Masterclass Testing Machine Learning (AI) Models
What you'll learn
- Understand how AI is working
- Understand basic software testing and how to apply it to Artificial Intelligence Models
- Understand how Machine Learning Models are tested compared to traditional software
- Understand the Ethics behind Artificial Intelligence (AI) and how to validate biases in Large Language Models ( LLMs)
- Understand how to test reasoning abilities of AI
- Gain knowledge of reasoning types and how to validate Foundation AI Models against different logic and reasoning Types
- Gain knowledge on what is Natural Language Processing, and what tools can be used to test for it in a Machine Learning Model
- See how to benchmark AI against models "HellaSWAG, MMLU, GLUE, BLEU, Humaneval"
- Importance of test data and how model drifting degrades Large Language Model Performance
- See how chatbots can be tested with real Chatgpt examples
- Demo on testing Chat GPT with automated Tools
- Understand Adversial Testing techniques - Gain knowhow on how to perform attacks on Artificial Intelligence Models
- Understand the common and traditional metrcs what are used in Machine Learning field, such as F1 Score, Perplexity Recall and Accuracy
- Understand K- Folding Data techniques
Requirements
- basic experience with software testing
- basic coding experience ( but not needed)
- optional - GPT model 4 subscription (but not needed)
- desire to learn the hottest skill on the market
- Basic programming in python
- VS Code, A mac/pc, OPEN AI API Key - not mandatory but desirable
Description
Welcome to "Testing AI: Foundation Models, LLMs, Chatbots & More," your comprehensive guide to understanding the fundamentals of testing advanced AI systems. Whether you're a developer, a data scientist, or simply an AI enthusiast, this course will equip you with the knowledge and skills necessary to assess and improve the reliability, performance, and safety of AI technologies.
What You Will Learn:
Introduction to AI Testing: Understand the importance of testing AI systems, including ethical considerations and the potential impacts of AI failures.
Testing Basics: Learn about different types of testing methodologies like unit testing, integration testing, and system testing as applied to AI.
Special Focus on Foundation Models and LLMs: Dive deep into the challenges and techniques for testing large language models and foundational AI systems that are reshaping numerous industries.
Chatbot Testing: Explore the unique aspects of testing conversational AI, ensuring they respond accurately and appropriately in varied scenarios.
AI System Evaluations: Learn how to design and implement effective testing regimes for different AI-based systems, using both manual and automated tools.
K - Folding of Data: Understand how to split all your data into : Training, Evaluation and testing data. Get more out of your data by splitting and training it on the same data, but with different validation subsets each time, ensuring that your model learns from multiple perspectives. This technique helps improve generalization, reduces overfitting, and provides a more reliable estimate of model performance.
Case Studies: Gain insights from real-world scenarios that highlight common pitfalls and best practices in AI testing.
Ethical AI: understand the risk with AI and the ethics behind AI. How can and should you test for this
Benchmarking: Understand how to test the AI against some common benchmarking models such as: BLUE, HellaSWAG, MMLU, HumanEval and other.
Testing ChatGPT / Chatbots with the help of an API and integration this into MLOPS chain.
Adversarial AI: understand how to test for robustness in AI Models
Who This Course Is For:
This course is ideal for anyone looking to gain a solid grounding in the techniques and practices essential for testing AI systems. Whether you’re starting a career in AI, looking to enhance your professional skills, or interested in the mechanisms behind AI system reliability, this course has valuable insights for you.
Course Features:
Engaging video lectures
Practical assignments and hands-on projects
Quizzes and exams to test your knowledge
Access to a community forum for discussion and collaboration
Lifetime access to course materials
Enroll now to start mastering the crucial skill of testing AI systems and ensure you’re prepared to contribute to the development of safe and reliable AI technologies!
Who this course is for:
- Citizen Developer
- Software testers
- quality engineers
- Engineering Directors
Instructor
Hi there, I'm Dan, and I have a genuine passion for software engineering and built-in quality.
Over my 20-year career, I've witnessed the rise and fall of various technologies, experiencing the good, the bad, and the challenges of building high-quality products. I've spent most of my career in the quality engineering space, with occasional roles such as software developer and application architect, where I've had the opportunity to explain complex topics to a less technical audience.
Even today, as an executive at a technology company, my passion remains unwavering for quality engineering, and more precisely, for spreading the word to all engineering teams on how to conduct testing effectively in modern times.
I have led more than 300 talented engineers and have personally overseen their career growth. I truly believe in empowering people and helping them to develop; this belief is also why I have decided to teach. Regarding projects, I have completed more than 100 projects across all major industries.
I am certified in all relevant quality engineering accreditations and practice what I preach. I constantly learn and explore new technologies