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#TechSkillsDay

Speakers: - Angie Jones (Vice President of Global Developer Relations, TBD @ Block) - Simon Allardice (Q&A Moderator, Creative Director & Principal Author, Pluralsight)

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Speakers: - Angie Jones (Vice President of Global Developer Relations, TBD @ Block) - Simon Allardice (Q&A Moderator, Creative Director & Principal Author, Pluralsight)

Major advances have been made in developing applications that utilize some form of AI, and software developers are now using tools such as GitHub Copilot and ChatGPT to help them code their projects. However, there's not nearly as much consideration given to how to test these applications. Angie will share her experiences with testing today's cutting-edge, innovative applications that utilize AI and the challenges of ensuring that they actually work the way we intend them to.

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What's inside

Syllabus

The reality of developing an artificial world (plus Q&A with Angie Jones)

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores rapidly-developing AI technologies that are becoming standard in software development
Taught by Angie Jones, Vice President of Global Developer Relations, TBD @ Block who has extensive experience in testing innovative AI applications
Examines challenges of testing AI applications, which is highly relevant to developers working with AI

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in The Reality of Developing an Artificial World (plus Q&A with Angie Jones) with these activities:
Gather course materials
Acquiring and organizing the necessary course materials will prepare you to fully engage with the course content.
Show steps
  • Review the course syllabus and identify required materials.
  • Acquire textbooks, online resources, and any necessary software.
  • Create a dedicated study space and organize materials for easy access.
Review software testing fundamentals
Refreshing your knowledge of software testing concepts will provide a stronger foundation for understanding AI testing.
Browse courses on Software Testing
Show steps
  • Review notes or textbooks on general software testing principles.
  • Complete practice questions or exercises on software testing.
Attend a Local Testing Meetup
Connect with professionals in the testing field and gain insights into current industry trends and best practices.
Browse courses on Networking
Show steps
  • Identify local testing meetups or conferences
  • Register and attend the event
  • Network with other attendees and speakers
  • Stay informed about upcoming events
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Complete online tutorials on AI testing
Structured tutorials will provide a solid foundation in AI testing principles and practices.
Browse courses on AI Development
Show steps
  • Identify reputable online resources offering AI testing tutorials.
  • Select tutorials that cover the core concepts and techniques.
  • Follow the tutorials step-by-step, practicing and implementing the concepts.
Explore ChatGPT for Test Case Generation
Expand your knowledge of cutting-edge AI tools by exploring ChatGPT for generating test cases.
Browse courses on ChatGPT
Show steps
  • Familiarize yourself with ChatGPT's capabilities
  • Provide ChatGPT with clear and specific requirements
  • Evaluate the generated test cases for quality and relevance
Practice testing AI applications
Hands-on practice will enhance your understanding of AI testing concepts and techniques.
Browse courses on AI Development
Show steps
  • Set up a testing environment for your AI application.
  • Design and execute test cases to evaluate different aspects of the application.
  • Analyze test results and identify areas for improvement.
Code Review with AI Assistance
Enhance your code quality and learn from AI suggestions by conducting code reviews with AI assistance.
Browse courses on AI-Assisted Coding
Show steps
  • Choose a codebase or project
  • Select an AI-powered code review tool
  • Run the code review and analyze the results
  • Implement recommended improvements
Attend a seminar on AI testing
Engaging with experts in the field will broaden your perspectives and enhance your learning.
Show steps
  • Research upcoming seminars on AI testing.
  • Register for the seminar and attend the session.
  • Actively participate in discussions and take notes.
Participate in a Hands-on Testing Workshop
Enhance your practical skills and learn from experts by participating in a hands-on testing workshop.
Show steps
  • Research and identify relevant workshops
  • Register and attend the workshop
  • Actively participate in exercises and discussions
  • Apply the knowledge gained to your own projects
Participate in an AI hackathon
Practical application of AI testing skills in a competitive environment will foster deeper understanding.
Browse courses on AI Development
Show steps
  • Find an AI hackathon that aligns with your interests.
  • Form a team or collaborate with others to develop an AI solution.
  • Work on the project, applying testing best practices.
  • Submit your solution and present it to the judges.
Implement a Test Case
Reinforce your understanding of testing best practices and gain hands-on experience in implementing test cases.
Browse courses on Testing
Show steps
  • Select a codebase or project
  • Identify the functionality to be tested
  • Design and write test cases
  • Execute and evaluate test results
Design an AI-Powered Testing Framework
Deepen your understanding of AI in testing by designing and implementing an AI-powered testing framework.
Browse courses on Testing Framework
Show steps
  • Research and explore existing AI-powered testing tools
  • Design the architecture and workflow of your framework
  • Develop and implement the framework using appropriate technologies
  • Test and evaluate the framework's effectiveness

Career center

Learners who complete The Reality of Developing an Artificial World (plus Q&A with Angie Jones) will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers build and maintain systems that can learn from data. This course can help Machine Learning Engineers understand the challenges of testing AI-powered applications and ensure that these applications work as intended.
Data Scientist
Data Scientists use data to solve business problems. This course can help Data Scientists understand the challenges of testing AI-powered applications and ensure that these applications work as intended.
Software Developer
Software Developers design, build, and maintain software applications. This course can help Software Developers understand the challenges of testing AI-powered applications and ensure that these applications work as intended.
AI Researcher
AI Researchers develop new AI algorithms and techniques. This course can help AI Researchers understand the challenges of testing AI-powered applications and ensure that these applications work as intended.
Cloud Architect
Cloud Architects design and manage cloud computing solutions. This course can help Cloud Architects understand the challenges of testing AI-powered applications and ensure that these applications are deployed and managed in the cloud.
Project Manager
Project Managers manage the development and launch of software applications. This course can help Project Managers understand the challenges of testing AI-powered applications and ensure that these applications are delivered on time and within budget.
Technical Writer
Technical Writers create documentation for software applications. This course can help Technical Writers understand the challenges of testing AI-powered applications and ensure that documentation is accurate and easy to understand.
UX Designer
UX Designers design the user experience for software applications. This course can help UX Designers understand the challenges of testing AI-powered applications and ensure that these applications are easy to use and meet the needs of users.
Security Analyst
Security Analysts protect software applications from security threats. This course can help Security Analysts understand the challenges of testing AI-powered applications and ensure that these applications are secure from attacks.
Quality Assurance Analyst
Quality Assurance Analysts test software applications to ensure that they meet the requirements of users. This course can help Quality Assurance Analysts understand the challenges of testing AI-powered applications and ensure that these applications work as intended.
Salesforce Developer
Salesforce Developers build and maintain Salesforce applications. This course can help Salesforce Developers understand the challenges of testing AI-powered applications and ensure that these applications work as intended.
DevOps Engineer
DevOps Engineers manage the development and operation of software applications. This course can help DevOps Engineers understand the challenges of testing AI-powered applications and ensure that these applications are deployed and maintained efficiently.
Business Analyst
Business Analysts help businesses understand their needs and develop solutions to meet those needs. This course can help Business Analysts understand the challenges of testing AI-powered applications and ensure that these applications meet the needs of businesses.
Data Analyst
Data Analysts analyze data to help businesses make better decisions. This course can help Data Analysts understand the challenges of testing AI-powered applications and ensure that these applications provide accurate insights.
Product Manager
Product Managers manage the development and launch of new products. This course can help Product Managers understand the challenges of testing AI-powered applications and ensure that these applications meet the needs of users.

Reading list

We've selected 18 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in The Reality of Developing an Artificial World (plus Q&A with Angie Jones).
A comprehensive textbook on deep learning, covering the latest advancements and techniques in the field. A valuable reference for those interested in developing AI applications.
A comprehensive textbook on statistical learning, covering a wide range of techniques and applications. Provides a solid foundation in the mathematical and statistical principles underlying AI.
A comprehensive textbook on machine learning from a probabilistic perspective. Provides a strong theoretical foundation for understanding AI algorithms.
A classic textbook on reinforcement learning, covering the fundamental principles and algorithms. Provides a solid foundation for understanding how AI systems can learn to make decisions in complex environments.
A comprehensive textbook on pattern recognition and machine learning, covering a wide range of topics. Provides a strong theoretical foundation for understanding AI algorithms.
A thought-provoking exploration of the potential risks and benefits of AI. Provides a good overview for those interested in the broader societal implications of AI.
Provides a practical guide to deep learning using Python. It covers the fundamental concepts, algorithms, and applications of deep learning, and valuable resource for students and professionals who want to gain a deeper understanding of the field.
A thought-provoking exploration of the potential future of humanity in the age of AI. Provides a good overview for those interested in the broader societal implications of AI.
An accessible overview of the potential benefits and risks of AI. Provides a good overview for those interested in the broader societal implications of AI.
Provides a practical guide to machine learning. It covers the fundamental concepts, algorithms, and applications of machine learning, and valuable resource for students and professionals who want to gain a deeper understanding of the field.
Provides a gentle introduction to machine learning. It covers the fundamental concepts, algorithms, and applications of machine learning, and valuable resource for students and professionals who want to gain a deeper understanding of the field.
Provides a gentle introduction to machine learning. It covers the fundamental concepts, algorithms, and applications of machine learning, and valuable resource for students and professionals who want to gain a deeper understanding of the field.
Provides a practical guide to machine learning. It covers the fundamental concepts, algorithms, and applications of machine learning, and valuable resource for students and professionals who want to gain a deeper understanding of the field.

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