Prompt Engineering

Introduction to Prompt Engineering

Prompt Engineering is a process to effectively guide and generate AI models and control their output to produce desired results. It is a prompt to improve accuracy and effectiveness.

Prompt engineering is the process of refining prompts that a person can input into a generative artificial intelligence service to create text or images. Anyone can do this using natural language in generators.ChatGPT or DALL–E. It is a technique that AI engineers use when refining large language models with specific or recommended rock.

Importance of Prompt Engineering in Generative AI

Prompt engineering is important for AI engineers to create better services, such as CHATBOTS, that can handle complex tasks, like customer service or generate legal contracts.
Making sure that generative AI services like ChatGPT are able to deliver outputs, requires engineers to BUILD CODE and train AI on extensive and accurate data.
Proper prompt engineering can also identify and mitigate prompt injection attacks to ensure companies deliver consistent and accurate services.

Prompt Engineering Examples

For Text Models like ChatGPT

What’s the difference between a professional summary and an executive summary?
Write a professional summary for a marketing analyst, looking for a marketing manager job.
Now trim it down to less than 60 words.
Rewrite it with a less formal tone.

For Image Models like DALL-E

A painting of a cat.
A painting of a cat chasing a mouse in impressionist style.
Now use only warm tones in the painting.

Step by Step Guide For Engineering Your Prompts

1. EXPRESS YOUR QUERY AS CLEARLY AS POSSIBLE
Since generative AI is a deep learning model trained on data produced by humans and machines, it doesn’t have the capability to shift through exactly what you are communicating to understand what you are actually saying.

For example, instead of, “ write an outline that includes the title and next steps”, you could query, “ write an outline for an academic research proposal that includes sections for title, summary and next steps”

2. EXPERIMENT TO COME UP WITH BEST PRACTICES
For each type of output, such as a brief outline, research proposal, or resume, bullet points, you will want to experiment with the generative AI by using different variations of the same request. This way, you will determine whether you need to include tidal” in a formal tone of.”

If you do need to include “ tone” in your prompt, should you write “ in a professional tone” or “ informal tone?” Playing with your inputs is important as well. Consider inputting sample outlines in a prompt of providing examples. You would like the generator to model.

3. FOLLOW UP WITH QUESTIONS OR INSTRUCTIONS
Once You have shaped your output into the correct format and tone, you might want to, for example, limit the number of words or characters, or, you might want to create two separate versions of the outlines, one for internal purposes.

4. PLAY WITH DIFFERENT PROMPTING TECHNIQUES

Zero-shot Prompting:
‍This is the most direct and simplest method of just asking direct questions/instructions without providing additional information.
Few-shot Prompting:
This involves supplying the generative AI with some examples to guide the output, this is more suitable for complex tasks than zero – shot prompting.
COT(Chain of Thought) Prompting:
This method helps improve an LLM’s output by breaking down complex reason into intermediate steps which can help the model produce more accurate.
Prompt Chaining:
The prompter splits a complex task into smaller and easier sub tasks, then uses the generative AI’s outputs to accomplish the overarching task. This method can improve reliability and consistency for some of the most complicated tasks.

Collecting Data and Repositories for Prompt Engineering

Imagine you're building a robot assistant, and to make it smart, it needs to learn from examples. This process is like teaching a pet new tricks, but instead of treats, it learns from lots of examples stored in something called a "repository," which is like a big library filled with different books.

Understanding Data: Just like a pet learns from experiences, our robot assistant learns from data. This data can be anything from text, images, to numbers, depending on what we want our assistant to learn.
Collecting Data: We need to gather lots of examples for our robot to learn from. This means finding text, images, or other information that represents the things we want our assistant to understand. For example, if we want it to help with cooking, we'd collect recipes, cooking tips, and food images.
Quality Check: Just like we don't want our pet to learn bad habits, we need to make sure our data is good quality. This means checking if the information is accurate, relevant, and not misleading.
Privacy and Ethics: We have to be careful where we get our data from. We need to make sure we're allowed to use it and that we're not invading anyone's privacy. It's like asking permission before borrowing someone's book from the library.
Organizing Data: Once we have our data, we organize it neatly in our "library" or repository. This makes it easier for our robot to find and learn from. We categorize the data, label it with relevant information, and make sure it's stored in a way that our robot can understand.
Continuous Learning: Just like learning doesn't stop after one trick, our robot assistant keeps learning over time. We regularly update our data and repository to keep our assistant smart and up-to-date with the latest information.

Websites to learn Prompt Engineering

Comparison of various online courses for Prompt Engineering

COURSE/ MODULE NAME

FEATURES/ HIGHLIGHTS

RATINGS/ REVIEWS

PRICING

Introduction to Prompt Injection Vulnerabilities by COURSERA

Can be completed in 2 hours, self study module,
Beginner-level, single module course,
Skills like test engineering, application security, security testing, software testing, black box, web application security are acquired,
Includes practical examples and real-world implications.

No reviews available.

One can enroll for free to avail this course module.

Prompt Engineering for Data analysis, Python, Pandas, ChatGPT by UDEMY

It is an online self study module of 11 hours.
One could learn skills like Python, Jupyter Notebook, Pandas, AI, Data visualization, Anaconda etc.
It helps individuals from diverse backgrounds who are eager to leverage the power of AI tools like chat GPT to revolutionize their coding and data analysis journey.

368 ratings have been given by 1888 students.
It has an overall rating of 4.5 stars out of 5 stars.

As for personal use, the course amounts to Rs. 799. And as for use by teams in a business organization, the pricing is different.

AI applications and Prompt Engineering by EDX

In this introductory online course, one can learn to create AI applications with prompt engineering.
This course goes beyond AI basics, and teaches technical and practical skills to harness the power of prompt engineering.
A certain experience with Java script, Node.js, and APIs is recommended.

This course boasts of 6495 enrolled students.

Specific ratings/ reviews were not mentioned in the EDX website.

This is a free course that can be upgraded to its paid version that includes a price tag of Rs. 8265 and other benefits like unlimited access to course materials, shareable certification upon completion, and graded assignments and exams.

Prompt Engineering for ChatGPT by VANDERBILT UNIVERSITY ( via COURSERA)

No prior experience is recommended for this beginner level course.
It is a module of 18 hours.
One would gain skills like chat, GPT advanced data analysis through this course.

With 2660 reviews, it has a rating of 4.8/5 stars.

Users having the subscription for COURSERA plus can access it freely. Although, paid versions are available too.

Generative AI: Prompt Engineering basics by IBM (via COURSERA)

Duration of 7+ hours, with on-demand sessions.
Anybody from students to professionals to executives and even enthusiasts interested in leveraging effective prompt engineering techniques can use it.
Introduction to various prompt engineering approaches like interview pattern, chain of thought, and tree of thought, which aims at generating precise and relevant responses.

4.8 rating at COURSERA based on 292 ratings on COURSERA.

It is a free online course to audit, and a paid certification is available too.

ChatGPT Prompt Engineering for developers by DeepLearning.AI ( via COURSERA)

It is a beginner level course, with on demand sessions, and a duration and workload of 1 hour, 5 minutes.
Introduction to various prompt engineering approaches like interview pattern, chain of thought, and tree of thought, which aims at generating precise and relevant responses.

This course has a 4.8/5 rating at COURSERA based on 421 ratings.

It is a paid course.

IBM: Introduction to prompt engineering by EDX

This course will explain the concept and relevance of prompting engineering in generating AI models, while also exploring commonly used tools for prompt engineering to aid with prompt engineering

Relevant reviews were not found for this particular course module.

This is a free course that can be upgraded to its paid version that includes a price tag of Rs. 4091 and other benefits like unlimited access to course materials, shareable certification upon completion, and graded assignments and exams.

The complete prompt engineering for AI Boot Camp 2024, by UDEMY

It is a paid course of a duration and workload of 15+ hours, with on demand sessions, for which the content is updated monthly.
This beginner level course comes with a certification and gives a practical understanding of coding skills for working professionally with AI, including GPT –4, stable diffusion, and GitHub copilot.
Helps in recognizing the “five principles of prompting”, as well as common tips and tricks for professional grade output, understand the python coding patterns and drawing that one needs to run and scale AI reliably in production, and start working as an engineer.

The course module had been rated 4.5/5 at UDEMY based on 27964 ratings.Has over 3000+ 5-star ratings.

It’s a paid course.

Prompt Engineering Course by EDUREKA

It is expertly created by top industry professionals and helps in acquiring the skills to effectively utilize prompts for generating customized text, code, and more, transforming a user's problem solving approach.
The course has unlimited access, 24/7 support hands on project based learning, industry recognize certification.

It has 2944 learner’s enrolledThrough 1200 ratings, it has been given a rating of 4.6 (on a 5 point scale).

The course is priced at Rs. 19,000.

Create effective prompts for generative AI training tools by MICROSOFT

It is a very basic MODULE, covering the basic concepts of prompt engineering, the elements of an effective prompt, and the best practices in prompting.
This module can be completed in 20 minutes.
This could be understood or done by even school going students due to its simplicity.

No relevant data on the ratings or reviews.

It is completely free.