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Introduction to Generative AI for Software Development

Laurence Moroney

This course is designed to enhance your skills by integrating AI chatbots into your development process. You’ll learn about how large language models (LLMs) work and how this general-purpose technology can be applied to common software development tasks to help boost productivity, creativity, and support you in your career.

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This course is designed to enhance your skills by integrating AI chatbots into your development process. You’ll learn about how large language models (LLMs) work and how this general-purpose technology can be applied to common software development tasks to help boost productivity, creativity, and support you in your career.

By the end of this course, you will be able to:

- Understand the differences between machine learning and traditional software development

- Describe how large language models generate text

- Prompt an LLM to assist in the tasks that make up the software developer role

- Guide an LLM to complete a task in a specific way by writing detailed prompts and iterating to improve output

- Leverage the depth of software development knowledge encoded in an LLM by prompting it to assume specific job roles or personas

- Write code quickly using an LLM as a pair-coding partner

- Analyze code for efficiency, security, and performance using an LLM

By knowing how machine learning systems work, and an understanding of how they can be applied in software development, you’ll be able to use them more effectively to support your growth and work as a developer or engineer.

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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops skills in prompting AI chatbots for software development tasks
Teaches underlying concepts of machine learning for software development
Helps learners improve productivity and creativity in software development
Provides a comprehensive overview of AI chatbots in software development
Offers hands-on practice in using AI chatbots for software development

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Generative AI for Software Development with these activities:
Review Software Development Fundamentals
Strengthen your foundational understanding of software development concepts before diving into AI chatbots.
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  • Revisit core programming principles, such as data structures, algorithms, and object-oriented programming.
  • Refresh your knowledge of a programming language, such as Python, which is commonly used for AI chatbots.
Engage in LLM-Focused Study Groups
Collaborate with peers to share knowledge, experiences, and best practices related to LLMs.
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  • Form a study group with other learners interested in LLMs.
  • Establish regular meetings to discuss LLM concepts, applications, and challenges.
  • Share resources, articles, and project ideas with the group.
  • Provide feedback and support to other members of the group.
Practice Prompts for Large Language Models
Sharpen your prompt engineering skills by practicing writing effective prompts for LLMs.
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  • Start with a clear goal in mind for the LLM's output.
  • Use relevant keywords and provide enough context.
  • Break down complex requests into smaller, more manageable tasks.
  • Experiment with different variations of the same prompt.
Four other activities
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Develop a Software Development Plan with LLM Integration
Enhance your software development process by creating a plan that incorporates the use of LLMs.
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  • Analyze your current software development workflow.
  • Identify areas where LLMs can complement or enhance your existing tools and techniques.
  • Develop a phased plan for integrating LLMs into your workflow, starting with low-risk tasks.
  • Monitor the effectiveness of LLM integration and make adjustments as needed.
Explore Code Generation with LLMs
Enhance your understanding of how LLMs can generate code by following guided tutorials.
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  • Identify a specific coding task you want the LLM to perform.
  • Choose a tutorial that aligns with your skill level and the complexity of the task.
  • Follow the tutorial step-by-step, experimenting with different LLM models and prompts.
  • Analyze the generated code, comparing it to manually written code in terms of efficiency and performance.
Contribute to LLM-Related Open-Source Projects
Gain practical experience and contribute to the LLM community by participating in open-source projects.
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  • Identify open-source projects that leverage LLMs or focus on LLM-related topics.
  • Choose a project that aligns with your interests and skills.
  • Review the project's documentation and contribute code, documentation, or other resources.
  • Engage with the project's community through forums or discussion boards.
Build an LLM-Assisted Development Project
Apply your LLM skills in a practical setting by building a project that leverages LLMs.
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  • Define the scope and goals of your project.
  • Identify specific tasks within your project where LLMs can provide assistance.
  • Develop a strategy for integrating LLM-generated content into your project.
  • Evaluate the effectiveness of the LLM's contributions to your project.

Career center

Learners who complete Introduction to Generative AI for Software Development will develop knowledge and skills that may be useful to these careers:

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