Course Description

The AI Prompt Engineer Level 1 Certification is one of the best AI prompt engineer certifications available, designed to empower learners from diverse backgrounds to excel in AI prompt engineering. This comprehensive course introduces the fundamental principles of generative AI prompt engineering, covering essential concepts of AI, machine learning, neural networks, and natural language processing. Through this AI prompt engineering certification, participants gain hands-on experience with the best practices for creating effective prompts that maximize the capabilities of AI models across various applications. With a blend of theoretical knowledge and practical exercises, this AI prompt engineer training equips learners with the skills to design, implement, and optimize prompts for advanced AI systems, making them proficient in AI prompt engineering techniques applicable across industries. By the end of the program, participants earn an AI prompt engineer certificate and are fully prepared to create high-quality, impactful prompts tailored for specific domains and objectives.

Course Objectives

  • Gain expertise in AI prompt engineering, learning to build and optimize prompts that drive AI model performance. This section teaches prompt structure, language adjustments, and troubleshooting to enhance output quality.
  • Explore methods for working with image data in generative AI prompt engineering. Learn to preprocess, fine-tune models, and improve performance for applications like classification, identification, and image synthesis.
  • Acquire a deep understanding of AI tools and models used in prompt engineering. This includes frameworks and architectures to implement AI solutions effectively across varied domains.
  • Apply AI prompt engineering concepts through real-world projects. This section enhances problem-solving, communication, and teamwork by working on collaborative AI projects.

Who Should Attend?

This certification is suitable for individuals from diverse backgrounds and levels of expertise who want to gain a comprehensive understanding of AI and prompt engineering. It is ideal for AI developers, data scientists, educators, and anyone interested in harnessing the full potential of AI models through effective prompting.

Course Agenda

  Module 1: Foundations of Artificial Intelligence (AI) and Prompt Engineering

  1.1 Introduction to Artificial Intelligence

  1.2 History of AI

  1.3 Machine Learning Basics

  1.4 Deep Learning and Neural Networks

  1.5 Natural Language Processing (NLP)

  1.6 Prompt Engineering Fundamentals

  Module 2: Principles of Effective Prompting

  2.1 Introduction to the Principles of Effective Prompting

  2.2 Giving Directions

  2.3 Formatting Responses

  2.4 Providing Examples

  2.5 Evaluating Response Quality

  2.6 Dividing Labor

  2.7 Applying The Five Principles

  2.8 Fixing Failing Prompts

  Module 3: Introduction to AI Tools and Models

  3.1 Understanding AI Tools and Models

  3.2 Deep Dive into ChatGPT

  3.3 Exploring GPT-4

  3.4 Revolutionizing Art with DALL-E 2

  3.5 Introduction to Emerging Tools using GPT

  3.6 Specialized AI Models

  3.7 Advanced AI Models

  3.8 Google AI Innovations

  3.9 Comparative Analysis of AI Tools

  3.10 Practical Application Scenarios

  3.11 Harnessing AI’s Potential

  Module 4: Mastering Prompt Engineering Techniques

  4.1 Zero-Shot Prompting

  4.2 Few-Shot Prompting

  4.3 Chain-of-Thought Prompting

  4.4 Ensuring Self-Consistency in AI Responses

  4.5 Generate Knowledge Prompting

  4.6 Prompt Chaining

  4.7 Tree of Thoughts: Exploring Multiple Solutions

  4.8 Retrieval Augmented Generation

  4.9 Graph Prompting and Advanced Data Interpretation

  4.10 Application in Practice: Real-Life Scenarios

  4.11 Practical Exercises

  Module 5: Mastering Image Model Techniques

  5.1 Introduction to Image Models

  5.2 Understanding Image Generation

  5.3 Style Modifiers and Quality Boosters in Image Generation

  5.4 Advanced Prompt Engineering in AI Image Generation

  5.5 Prompt Rewriting for Image Models

  5.6 Image Modification Techniques: Inpainting and Outpainting

  5.7 Realistic Image Generation

  5.8 Realistic Models and Consistent Characters

  5.9 Practical Application of Image Model Techniques

  Module 6: Project-Based Learning Session

  6.1 Introduction to Project-Based Learning in AI

  6.2 Selecting a Project Theme

  6.3 Project Planning and Design in AI

  6.4 AI Implementation and Prompt Engineering

  6.5 Integrating Text and Image Models

  6.6 Evaluation and Integration in AI Projects

  6.7 Engaging and Effective Project Presentation

  6.8 Guided Project Example

  Module 7: Ethical Considerations and Future of AI

  7.1 Introduction to AI Ethics

  7.2 Bias and Fairness in AI Models

  7.3 Privacy and Data Security in AI

  7.4 The Imperative for Transparency in AI Operations

  7.5 Sustainable AI Development: An Imperative for the Future

  7.6 Ethical Scenario Analysis in AI: Navigating the Complex Landscape

  7.7 Navigating the Complex Landscape of AI Regulations and Governance

  7.8 Navigating the Regulatory Landscape: A Guide for AI Practitioners

  7.9 Ethical Frameworks and Guidelines in AI Development

  Optional Module: AI Agents for Prompt Engineering

  1. What Are AI Agents

  2. Applications and Trends of AI Agents for Prompt Engineers

  3. How Does an AI Agent Work

  4. Core Characteristics of AI Agents

  5. Importance of AI Agents

  6. Types of AI Agents

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.