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DeepLearning.AI via Coursera

Introduction to Generative AI for Software Development

4.6668 ratings at Coursera

Overview

This course is designed to enhance your skills by integrating AI chatbots as pair programmers in 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 tasks as a developer.

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

This course assumes you have a background in software development, but are new to using LLMs as part of your development process. By knowing how machine learning systems work, and having 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.

Syllabus 3

  1. Introduction to Generative AI 1.5 hours
  2. Pair-coding with an LLM 2 hours
  3. Leveraging an LLM for code analysis 6 hours

Advantages and disadvantages

Advantages

  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • Andrew Ng and his team are among the clearest AI teachers anywhere.
  • Short courses are made with the companies building the tools (OpenAI, Google, AWS, Hugging Face).
  • From DeepLearning.AI, a well-regarded name.
  • Rated 4.6 out of 5 by 668 learners.
  • Self-paced: start any time.

Disadvantages

  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.
  • Short courses are 1–2 hours: an introduction, not mastery.
  • Some notebooks need a paid Pro plan or your own API key.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

  • Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
  • Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.

Taught by

  • Laurence MoroneyInstructor

DeepLearning.AI is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (90/100). Andrew Ng's courses.

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