Generative AI for Software Development Skill Certificate

Generative AI for Software Development Skill Certificate

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 6h 18m | 4.00 GB

Leverage AI in your software development workflow. Enhance your skills as a software developer, grow your career, and stay competitive in this fast-paced industry.

What you’ll learn

  • Learn how LLMs work. By knowing how machine learning systems work, you’ll be able to use them more effectively to support your work as a developer.
  • Experiment quickly. Using LLMs can speed up your ability to prototype and test new features, allowing you to quickly iterate and ship your code.
  • Optimize your code quality. Get to production-ready code faster by working with an LLM to find and fix bugs.
  • Team up with AI on engineering tasks. Break through roadblocks and with your team by leveraging an LLM’s knowledge of development roles and tasks.

Skills you’ll gain

  • Software Engineering
  • Large Language Models
  • Software Development
  • Generative AI
  • Machine Learning

Generative AI is transforming software development by enhancing and augmenting traditional coding practices.

In this Skill Certificate from DeepLearning.AI, you’ll learn from Laurence Moroney, former AI lead at Google, as he guides you through a comprehensive pathway to understand and apply generative AI technologies in real-world software development.

As AI-powered coding tools are set to transform the industry, with Gartner predicting 70% adoption by platform engineering teams by 2027, this program will support you in learning these technologies at all stages of your career. It will show you how to use LLMs to leverage your own experience and knowledge to become a faster, more productive worker. You will be introduced to a new paradigm for software development, where LLMs become invaluable members of your development team by acting as pair coding partners, software testers, security experts, and knowledgeable colleagues.

Go beyond theory and apply your new skills to real-world projects. This hands-on approach ensures you graduate with the practical expertise to leverage generative AI and augment your development workflow.

When you complete the program, you’ll earn a Skill Certificate from DeepLearning.AI, demonstrating your aptitude with the latest GenAI skills and tools to help you advance in your career.

Applied Learning Project

Pair-coding with an LLM to efficiently modify data structures for use in production and at big data scales

Work with an LLM as a skilled software tester to identify bugs, create edge case tests, and update code to correct errors

Implement a functioning local database from scratch, and partner with an LLM to think through software design issues and how to optimize for efficient, secure data access.

Table of Contents

conversation-between-laurence-moroney-and-andrew-ng
in-video-resources_instructions
setting-up-your-jupyter-environment_instructions
essential-reading-engage-directly-with-our-jupyter-and-chatgpt-labs_instructions
module-introduction
configuration-driven-development-overview
choosing-a-configuration-file-format
json-and-pickle
using-the-dall-e-api
implementing-cdd
serializing-results
important-have-questions-issues-or-ideas-join-our-forum_instructions
module-introduction
setting-up-a-simple-database
design-and-implement-a-database-schema
implementing-crud-operations
module-exercise
advanced-querying
databaset-optimization
debugging
graded-lab-social-network-database
module-introduction
gang-of-four-patterns-overview
singletons
patterns-advice-from-an-llm
singleton-for-database-connection-manager
factory-patterns
template-method-pattern
strategy-pattern
course-conclusion
acknowledgments_instructions
optional-opportunity-to-mentor-other-learners_instructions
conversation-between-laurence-moroney-and-andrew-ng
in-video-resources_instructions
setting-up-your-jupyter-environment_instructions
essential-reading-engage-directly-with-our-jupyter-and-chatgpt-labs_instructions
what-is-generative-ai
ai-and-machine-learning
machine-learning-example
supervised-learning
introduction-to-transformers
key-transformer-concepts
important-have-questions-issues-or-ideas-join-our-forum_instructions
transformers-and-code
generating-code-with-chatbots
iterative-prompting
giving-the-llm-feedback
assigning-the-llm-a-role
leveling-up-with-multiple-roles
expert-roles-for-specialized-knowledge
llm-best-practices
data-structures-in-production
arrays
linked-lists
self-paced-exercise-doubly-linked-lists
trees
graphs
graded-lab-graph-algorithms
implementing-algorithms-in-graphs_instructions
hash-tables-and-maps
course-conclusion
acknowledgments_instructions
conversation-between-laurence-moroney-and-andrew-ng
in-video-resources_instructions
setting-up-your-jupyter-environment_instructions
essential-reading-engage-directly-with-our-jupyter-and-chatgpt-labs_instructions
module-introduction
testing-and-debugging-strategies
exploratory-testing
functional-testing
automated-testing
software-performance-testing
security-testing
flask-example-walkthough-optional
analyzing-code-for-security-vulnerabilities
important-have-questions-issues-or-ideas-join-our-forum_instructions
module-introduction
principles-of-good-documentation
inline-comments
documentation-comments
automated-documentation-tools
autodocs-with-sphinx-walkthrough-optional
documentation-in-other-coding-languages
documentation-for-life-in-production
module-introduction
virtual-environments
researching-dependencies
dependency-conflicts
dependencies-and-security
dependency-management-and-other-programming-languages
course-conclusion
acknowledgments_instructions

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