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AI+ Prompt Engineer Level 2™
Mastering Advanced Techniques for Effective AI PromptingThe AI+ Prompt Engineer Level 2 certification is designed for developers aiming to master advanced prompt engineering techniques. This program equips learners with skills in crafting and optimizing prompts, integrating them with cutting-edge development tools, and applying them across diverse domains. Through project-based learning, participants gain practical experience by working on real-world AI projects. The curriculum explores advanced strategies, experimentation, and optimization, ensuring proficiency in creating impactful AI-driven solutions. Ideal for professionals looking to enhance their expertise, this certification bridges the gap between AI innovation and application, empowering developers to lead in the evolving field of prompt engineering.
Buy e-Learning Course Buy Instructor-Led CourseKey Benefits
The AI+ Prompt Engineer Level 2 Certification provides essential skills and knowledge to master AI and prompt engineering. This seven-module course covers foundational AI concepts, advanced prompt engineering techniques, and practical applications, empowering you to generate actionable results effectively.
Comprehensive AI Knowledge
Understand AI fundamentals, including machine learning, deep learning, and natural language processing.
Advanced Prompt Engineering
Master key principles and advanced techniques to craft effective prompts and troubleshoot issues.
Practical AI Tools and Models
Gain hands-on experience with cutting-edge AI tools, text, and image generation models like GPT-4 and DALL-E 2.
Ethical AI Practices
Learn about AI ethics, including data security, privacy, and regulatory compliance to ensure responsible AI use.
Prerequisites
- Familiarity with at least one programming language (Python recommended).
- Basic knowledge of RESTful services and API interactions.
- Basic understanding of AI concepts and language models.
Modules
7
Examination
1
50 MCQs
90 Minutes
Passing Score
70%
Certification Modules
- 1.1 Overview of Prompt Engineering
- 1.2 Basics of API Interaction
- 1.3 Understanding Prompt Structures
- 1.4 Case Studies and Best Practices
- 1.5 Hands-on Exercise
- 2.1 Designing Advanced Prompt Techniques
- 2.2 Designing Multi-Turn Interactions
- 2.3 Contextual and Conditional Prompting
- 2.4 Crafting Domain-Specific Prompts
- 2.5 Contextual and Stateful Prompt Engineering
- 2.6 Meta-Prompting and Autonomous Refinement
- 2.7 Hands-on Exercise
- 3.1 Automated Prompt Optimization Tools
- 3.2 A/B Testing and Evaluation
- 3.3 Reinforcement Learning for Prompt Engineering
- 4.1 Contextual and Role-Based Prompting
- 4.2 Adaptive and Multimodal Prompting
- 5.1 Integrating with Popular Development Tools for Prompt Engineering
- 5.2 Code Repositories and Templates for Prompt Engineering
- 5.3 Developer Communities and Forums for Prompt Engineering
- 5.4 Version Control in Prompt Engineering Projects
- 6.1 Natural Language Processing (NLP) Applications using Prompt Engineering
- 6.2 Business Applications using Prompt Engineering
- 6.3 Creative Applications using Prompt Engineering
- 7.1 Project 1: AI-Driven Customer Support
- 7.2 Project 2: Personalized Content Generation
- 7.3 Project 3: AI in Data Analysis
Certification Modules
- 1.1 Overview of Prompt Engineering
- 1.2 Basics of API Interaction
- 1.3 Understanding Prompt Structures
- 1.4 Case Studies and Best Practices
- 1.5 Hands-on Exercise
- 2.1 Designing Advanced Prompt Techniques
- 2.2 Designing Multi-Turn Interactions
- 2.3 Contextual and Conditional Prompting
- 2.4 Crafting Domain-Specific Prompts
- 2.5 Contextual and Stateful Prompt Engineering
- 2.6 Meta-Prompting and Autonomous Refinement
- 2.7 Hands-on Exercise
- 3.1 Automated Prompt Optimization Tools
- 3.2 A/B Testing and Evaluation
- 3.3 Reinforcement Learning for Prompt Engineering
- 4.1 Contextual and Role-Based Prompting
- 4.2 Adaptive and Multimodal Prompting
- 5.1 Integrating with Popular Development Tools for Prompt Engineering
- 5.2 Code Repositories and Templates for Prompt Engineering
- 5.3 Developer Communities and Forums for Prompt Engineering
- 5.4 Version Control in Prompt Engineering Projects
- 6.1 Natural Language Processing (NLP) Applications using Prompt Engineering
- 6.2 Business Applications using Prompt Engineering
- 6.3 Creative Applications using Prompt Engineering
- 7.1 Project 1: AI-Driven Customer Support
- 7.2 Project 2: Personalized Content Generation
- 7.3 Project 3: AI in Data Analysis
Exam Objectives
Design and Optimization of Prompts
Demonstrate the ability to craft, refine, and optimize prompts to achieve desired outcomes across different AI applications.
Advanced Strategies in Prompt Engineering
Apply advanced prompt engineering techniques and strategies to solve complex problems and drive innovation in AI systems.
Integration with Development Tools
Showcase proficiency in integrating prompt engineering workflows with development tools, APIs, and programming environments.
Real-World Applications and Project Execution
Implement prompt engineering concepts in real-world scenarios, completing project-based tasks that highlight practical applications across diverse domains.
Hear it from the Learners
Marc H
Happy to share I've completed the AI+ Executive Certification from AI CERTs! This program has sharpened my skills in strategic AI application + implementation, further equipping me to lead AI-driven organizational transformation.
Georgia L
As VP Operations, my recent completion of the AI+ Executive exam through AI CERTs was a pivotal step in advancing my AI skill set as we embrace an AI-driven future. This certification not only deepened my understanding of AI's broad impact across various divisions but also equipped me with the tools to make informed, strategic decisions.
Antonio C
AI+ Executive™ Instructor Guide Certificate. Today, I am part of the team of #CompuEducación instructors to teach the #AI CERTs AI+Executive certification course . This 8-hour course is a new standard for business leaders who want to start a solid path in the adoption of AI for the transformation of their companies. The technological, business, ethical, legal and strategy foundations are covered. The examples of using “AI” are practical, up-to-date, and touch on the different variants of “AI.”
Doug F
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Get CertifiedFrequently Asked Questions
This course dives into advanced prompt engineering techniques for AI models, focusing on optimizing prompts for better AI responses.
AI developers, data scientists, and content creators who have completed basic prompt engineering courses and want to advance their skills.
You’ll explore advanced techniques like few-shot prompting, chain-of-thought prompting, and AI prompt optimization for complex models.
Industries like AI development, content creation, and AI research benefit from better prompt engineering.
You will work on projects that include optimizing AI-generated content and enhancing AI tools for business applications.