Home » Business Topics » Data Trends

Prompt engineering and few-shot learning: An experience beyond data science

  • Aileen Scott 

Chat GPT has been a massive revelation of all time. Generations have evolved and experienced a system that is technically advanced and leverages the highest possible benefits for diversified sectors. As per reports from Investingnews.com, OpenAI Chat GPT has a market value of USD 29 billion with the company’s recent 2023 forecast reflecting a 150% hike from the previous year. This number is predicted to spike to USD 1 billion by 2024. Isn’t that a giant number to bank upon?

Artificial Intelligence has made itself felt with loud yet transformational revelations. This has led to a drastic shift in the quantum of data generated and consumed. Over the years, it has been a clear observation that 90% of the data was generated in the last two years. Adding to this, 120 Zb generated this year is expected to spike by over 150% in 2025, hitting the 181 Zb mark (excerpts from explodingtopics.com).

Based on Precedence Research, the global data science Platforms Market is poised to grow at a CAGR of 16.43%; with the market size reaching USD 378.7 billion mark by 2030. This is an incredible opportunity to dive in and build a career as a certified Data Scientist today.

About GPT-4

GPT-4 is an incredibly efficient processing system for text as well as images; allowing ample opportunities for users to generate prompts based on visual inputs. It is a powerful technology that transforms hand-drawn sketches into functional websites. This powerful AI model surpasses the Chat GPT technology with astounding results.

About prompt engineering

Prompt engineering is a natural language processing (NLP) technique to create and fine-tune prompts to access accurate responses from the given model; that assists in securing the results from model hallucinations. Prompt AI Engineers craft prompts, with targeted verbs and vocabulary that allows for unraveling errors or any issues that may arise.

Popular use cases

  • Healthcare: Allows for improved accuracy of medical diagnosis, developing new treatments; and personalizing healthcare manifold
  • Finance: Allows creation of intelligent assistants to offer personalized investment advice or financial planning to consumers
  • Education: Allows personalized learning with feedback on assignments; alongside creating encapsulating learning experiences

About few-shot learning

Few-shot learning is a machine learning framework that offers ample opportunity for pre-trained models to generalize new categories of data by utilizing a few labeled samples per class.

Popular Use cases

  • Image Classification: Few-shots proposes to use the optimal matching cost between structures to represent the similarity in images.
  • Object Detection: It is a computer vision problem of identifying and locating objects in an image or video sequence and it differs from simple image classification tasks.
  • Semantic Segmentation: It is used to perform binary and multi-label semantic segmentation; wherein every pixel in the image is assigned a class (one or more objects, or background).
  • Robotics: Few shots enable the Robots to mimic the ability of humans to generalize tasks by using only a few demonstrations.
  • Natural Language Processing: In this, the diverse few-shot tasks can derive a variety of metrics from the previous learning experience.

How do prompt engineering and few-shot learning impact the world of data science?

Learned data science professionals, around the world, are paving the way for a flourishing marketspace for expertise in data. Deep learning has been a pivot in solving Computer vision and pattern recognition tasks.

Data Science has garnered enough space in the brains as well as in business processes worldwide. Not just that, with the evolution of data technology, Prompt Engineering and Few-Shot Learning have paced out the way data is viewed and treated. Prompt Engineering plays a pivotal role in the successful training of data models. Qualified data specialists ensure that the model is trained on high-quality data that accurately reflects the underlying task. It has leveled up the entire game plan of global data generation. Many aspiring Data Science professionals have invested hugely in top Data Science certifications; as they are revered as the most targeted trajectory to a lasting career.


Getting certified as a qualified Data professional is the right way to begin your career in the field. There is no doubt when we say that Prompt Engineering and Few-Shot Learning are a way up the ladder, to amplifying your chances at landing a quality data science job role.