AI+ Prompt Engineer Level 1™

Course code: AC130

Price of the certification exam is included in the price of the course.

Formerly known as AI+ Prompt Engineer Level 1™

Master AI Prompts: Elevate Your Engineering Skills

  • 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
Akční cena
140 EUR

169 EUR including VAT

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Course dates

Starting date: Upon request

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 140 EUR Akční cena

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Type Course
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Upon request Self-paced 8 hours en A 140 EUR Register
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Course description

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 and DALL-E

Ethical AI Practices:

Learn about AI ethics, including data security, privacy, and regulatory compliance to ensure responsible AI use.

  • LangChain
  • OpenAI’s GPT

Target group

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.

Course structure

Course Overview

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

Prerequisites

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

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Certification

50 questions, 70% passing, 90 minutes, online proctored exam

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