25 Great Coding Prompts for ChatGPT: A Beginner’s Guide

We’ve included 25 fantastic coding prompts in this guide just for ChatGPT users. These prompts are meant to push and motivate you to solve problems creatively, sharpen your coding skills, and think outside the box.

Yes, here are 25 programming prompts that are arranged according to scenarios, along with recommended programming languages and expert advice:

1. Development of a Tool:

Scenario: You’re tasked with creating a text manipulation tool for data processing.

Prompt: Build a command-line tool that accepts a text file as input and performs operations such as word count, character count, and search/replace functionality.

Pro Tips:

• Use Python for its simplicity and extensive standard library for file handling and string manipulation.

• Consider using regular expressions for efficient search and replace operations.

• Provide clear command-line arguments and error handling to enhance user experience.

2. Development of a Game:

Scenario: You’re developing a 2D platformer game for mobile devices.

Prompt: Create a game prototype featuring a character that can move left, right, and jump to navigate through levels filled with obstacles and enemies.

Pro Tips:

• Use Unity with C# for cross-platform development and easy integration of game assets.

• Implement physics-based movement for realistic character behavior.

• Design levels with increasing difficulty to engage players and encourage replayability.

3. Development of a Mobile App:

Scenario: You’re building a social networking app for sharing photos and connecting with friends.

Prompt: Develop an app that allows users to upload photos, apply filters, and share them with their friends. Include features such as user profiles, likes, and comments.

Pro Tips:

• Use React Native for efficient development of iOS and Android apps with a single codebase.

• Integrate with cloud storage services like Firebase or AWS S3 for photo storage and retrieval.

• Implement real-time updates using WebSocket or Firebase Realtime Database for a seamless user experience.

4. Development of an AI Tool:

Scenario: You’re creating a virtual assistant to help users with daily tasks.

Prompt: Build an AI-powered chatbot that can answer questions, set reminders, and provide personalized recommendations based on user preferences.

Pro Tips:

• Use Python with libraries like NLTK or spaCy for natural language processing.

• Train your chatbot using machine learning algorithms such as sequence-to-sequence models or transformers.

• Integrate with APIs for additional functionalities like weather forecasts or news updates.

5. Web Development:

Scenario: You’re developing an e-commerce website for selling products online.

Prompt: Design a website with features for browsing products, adding them to a shopping cart, and completing purchases securely.

Pro Tips:

• Use a combination of HTML, CSS, and JavaScript for frontend development to create a responsive and user-friendly interface.

• Utilize frameworks like React.js or Vue.js for building interactive components and managing state.

• Implement backend functionality using Node.js with Express.js or Django for handling user authentication, product management, and payment processing.

These prompts cover a variety of scenarios and programming languages, providing opportunities for developers to practice different skills and techniques.

6. Data Analysis and Visualization:

Scenario: You’re analyzing a dataset containing information about sales transactions and customer demographics.

Prompt: Use Python with libraries like Pandas and Matplotlib to explore the dataset, calculate summary statistics, and create visualizations to identify trends and patterns.

Pro Tips:

• Use Pandas for data manipulation tasks such as filtering, grouping, and aggregating.

• Create various plots including histograms, scatter plots, and box plots to visualize distributions and relationships between variables.

• Provide insights and recommendations based on the analysis to improve business strategies.

7. Network Programming:

Scenario: You’re developing a chat application that allows users to communicate over a local network.

Prompt: Implement a client-server architecture using sockets in Python to enable real-time messaging between multiple clients connected to the same server.

Pro Tips:

• Use the socket module in Python for handling network communication.

• Implement a simple protocol for sending and receiving messages between clients and the server.

• Handle concurrency using threading or asynchronous programming to support multiple simultaneous connections.

8. Security and Cryptography:

Scenario: You’re tasked with implementing a secure login system for a web application.

Prompt: Develop a login system using secure password hashing and encryption to protect user credentials from unauthorized access.

Pro Tips:

• Use bcrypt or Argon2 for secure password hashing to prevent password cracking attacks.

• Implement HTTPS and secure cookie handling to encrypt data transmitted over the network.

• Apply security best practices such as input validation and session management to prevent common vulnerabilities like SQL injection and cross-site scripting (XSS).

9. Machine Learning:

Scenario: You’re building a spam email classifier to filter out unwanted emails from users’ inboxes.

Prompt: Train a machine learning model using Python with libraries like scikit-learn or TensorFlow to classify emails as spam or non-spam based on their content.

Pro Tips:

• Preprocess email data by tokenizing, stemming, and removing stop words to extract relevant features.

• Experiment with different machine learning algorithms such as Naive Bayes, Support Vector Machines, or deep learning models to find the best classifier.

• Evaluate the model’s performance using metrics like accuracy, precision, recall, and F1-score, and fine-tune parameters to improve results.

10. Internet of Things (IoT) Development:

Scenario: You’re designing a smart home system to control lights, temperature, and security devices remotely.

Prompt: Develop an IoT solution using Raspberry Pi and sensors to monitor environmental conditions and control connected devices via a web or mobile interface.

Pro Tips:

• Use Python with libraries like RPi.GPIO or Pi4J for interfacing with sensors and actuators connected to the Raspberry Pi.

• Implement a web server using frameworks like Flask or Django to create a user interface for managing IoT devices.

• Secure communication between devices using protocols like MQTT or HTTPS to prevent unauthorized access to sensitive data.

These prompts cover additional programming domains such as data analysis, network programming, security, machine learning, and IoT development, providing a comprehensive range of challenges for developers to explore.

11. Embedded Systems Development:

Scenario: You’re developing firmware for a wearable fitness tracker that collects data on users’ physical activity.

Prompt: Write C code to interface with sensors (accelerometer, heart rate monitor, etc.), log data, and implement algorithms for activity tracking and analysis.

Pro Tips:

• Use a real-time operating system (RTOS) like FreeRTOS or develop your own lightweight scheduler for task management.

• Optimize code for low power consumption to maximize battery life.

• Implement communication protocols such as Bluetooth Low Energy (BLE) for syncing data with mobile devices.

12. Robotics Programming:

Scenario: You’re programming a robot to navigate through a maze and perform tasks such as object detection and manipulation.

Prompt: Develop control algorithms using ROS (Robot Operating System) and Python/C++ to enable the robot to map its environment, plan paths, and interact with objects.

Pro Tips:

• Use ROS for its modular architecture and extensive library of packages for robot perception, navigation, and manipulation.

• Implement algorithms like SLAM (Simultaneous Localization and Mapping) for mapping and localization, and A* or Dijkstra’s algorithm for path planning.

• Integrate sensors such as LiDAR, cameras, and encoders for environment perception and feedback control.

13. Cloud Computing:

Scenario: You’re building a cloud-based application for storing and analyzing large datasets.

Prompt: Develop a web application using a cloud platform like AWS or Google Cloud Platform (GCP) to upload, process, and visualize data stored in a distributed database or object storage service.

Pro Tips:

• Use cloud services like AWS S3 or GCP Cloud Storage for scalable and durable storage of large datasets.

• Implement data processing tasks using serverless computing platforms like AWS Lambda or Google Cloud Functions to automatically scale based on demand.

• Use cloud-native databases like AWS DynamoDB or GCP Bigtable for storing and querying structured data with high throughput and low latency.

14. DevOps and Continuous Integration/Continuous Deployment (CI/CD):

Scenario: You’re automating the deployment pipeline for a web application to streamline development and release processes.

Prompt: Set up a CI/CD pipeline using tools like Jenkins, GitLab CI/CD, or GitHub Actions to automatically build, test, and deploy changes to production environments.

Pro Tips:

• Define stages in the pipeline for code linting, unit testing, integration testing, and deployment to various environments (development, staging, production).

• Use infrastructure as code (IaC) tools like Terraform or AWS CloudFormation to provision and configure resources required for the application stack.

• Monitor pipeline performance and logs to identify bottlenecks and optimize build times for faster feedback loops.

15. Natural Language Processing (NLP):

Scenario: You’re developing a sentiment analysis tool to analyze social media posts and classify them as positive, negative, or neutral.

Prompt: Train a machine learning model using Python with NLP libraries like NLTK or spaCy to preprocess text data, extract features, and classify sentiments.

Pro Tips:

• Experiment with different text representations such as bag-of-words, TF-IDF, or word embeddings like Word2Vec or GloVe.

• Fine-tune pre-trained language models like BERT or GPT to improve performance on specific tasks.

• Evaluate the model’s performance using metrics like accuracy, precision, recall, and F1-score, and analyze misclassifications to identify areas for improvement.

These prompts cover specialized domains such as embedded systems, robotics, cloud computing, DevOps, and NLP, providing opportunities for developers to explore advanced topics and technologies in their respective fields.

16. Blockchain Development:

Scenario: You’re building a decentralized application (DApp) for tracking supply chain logistics using blockchain technology.

Prompt: Develop smart contracts using Solidity for Ethereum blockchain to record product information, track movement across the supply chain, and ensure transparency and immutability.

Pro Tips:

• Use Ethereum development tools like Truffle or Hardhat for compiling, testing, and deploying smart contracts.

• Implement access control mechanisms to restrict write access to authorized parties and ensure data integrity.

• Integrate with off-chain systems for interacting with external data sources and triggering contract actions.

17. Game Development with Unity (3D):

Scenario: You’re creating a first-person shooter (FPS) game with Unity for PC and console platforms.

Prompt: Design levels with realistic environments, implement player controls, enemy AI, weapons, and multiplayer functionality to create an immersive gaming experience.

Pro Tips:

• Utilize Unity’s built-in physics engine for realistic interactions between game objects.

• Implement finite state machines (FSM) or behavior trees for enemy AI to create challenging opponents.

• Optimize game performance by managing resources efficiently and using techniques like occlusion culling and level-of-detail (LOD) systems.

18. Mobile App Development with Flutter:

Scenario: You’re developing a cross-platform mobile app for managing personal finances.

Prompt: Build an app with features for budget tracking, expense categorization, and generating financial reports using Flutter framework with Dart programming language.

Pro Tips:

• Use Flutter’s widget-based architecture for building responsive and visually appealing user interfaces across iOS and Android devices.

• Integrate with local storage or cloud databases like Firebase Firestore for storing and syncing financial data.

• Implement charts and graphs for visualizing spending patterns and budget goals to help users make informed financial decisions.

19. Web Scraping and Automation:

Scenario: You’re tasked with extracting data from multiple websites and aggregating it into a single database.

Prompt: Write Python scripts using libraries like BeautifulSoup and Scrapy to crawl web pages, extract relevant information, and store it in a structured format (e.g., CSV, JSON, database).

Pro Tips:

• Respect website policies and robots.txt files to avoid overloading servers and getting blocked.

• Handle different HTML structures and dynamic content using techniques like CSS selectors and XPath expressions.

• Schedule and automate scraping tasks using cron jobs or task schedulers to keep data up-to-date.

20. Augmented Reality (AR) Development:

Scenario: You’re developing an AR application for visualizing furniture placement in real-world environments.

Prompt: Use ARCore (for Android) or ARKit (for iOS) along with Unity or native development to create an app that allows users to place virtual furniture models in their physical surroundings.

Pro Tips:

• Implement plane detection and object tracking to accurately position virtual objects relative to real-world surfaces.

• Optimize rendering performance for AR applications by minimizing polygon counts and texture sizes.

• Provide intuitive gestures and controls for users to rotate, scale, and interact with virtual objects seamlessly.

These prompts cover advanced topics and specialized technologies such as blockchain development, Unity game development, Flutter app development, web scraping, and augmented reality, offering developers opportunities to explore cutting-edge tools and frameworks in their respective domains.

21. Natural Language Understanding (NLU) with BERT:

Scenario: You’re building a question-answering system that can understand and respond to user queries.

Prompt: Fine-tune a pre-trained BERT model using TensorFlow or PyTorch to process natural language inputs, extract relevant information, and generate accurate responses to questions.

Pro Tips:

• Fine-tune BERT on domain-specific datasets to improve performance on specialized tasks.

• Implement techniques like tokenization, attention mechanisms, and positional encoding to preprocess input data for BERT.

• Evaluate the model’s performance using evaluation metrics like exact match and F1-score on question-answering datasets.

22. Cloud-Native Application Development:

Scenario: You’re building a microservices-based application to support scalability and fault tolerance in a cloud environment.

Prompt: Design and implement individual microservices using Docker containers and Kubernetes orchestration to manage deployment, scaling, and service discovery.

Pro Tips:

• Containerize each microservice using Docker to encapsulate dependencies and ensure consistency across different environments.

• Use Kubernetes for container orchestration to automate deployment, scaling, and management of microservices.

• Implement health checks, load balancing, and fault tolerance mechanisms to ensure high availability and reliability of the application.

23. Reactive Programming with RxJava:

Scenario: You’re developing a real-time analytics dashboard that processes streaming data from IoT devices.

Prompt: Use RxJava to handle asynchronous data streams, apply transformations, and aggregate data in real-time to update the analytics dashboard dynamically.

Pro Tips:

• Use RxJava’s Observable and Observer patterns to represent and subscribe to data streams emitted by IoT devices.

• Apply operators like map, filter, and reduce to manipulate and process data streams efficiently.

• Use backpressure handling techniques like buffering and throttling to manage data flow and prevent overload.

24. Quantum Computing Simulation:

Scenario: You’re simulating quantum algorithms on a classical computer to understand their behavior and performance.

Prompt: Write Python code using libraries like Qiskit or Cirq to implement quantum circuits, simulate quantum operations, and analyze results using classical simulation techniques.

Pro Tips:

• Design quantum circuits to perform tasks such as quantum teleportation, Grover’s search algorithm, or Shor’s factoring algorithm for benchmarking and experimentation.

• Use quantum simulators to simulate quantum circuits on classical computers for small-scale testing and validation.

• Analyze simulation results to understand quantum phenomena and optimize quantum algorithms for potential future implementation on actual quantum hardware.

25. Geospatial Data Analysis and Visualization:

Scenario: You’re analyzing geospatial data to understand patterns and trends in environmental phenomena.

Prompt: Use Python with libraries like GeoPandas, Matplotlib, and Folium to process geospatial datasets, perform spatial analysis, and create interactive visualizations.

Pro Tips:

• Use GeoPandas for handling geospatial data structures like points, lines, and polygons, and performing spatial operations like buffering, intersection, and union.

• Visualize geospatial data using Matplotlib for static plots and Folium for interactive maps embedded in web applications.

• Apply statistical techniques and machine learning algorithms to extract insights and patterns from geospatial data, such as clustering or regression analysis.

These prompts cover advanced topics in natural language understanding, cloud-native application development, reactive programming, quantum computing simulation, and geospatial data analysis, providing developers with opportunities to explore cutting-edge technologies and methodologies in these domains.