathematical Concepts
4.2 Essential Statistics
4.3 Mathematical Reasoning for AI
4.4 Case Study: Average Performance Hides a Major Customer Problem
4.5 Use Case: Similarity-Based Product Recommendation

05Module 5: Machine Learning Fundamentals

5.1 Understanding Machine Learning
5.2 Supervised Machine Learning
5.3 Unsupervised and Other Beginner Methods
5.4 Case Study: Customer Churn Prediction
5.5 Use Case: Delivery-Time Prediction

06Module 6: Model Evaluation and Improvement

6.1 Model Evaluation Metrics
6.2 Improving Model Performance
6.3 Reliable Model Delivery
6.4 Case Study: A High-Accuracy Model Misses the Important Cases
6.5 Use Case: Spam Email Detection

07Module 7: Deep Learning and Computer Vision Basics

7.1 Neural Network Fundamentals
7.2 Beginner Deep Learning with PyTorch
7.3 Computer Vision Foundations
7.4 Case Study: Manufacturing Defect Detection with Transfer Learning
7.5 Use Case: Product Image Classification

08Module 8: Natural Language Processing, Transformers, and LLM Fundamentals

8.1 Text Processing Fundamentals
8.2 Embeddings and Transformers
8.3 Large Language Model Fundamentals
8.4 Case Study: Choosing Between a Text Classifier and an LLM for Routing Support Tickets
8.5 Use Case: Customer Review Analysis

09Module 9: Generative and Multimodal AI Application Development

9.1 Prompt Engineering Foundations
9.2 Building Controlled Generative AI Applications
9.3 Multimodal AI Foundations
9.4 Case Study: Invoice Extraction Produces Incorrect Financial Fields
9.5 Use Case: Multimodal Product Information Assistant

10Module 10: Retrieval-Augmented Generation and Knowledge Assistants

10.1 Retrieval Fundamentals
10.2 Building a Basic RAG Workflow
10.3 RAG Quality and Control
10.4 Case Study: A Policy Assistant Returns an Outdated Rule
10.5 Use Case: Employee Handbook Assistant

11Module 11: Simple AI Agents, APIs, and Deployment

11.1 API Development for AI
11.2 Basic AI Agents and Tool Use
11.3 Beginner Deployment and Operations
11.4 Case Study: An Over-Privileged Agent Performs an Unapproved Action
11.5 Use Case: IT Support Triage Assistant

12Module 12: Responsible AI, Security, Monitoring, and Capstone

12.1 Responsible AI Foundations
12.2 AI Application Security
12.3 Monitoring and Production Readiness
12.4 Case Study: Prompt Injection Causes Confidential Data Exposure
12.5 Use Case: Beginner AI Release Checklist

13Optional Module: AI Agents for Developer

1.1 What Are AI Agents?
1.2 Significance of AI Agents for Developers
1.3 Applications and Trends of AI Agents for Developers
1.4 How Does an AI Agent Work?
1.5 Core Characteristics of AI Agents
1.6 Importance of AI Agents
1.7 Types of AI Agents
1.8 Comparison Table of AI Agents in Ethics

Tools referenced by AI CERTs

Platforms and tools included in the course information.

GitHub Copilot

Lobe

H2O.ai

Snorkel

Before you enrol

This course information is supplied through the AI CERTs catalogue. Kiwi Fern Education will confirm current availability, delivery arrangements, inclusions and fees before enrolment. The programme is not presented as a New Zealand Qualifications Authority qualification.

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