Generative AI for Code Completion
Did you know that AI-powered code completion tools can significantly accelerate coding tasks and enhance code quality?
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Did you know that AI-powered code completion tools can significantly accelerate coding tasks and enhance code quality?
Did you know that AI-powered code completion tools can significantly accelerate coding tasks and enhance code quality?
This short course was created to help software engineers, developers, and coding enthusiasts use Generative AI for Code Completion.
By completing this course, you'll be able to:
- Understand the role of AI in code completion.
- Gain familiarity with basic and advanced usage of Generative AI tools for coding, such as ChatGPT and GitHub Copilot.
- Apply AI-driven code completion tools in real-world coding scenarios to enhance productivity and code quality.
By the end of this course, you will be able to:
- Apply Large Language Models (LLMs) for both basic and advanced code completion to enhance coding efficiency and accuracy.
- Evaluate Generative AI tools to enhance productivity, creativity, and problem-solving capabilities in software development workflows.
This course is unique because it bridges AI technology with practical coding skills, equipping you to leverage AI-driven code completion tools effectively.
To be successful in this project, you should have basic programming knowledge and familiarity with coding.
What's inside
Syllabus
Generative AI for Code Completion
In this course, you will leverage AI powered completions tools to accelerate coding tasks, reduce errors, enhance code quality. You will also be able to assess and apply best practices in AI-driven code completion within their software development projects.
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Syllabus
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Activities
Review Programming Fundamentals
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Before starting the course, brush up on basic programming concepts to ensure a solid foundation for understanding AI-powered code completion.
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Programming Fundamentals
Show steps
-
Review online resources or tutorials on core programming concepts such as data types, variables, operators, loops, and conditional statements.
-
Solve simple coding exercises to practice applying these concepts.
Explore AI Code Completion Tools
Show steps
Familiarize yourself with the different Generative AI tools available for code completion, their features, and how to integrate them into your development environment.
Browse courses on
Generative AI
Show steps
-
Watch online tutorials or read documentation on popular AI code completion tools such as ChatGPT, GitHub Copilot, or TabNine.
-
Install and set up the tools in your preferred development environment.
-
Experiment with the tools by completing simple coding tasks and observing the suggestions and completions provided.
Code Completion Challenges
Show steps
Solve a series of coding challenges using AI-driven code completion tools to strengthen your understanding of syntax and best practices.
Browse courses on
Generative AI
Show steps
-
Access online coding platforms or IDEs that offer AI-powered code completion tools.
-
Select a series of coding challenges or exercises that focus on areas you want to improve.
-
Attempt to solve the challenges using AI-driven code completion, paying attention to the suggestions and patterns provided.
-
Review your solutions and compare them to the suggested completions, noting the accuracy and efficiency of the AI tools.
Three other activities
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Show all six activities
AI-assisted Code Review
Show steps
Pair up with a peer and review each other's code using AI-driven code completion tools to identify potential improvements and best practices.
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Generative AI
Show steps
-
Find a partner who is also taking the course or has experience with AI-powered code completion tools.
-
Exchange code samples that you want to review and provide feedback on.
-
Use AI-powered code completion tools to analyze the code, suggest improvements, and identify potential errors or inefficiencies.
-
Discuss the suggestions and insights generated by the AI tools and agree on the best course of action to enhance the code quality.
Code Refactoring Project
Show steps
Refactor an existing codebase using AI-powered code completion tools to enhance readability, maintainability, and efficiency.
Browse courses on
Code Completion
Show steps
-
Choose an open-source project or a codebase that you have developed earlier.
-
Identify areas in the codebase that can benefit from code completion, such as repetitive blocks of code, complex logic, or error-prone sections.
-
Use Generative AI tools for code completion to suggest alternative and improved code structures, algorithms, or error handling mechanisms.
-
Implement the suggested changes, review the impact on code quality and efficiency, and document the process and the results in a project report.
Custom AI Code Completion Tool
Show steps
Develop your own AI-powered code completion tool tailored to a specific domain or programming language to expand your understanding of the techniques and algorithms involved in code completion.
Browse courses on
Generative AI
Show steps
-
Define the scope and functionality of your custom AI code completion tool.
-
Gather a dataset of code snippets, documentation, and other relevant materials for training the AI model.
-
Choose and implement an appropriate machine learning model for code completion, such as a Transformer-based model or a language model.
-
Train the model on the collected dataset and evaluate its performance.
-
Integrate the trained model into a user-friendly interface or tool for easy access and use by developers.
Review Programming Fundamentals
Show steps
Before starting the course, brush up on basic programming concepts to ensure a solid foundation for understanding AI-powered code completion.
Browse courses on
Programming Fundamentals
Show steps
- Review online resources or tutorials on core programming concepts such as data types, variables, operators, loops, and conditional statements.
- Solve simple coding exercises to practice applying these concepts.
Explore AI Code Completion Tools
Show steps
Familiarize yourself with the different Generative AI tools available for code completion, their features, and how to integrate them into your development environment.
Browse courses on
Generative AI
Show steps
- Watch online tutorials or read documentation on popular AI code completion tools such as ChatGPT, GitHub Copilot, or TabNine.
- Install and set up the tools in your preferred development environment.
- Experiment with the tools by completing simple coding tasks and observing the suggestions and completions provided.
Code Completion Challenges
Show steps
Solve a series of coding challenges using AI-driven code completion tools to strengthen your understanding of syntax and best practices.
Browse courses on
Generative AI
Show steps
- Access online coding platforms or IDEs that offer AI-powered code completion tools.
- Select a series of coding challenges or exercises that focus on areas you want to improve.
- Attempt to solve the challenges using AI-driven code completion, paying attention to the suggestions and patterns provided.
- Review your solutions and compare them to the suggested completions, noting the accuracy and efficiency of the AI tools.
AI-assisted Code Review
Show steps
Pair up with a peer and review each other's code using AI-driven code completion tools to identify potential improvements and best practices.
Browse courses on
Generative AI
Show steps
- Find a partner who is also taking the course or has experience with AI-powered code completion tools.
- Exchange code samples that you want to review and provide feedback on.
- Use AI-powered code completion tools to analyze the code, suggest improvements, and identify potential errors or inefficiencies.
- Discuss the suggestions and insights generated by the AI tools and agree on the best course of action to enhance the code quality.
Code Refactoring Project
Show steps
Refactor an existing codebase using AI-powered code completion tools to enhance readability, maintainability, and efficiency.
Browse courses on
Code Completion
Show steps
- Choose an open-source project or a codebase that you have developed earlier.
- Identify areas in the codebase that can benefit from code completion, such as repetitive blocks of code, complex logic, or error-prone sections.
- Use Generative AI tools for code completion to suggest alternative and improved code structures, algorithms, or error handling mechanisms.
- Implement the suggested changes, review the impact on code quality and efficiency, and document the process and the results in a project report.
Custom AI Code Completion Tool
Show steps
Develop your own AI-powered code completion tool tailored to a specific domain or programming language to expand your understanding of the techniques and algorithms involved in code completion.
Browse courses on
Generative AI
Show steps
- Define the scope and functionality of your custom AI code completion tool.
- Gather a dataset of code snippets, documentation, and other relevant materials for training the AI model.
- Choose and implement an appropriate machine learning model for code completion, such as a Transformer-based model or a language model.
- Train the model on the collected dataset and evaluate its performance.
- Integrate the trained model into a user-friendly interface or tool for easy access and use by developers.
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