5 Hours
Course Description
In the rapidly evolving world of technology, the application of AI in software testing and QA processes is not just an advantage—it’s becoming essential. This course provides a comprehensive journey through the integration of AI into software testing, promising to equip you with the knowledge and skills necessary to excel in this innovative domain.
Why is this course relevant today? In an era where digital products and services are increasingly complex, the demand for superior quality and reliability has never been higher. Traditional QA methods alone no longer suffice; AI-driven approaches are essential for keeping pace with rapid development cycles, ever-expanding codebases, and the growing complexity of user needs. Learning to harness AI in testing and quality assurance allows teams to predict and prevent potential failures, improve test coverage and efficiency, and ultimately deliver products that better meet customer expectations.
Embark on a journey that begins with an exploration of the basic principles of AI in testing applications, moving all the way through to the intricacies of AI-driven test case generation, defect detection, predictive analytics, performance testing, and more. You’ll dive deep into core technologies powering AI in software testing, understanding not just how they work, but how they can be applied to real-world challenges.
One of the unique values this course offers is its practical approach to learning. Whether you are a complete beginner or a seasoned professional looking to deepen your knowledge, this course is designed to cater to various levels of expertise. For newcomers, this course provides a solid foundation and build up to more complex concepts, ensuring you never feel lost. For experienced professionals, this course offers insights into advanced techniques and the latest innovations, facilitating a deeper understanding and practical application of AI in QA.
Throughout the course, you’ll encounter real-life case studies that highlight the challenges and solutions in AI-driven test case generation, defect management, and predictive analytics. These examples not only provide context but also inspire ideas for application in your projects. By the end of this journey, you’ll be equipped with a comprehensive understanding of AI’s capabilities and limitations in testing, ethical considerations in AI testing tools, improving user experience quality, and the role of AI in Agile and DevOps.
But the value of this course extends beyond its immediate curriculum. This course is not just about learning new tools or techniques—it’s about fostering a mindset geared towards innovation, quality, and efficiency.
Moreover, this holistic approach ensures that you’re not just prepared to work with AI in software testing and QA but are also ready to lead the charge in its implementation.
In conclusion, this course represents a comprehensive, up-to-date, and practical guide to understanding and applying AI in software testing and QA. With hands-on projects and a focus on both foundational principles and cutting-edge techniques, you’re not just enrolling in a course—you’re preparing to be at the forefront of an exciting field. Dive in and transform the future of software quality assurance with AI.
Learning objectives
- Define AI’s role in software testing.
- Describe the evolution from manual to AI-driven testing.
- Explain basic AI principles in testing applications.
- Identify core technologies in AI software testing.
- Discuss AI capabilities and limitations in testing.
- Outline the pillars of quality assurance in software development.
- Describe the importance of automated testing.
- Explain machine learning’s role in QA.
- Identify tools for modern QA professionals.
- Differentiate between AI-enabled and traditional QA.
- Generate test cases using AI principles.
- Improve test coverage with AI-based cases.
- Analyze effectiveness of AI-generated test scenarios.
- Identify challenges in AI test case generation.
- Use AI to detect software defects efficiently.
- Integrate AI in bug tracking and management.
- Apply predictive analytics in software testing.
- Assess quality standards in development with AI.
- Utilize AI for performance test script creation.
- Enhance user experience quality with AI techniques.
Topics covered
Click “AI and the future of software testing and quality assurance-Download” to read the topics covered.
Course Duration:
This course may take up to 5 hours to be completed. However, actual study time differs as each learner uses their own training pace.
Course pre-requisites
There are no requirements or pre-requisites for this course, but the items listed below are a guide to useful background knowledge which will increase the value and benefits of this course:
- Basic understanding of software development processes and methodologies.
- Familiarity with the concepts of software testing and quality assurance.
- An introductory knowledge of artificial intelligence and machine learning principles.
The course is addressed to:
- QA Engineers seeking to enhance their testing strategies with modern AI tools.
- Software Developers interested in integrating AI into their testing and development process to improve efficiency and accuracy.
- Project Managers looking for innovative ways to boost project quality and mitigate risks using AI-driven QA techniques.
- Test Automation Specialists aiming to expand their skills in AI-driven test case generation and defect detection.
- IT Managers and CTOs exploring advanced technologies to elevate software quality and user experience in their products.
- Data Scientists in the software industry keen on applying their skills to predictive analytics and machine learning within QA processes.
Training Method
The course is offered fully online using a self-paced approach. The learning units consist of videos. Learners may start, stop and resume their training at any time.
At the end of the course, participants take a Quiz to complete the course and earn a Certificate of Completion once the Quiz has been passed successfully.
Registration and Access
To register to this course, click on the Take this course button to pay online and receive your access instantly. If you are purchasing this course on behalf of others, please be advised that you will need to create or use their personal profile before finalizing your payment.
Access to the course is valid for 90 days.
If you wish to receive an invoice instead of paying online, please Contact us by email. Talk to us for our special Corporate Group rates.
Instructor
Peter Alkema is a highly accomplished Business and IT leader specialising in large scale technology delivery and digital transformation strategy implementation for leading financial services business. A proven record in driving the full development lifecycle at all levels across large and complex banking enterprises ensures a deep understanding of the challenges, opportunities and pathways to success for digital transformation in banking. By utilising innovation, awareness, and knowledge, able to drive high-level business strategy formulation, product and platform development, and change management.
Teaching 500k online students about Data Science, Machine Learning, Digital Transformation, Business, Academic, Self Development and Technology skills.
Business & IT leader specialising in large scale technology delivery, digital transformation and Agile software engineering (PhD). 24 years in the banking industry; 10 years consulting (Accenture) and 14 years working in banking (Absa & FNB).
Won the ITWeb Gartner Visionary CIO Of The Year in 2016 & featured on CNBC Africa. Founded and led the largest banking hackathon in South Africa which was featured on Harvard Business Review.
Professional skills: Digital Transformation, Technology, Agile, ERP, Programme Management, Innovation, Thought Leadership, Communication, Process Engineering, Online Training.
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