GenAI Foundations and Prompt Engineering
Master prompt engineering to design advanced AI interactions. Learn GenAI architecture, real-world use cases, and hands-on techniques to build chatbots, optimize prompts, and scale AI apps that deliver real business value.
Overview
This course includes:
- On-demand videos
- Practice assessments
- Multiple hands-on learning activities
- Exposure to a real-world project
- 100% self-paced learning opportunities
- Certification of completion
Ever struggled to get consistent, high-quality responses from AI systems, or wondered how to build chatbots that actually understand your customers' needs? Most professionals know AI is powerful, but few know how to communicate with it effectively to unlock its true potential.
This course transforms you from an AI user into a prompt engineering expert who can design sophisticated interactions with large language models. You'll master the fundamental architecture of GenAI systems, explore real-world enterprise applications, and learn advanced prompting techniques that consistently deliver exceptional results. Through hands-on practice, you'll build multi-step prompt chains, optimize context windows, and create customer support chatbots that provide human-like assistance.
By the end of this course, you'll confidently design prompt strategies for any business scenario, architect GenAI applications that scale, and implement conversation systems that drive real business value. You'll have the skills to turn AI from a mysterious black box into a powerful, predictable tool for solving complex problems.
Take the first step toward mastering AI communication and become the prompt engineering specialist every organization needs in the AI-driven future.
Skills You Will Gain
Learning Outcomes (At The End Of This Program, You Will Be Able To...)
- Apply GenAI system architecture principles to design scalable AI applications.
- Construct advanced prompt engineering patterns for different business use cases.
- Implement interactive prompt building workflows with real-time optimization.
- Develop customer support conversation systems with quality assurance frameworks.
Prerequisites
In this course, learners are expected to have a basic understanding of APIs and web services to effectively integrate AI systems into real-world applications. Familiarity with Python programming is important, as it serves as the primary language for implementing generative AI solutions. A general knowledge of machine learning concepts will provide the necessary foundation to grasp the core principles of GenAI and large language models. Additionally, experience with command line tools will help in setting up development environments and managing workflows efficiently throughout the course.
Who Should Attend
In this course, the target audience includes software engineers who are exploring AI integration to enhance their applications, product managers seeking to implement AI-driven solutions for business growth, data scientists looking to expand their expertise into generative AI, and business analysts aiming to optimize workflows and decision-making with AI-powered tools.
