Top 10 Promising Study Fields for future

It is difficult to predict the exact top 10 fields in the near future as they may change due to various factors such as technological advancements and shifts in global economic and political priorities. However, some fields that are expected to grow and have high demand in the near future include:

1. Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are designed to think and act like humans. It involves the development of algorithms and computer programs that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. AI systems can learn from experience, recognize patterns in data, and make predictions or decisions. The goal of AI research is to create systems that can perform tasks that would normally require human intelligence, without human intervention.

2. Healthcare and Biotechnology

Biotechnology refers to the application of biological processes, organisms, cells, and systems to create products and technologies that improve human health and quality of life. It involves the manipulation and engineering of biological systems for practical purposes, such as the production of medicines, vaccines, diagnostic tools, and genetically modified crops. Biotechnology encompasses a range of fields, including genetics, molecular biology, microbiology, and biochemistry, and it has applications in many industries, including healthcare, agriculture, and environmental management. The goal of biotechnology is to harness the power of biological systems to solve real-world problems and improve human life.

3. Cybersecurity

Cybersecurity refers to the practice of protecting internet-connected systems, including hardware, software, and data, from attack, damage, or unauthorized access. It involves implementing a combination of technologies, processes, and policies to secure networks, systems, and data from cyber threats such as hacking, malware, phishing, and data breaches. Cybersecurity professionals are responsible for identifying and mitigating risks, detecting and responding to security incidents, and ensuring the confidentiality, integrity, and availability of sensitive information. The field of cybersecurity is constantly evolving as new technologies emerge and cyber threats become more sophisticated, making it a critical area of focus for organizations of all sizes and in all industries.


4. Data Science and Analytics

Data Science is an interdisciplinary field that combines knowledge and skills from statistics, computer science, and domain expertise in order to extract insights and knowledge from data.

A data scientist should have the following skills:

  • Strong mathematical and statistical background, including probability, linear algebra, and machine learning.
  • Proficiency in programming languages such as Python, R, SQL, and others, as well as experience with big data tools and databases.
  • Knowledge of data visualization tools, such as Tableau, ggplot, and D3.js, to effectively communicate insights.
  • Ability to work with large and complex data sets, including the ability to clean, process, and manipulate data.
  • Experience with machine learning techniques, including supervised and unsupervised learning, and deep learning.
  • Strong communication and collaboration skills, as data science often involves working with cross-functional teams and stakeholders.
  • A curious and investigative mindset, as well as a passion for discovering new insights and trends in data.

5. Renewable Energy

Renewable energy is energy that is generated from natural resources that are replenished over time, such as wind, solar, hydro, geothermal and biomass. Unlike non-renewable energy sources, such as coal, oil, and natural gas, which are finite, renewable energy sources are considered sustainable and have a much lower impact on the environment. They emit fewer greenhouse gases and other pollutants, and can help to mitigate the effects of climate change. Renewable energy technologies also offer the potential for decentralized energy generation, reducing dependence on large centralized power plants and increasing energy security. Additionally, renewable energy projects can create jobs, stimulate local economies, and improve energy access for communities around the world.

6. Virtual and Augmented Reality

Augmented Reality (AR) is a technology that enhances the physical world with computer-generated elements, such as sound, video, graphics, or GPS data. It allows users to interact with virtual objects and information in a real-world environment.

Virtual Reality (VR) is a technology that replaces the real world with a simulated environment, allowing users to immerse themselves in a different world. The user interacts with the virtual environment through a headset and often uses hand-held controllers to navigate.

To learn AR and VR, you can start by researching and exploring the various applications and platforms available. You can also take online courses, read books and tutorials, or attend workshops and events. To gain hands-on experience, you can try developing simple AR and VR projects using tools such as Unity, Unreal Engine, or ARKit (for AR). To advance your skills, you can also consider getting certified in AR and VR development.

7. Blockchain Technology

Blockchain is a decentralized, digital ledger that records transactions on multiple computers in a secure and transparent way. Each block in the chain contains a unique cryptographic hash and timestamped transaction data. Once data is recorded on the blockchain, it is extremely difficult to modify, making it a secure and reliable way to store and transfer information.

Applications of blockchain technology include:

  • Cryptocurrency – Most well-known application of blockchain is Bitcoin and other digital currencies.
  • Supply Chain Management – Blockchain can provide a transparent and secure record of transactions, making it easier to track goods and ensure that they were ethically sourced.
  • Digital Identity Management – Blockchain can be used to securely store personal information and provide individuals with more control over their online identity.
  • Smart Contracts – Programs that automatically execute terms of a contract when conditions are met, can be stored on the blockchain, making contract execution faster, more efficient, and less susceptible to tampering or fraud.
  • Voting Systems – Blockchain can provide a secure and transparent way to store and count votes, reducing the risk of electoral fraud.

8. Internet of Things (IoT)

IoT (Internet of Things) refers to the interconnectivity of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, and connectivity which enables these objects to connect and exchange data.

Use Cases:

  • Smart homes: Home automation and control of appliances through a smartphone or voice assistants.
  • Industrial IoT: Monitoring and control of industrial equipment and processes for increased efficiency and safety.
  • Healthcare IoT: Wearable devices and remote monitoring of patients’ health.
  • Agriculture IoT: Precision agriculture using sensors and connected devices to optimize crop yields and conserve resources.
  • Transportation IoT: Intelligent transportation systems for optimizing traffic flow, reducing accidents and increasing fuel efficiency.


  • Connectivity: Devices need to be connected to the internet through Wi-Fi, cellular, or other communication technologies.
  • Hardware: IoT devices require specialized hardware such as sensors, microcontrollers, and communication modules.
  • Software: IoT devices require firmware or software to perform their intended functions and communicate with other devices.
  • Data Management: Large amounts of data generated by IoT devices need to be stored, processed and analyzed in real-time.
  • Security: IoT devices are vulnerable to cyber-attacks and need to have robust security measures in place.
  • Interoperability: IoT devices from different manufacturers need to be able to work together seamlessly

9. Robotics and Automation

Robotics is the interdisciplinary branch of engineering and computer science that deals with the design, construction, operation, and use of robots, as well as computer systems for their control, sensory feedback, and information processing. Robotics study covers a wide range of topics including:

  • Mechanisms: Design and analysis of mechanical systems and their movement.
  • Kinematics: The study of the motion of robots and their joints and links.
  • Dynamics: The study of forces and torques applied on robots and their effects on motion.
  • Control Systems: Design and implementation of algorithms to control the motion of robots.
  • Sensors and Actuators: Design and implementation of sensors and actuators to provide feedback and control to robots.
  • Artificial Intelligence: The application of artificial intelligence techniques such as machine learning and computer vision to enable robots to perform tasks.
  • Human-Robot Interaction: The design of interfaces and systems to enable effective communication and interaction between robots and humans.
  • Mobile Robotics: The study of robots that can move and navigate in unstructured environments.
  • Robotics is a rapidly growing field with applications in industries such as manufacturing, healthcare, agriculture, and entertainment, among others. Studying robotics involves a combination of theory, design, and hands-on implementation, making it a challenging and rewarding field for students with an interest in technology and innovation.

10. Quantum Computing

Quantum computing is a type of computing that uses quantum mechanics to store and process information. Unlike traditional computers that use binary digits (bits) to represent and process data, quantum computers use quantum bits (qubits) that can exist in multiple states simultaneously. This allows quantum computers to perform certain types of calculations much faster than classical computers.

This post is generated using Chat-GPT AI bot.

How does ChatGPT work?

Since OpenAI hasn’t provided all the details, some parts of the diagram may be inaccurate.

We attempted to explain how it works in the diagram below. The process can be broken down into two parts (by Ali Aminian and Alex Xu).

1. Training. To train a ChatGPT model, there are two stages:

– Pre-training: In this stage, we train a GPT model (decoder-only transformer) on a large chunk of internet data. The objective is to train a model that can predict future words given a sentence in a way that is grammatically correct and semantically meaningful similar to the internet data. After the pre-training stage, the model can complete given sentences, but it is not capable of responding to questions.

– Fine-tuning: This stage is a 3-step process that turns the pre-trained model into a question-answering ChatGPT model:

1). Collect training data (questions and answers), and fine-tune the pre-trained model on this data. The model takes a question as input and learns to generate an answer similar to the training data.
2). Collect more data (question, several answers) and train a reward model to rank these answers from most relevant to least relevant.
3). Use reinforcement learning (PPO optimization) to fine-tune the model so the model’s answers are more accurate.

2. Answer a prompt

🔹Step 1: The user enters the full question, “Explain how a classification algorithm works”.

🔹Step 2: The question is sent to a content moderation component. This component ensures that the question does not violate safety guidelines and filters inappropriate questions.

🔹Steps 3-4: If the input passes content moderation, it is sent to the chatGPT model. If the input doesn’t pass content moderation, it goes straight to template response generation.

🔹Step 5-6: Once the model generates the response, it is sent to a content moderation component again. This ensures the generated response is safe, harmless, unbiased, etc.

🔹Step 7: If the input passes content moderation, it is shown to the user. If the input doesn’t pass content moderation, it goes to template response generation and shows a template answer to the user.