Courses AI certifications (AI CERTs®)

AI+ Prompting Fundamentals™

  • Price 109 EUR + VAT
  • E-learning Start any time
  • Duration 8 hours of content, self-paced
  • Language English
  • Topic AI Essentials

How you can take it

  • E-learning Start any time · 109 EUR + VAT Order
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Overview

What the course covers

The course, the materials and the exam are in English. The description below is the original AI CERTs® text.

  • Foundational Knowledge: Covers generative AI, ML, NLP, and neural networks essentials
  • Hands-on Learning: Offers practical training in designing and optimizing prompts
  • Industry-Relevant Skills: Prepares learners to build effective AI solutions across sectors
  • Prompting Expertise: Certifies participants to craft impactful, domain-specific prompts

Prerequisites

Understand AI basics, Willingness to think creatively to generate ideas and use AI tools effectively.

Audience

Who is it for

Research Scientists: Advance your research with AI by creating and utilizing effective prompts to explore new scientific data and solve complex problems.

Data Scientists & Analysts: Enhance your ability to optimize machine learning models by mastering prompt engineering for better data analysis and insights.

Developers & Programmers: Learn to build, refine, and deploy AI-driven applications by creating efficient prompts for improved AI system performance.

Business Leaders & Strategists: Gain the skills to incorporate AI solutions into business strategies, optimizing processes and decision-making.

Machine Learning Engineers: Strengthen your expertise by learning how to fine-tune AI prompts to enhance the performance of machine learning models.

In the price

What the price includes

  • Self-paced online course with the full learning material
  • The official AI CERTs® exam
  • Digital badge after passing the exam

Course content

Syllabus

Course Overview
  • Course Introduction Preview
Module 1: Foundations of Artificial Intelligence (AI) and Prompt Engineering
  • 1.1 Introduction to Artificial Intelligence Preview
  • 1.2 History of AI Preview
  • 1.3 Machine Learning Basics Preview
  • 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 PromptingPreview
  • 2.2 Giving DirectionsPreview
  • 2.3 Formatting ResponsesPreview
  • 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 Preview
  • 3.2 Deep Dive into ChatGPT Preview
  • 3.3 Exploring GPT Preview
  • 3.4 Revolutionizing Art with DALL-E
  • 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
  • 5.10 Ethical and Legal Dimensions of AI-Generated Images
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
  • 6.9 Sample Projects and Evaluation Framework
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
  • 7.10 Future of AI Governance and Responsible Innovation
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

Exam

About the exam

  • 50 Questions
  • 90 min Time limit
  • 70% Pass mark
  • Online proctored exam

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Any of our courses can be delivered as private, in-company training, tailored to your organisation, in English or Hungarian.

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