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Generative AI & Prompt Engineering for Beginners - Learnees

Generative AI & Prompt Engineering for Beginners

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Generative AI & Prompt Engineering for Beginners

Unlock the power of Generative AI! This course provides a comprehensive introduction to generative AI models and the art of prompt engineering. Learn how to craft effective prompts to generate text, images, and code, and explore the ethical considerations surrounding this transformative technology. By the end of this course, you'll be equipped with the skills to leverage generative AI tools for creative problem-solving and automation.

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Course started on:

Upto First 3 Sessions - 100% Refund Guarantee

1. OOPS CONCEPT

Topics:

qwertyuiopasdfghjklzxcvbnm
asdfghjkl;qwertyuiopsdfghjklzxcvbnm

Hands-on:

Skills You Will Learn:

2. qwertyui

Topics:

zxcvbnm
sdfghjkl

Hands-on:

Skills You Will Learn:

3. VBBWWAJSB IKGFDA

Topics:

VBBWWAJSB IKGFDA Module Introduction & Decoding (What do these acronyms stand for in the context of Generative AI?)
Understanding the VBBWWAJSB Framework: Core Principles and Applications in Prompt Engineering
IKGFDA Data Structures & Formats: Representing and Processing Data for Generative Models
VBBWWAJSB Prompts: Designing Effective Prompts Based on the Framework's Principles
Practical Implementation of VBBWWAJSB: Building a Simple Generative AI Application (Hands-on Exercise)
IKGFDA Optimization Techniques: Enhancing Generative Model Performance
Advanced Prompt Engineering with VBBWWAJSB: Creative Applications and Use Cases
Troubleshooting and Debugging VBBWWAJSB-Based Generative AI Projects

Hands-on:

Skills You Will Learn:

4. ASDFBN

Topics:

Understanding ASDFBN: Defining the Problem Space & Use Cases for Generative AI
ASDFBN Architecture: Core Components and Data Flow in Generative Models (Simplified)
Prompt Engineering for ASDFBN: Crafting Effective Prompts for Desired Outputs
Data Preparation & Augmentation Techniques for ASDFBN Training
Evaluating ASDFBN Performance: Metrics and Bias Detection
Hands-on Project: Building a Simple ASDFBN Application with Pre-trained Models
Fine-tuning ASDFBN Models: Adapting Pre-trained Models to Specific Tasks
Ethical Considerations and Responsible Use of ASDFBN in IT & Software

Hands-on:

Skills You Will Learn:

5. FGH

Topics:

FGH Module Introduction: Defining FGH Prompt Engineering (Focus
Granularity
and Handling)
Understanding the "Focus" aspect of FGH: Techniques for creating prompts with a specific and well-defined objective
Mastering "Granularity": Controlling the level of detail in AI outputs through prompt design
"Handling" ambiguity and errors: Strategies for robust prompt design and error mitigation in generative AI
Practical applications of FGH: Case studies and real-world examples of effective FGH prompt engineering in various domains
Advanced FGH Techniques: Combining Focus
Granularity
and Handling for complex generative AI tasks
FGH for different Generative AI models: Adapting prompt engineering strategies for different AI architectures (e.g.
text
image
code)
Evaluating FGH prompt effectiveness: Metrics and methods for assessing the quality and performance of FGH-optimized prompts.

Hands-on:

Skills You Will Learn:

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What You'll Learn in Generative AI & Prompt Engineering for Beginners

Master the essential skills and industry-leading tools that will prepare you for real-world challenges and career success

asdfghjkl;lkjhgfdfghjkl;lksdfghjkl;lkjhgfxcvbnm

Curriculum Designed by Industry Experts

Master the skills employers are looking for with our comprehensive, hands-on curriculum

OOPS CONCEPT

2 Topics

qwertyui

2 Topics

VBBWWAJSB IKGFDA

8 Topics

ASDFBN

8 Topics

FGH

15 Topics

Free Career Counselling

We're happy to help you 24/7

1. OOPS CONCEPT

Topics:

qwertyuiopasdfghjklzxcvbnm
asdfghjkl;qwertyuiopsdfghjklzxcvbnm

Hands-on:

Skills You Will Learn:

2. qwertyui

Topics:

zxcvbnm
sdfghjkl

Hands-on:

Skills You Will Learn:

3. VBBWWAJSB IKGFDA

Topics:

VBBWWAJSB IKGFDA Module Introduction & Decoding (What do these acronyms stand for in the context of Generative AI?)
Understanding the VBBWWAJSB Framework: Core Principles and Applications in Prompt Engineering
IKGFDA Data Structures & Formats: Representing and Processing Data for Generative Models
VBBWWAJSB Prompts: Designing Effective Prompts Based on the Framework's Principles
Practical Implementation of VBBWWAJSB: Building a Simple Generative AI Application (Hands-on Exercise)
IKGFDA Optimization Techniques: Enhancing Generative Model Performance
Advanced Prompt Engineering with VBBWWAJSB: Creative Applications and Use Cases
Troubleshooting and Debugging VBBWWAJSB-Based Generative AI Projects

Hands-on:

Skills You Will Learn:

4. ASDFBN

Topics:

Understanding ASDFBN: Defining the Problem Space & Use Cases for Generative AI
ASDFBN Architecture: Core Components and Data Flow in Generative Models (Simplified)
Prompt Engineering for ASDFBN: Crafting Effective Prompts for Desired Outputs
Data Preparation & Augmentation Techniques for ASDFBN Training
Evaluating ASDFBN Performance: Metrics and Bias Detection
Hands-on Project: Building a Simple ASDFBN Application with Pre-trained Models
Fine-tuning ASDFBN Models: Adapting Pre-trained Models to Specific Tasks
Ethical Considerations and Responsible Use of ASDFBN in IT & Software

Hands-on:

Skills You Will Learn:

5. FGH

Topics:

FGH Module Introduction: Defining FGH Prompt Engineering (Focus
Granularity
and Handling)
Understanding the "Focus" aspect of FGH: Techniques for creating prompts with a specific and well-defined objective
Mastering "Granularity": Controlling the level of detail in AI outputs through prompt design
"Handling" ambiguity and errors: Strategies for robust prompt design and error mitigation in generative AI
Practical applications of FGH: Case studies and real-world examples of effective FGH prompt engineering in various domains
Advanced FGH Techniques: Combining Focus
Granularity
and Handling for complex generative AI tasks
FGH for different Generative AI models: Adapting prompt engineering strategies for different AI architectures (e.g.
text
image
code)
Evaluating FGH prompt effectiveness: Metrics and methods for assessing the quality and performance of FGH-optimized prompts.

Hands-on:

Skills You Will Learn:

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Generative AI & Prompt Engineering for Beginners Certification

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Why enroll for Generative AI & Prompt Engineering for Beginners Certification?

Unlock your potential in with Generative AI & Prompt Engineering for Beginners certification

Most Popular Certification

Generative AI & Prompt Engineering for Beginners certification is rated as one of the most popular and lucrative cloud certifications in IT globally.

Growing Market

The global Generative AI & Prompt Engineering for Beginners market size is expected to grow at a CAGR of 21.2% from 2024 to 2030.

High Salary Potential

The estimated total pay for an Generative AI & Prompt Engineering for Beginners is ₹7,09,000 per year, with an average salary of ₹6,09,000 per year - Glassdoor.

Course Overview: Generative AI & Prompt Engineering for Beginners

Essential details: objectives, prerequisites, schedule, and outcomes

Define Generative AI and its various types, including text, image, and code generation models. Understand the fundamental concepts of prompt engineering and its importance in controlling AI outputs. Develop effective prompt writing techniques, including specifying context, tone, and desired output format. Experiment with different generative AI models and platforms to generate various types of content. Identify and address potential biases and ethical concerns associated with generative AI technologies. Apply prompt engineering skills to solve practical problems and automate tasks. Evaluate the quality and relevance of AI-generated content.