Quick Guide & Tips

💻   Accessing Utils File and Helper Functions

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Open"

You will be able to see all the notebook files for the lesson, including any helper functions used in the notebook on the left sidebar. See the following image for the steps above.

🔄   Reset User Workspace

If you need to reset your workspace to its original state, follow these quick steps:

1:   Access the Menu: Look for the three-dot menu (⋮) in the top-right corner of the notebook toolbar.

2:   Restore Original Version: Click on "Restore Original Version" from the dropdown menu.

For more detailed instructions, please visit our Reset Workspace Guide.

💻   Downloading Notebooks

In each notebook on the top menu:

1:   Click on "File"

2:   Then, click on "Download as"

3:   Then, click on "Notebook (.ipynb)"

💻   Uploading Your Files

After following the steps shown in the previous section ("File" => "Open"), then click on "Upload" button to upload your files.

📗   See Your Progress

Once you enroll in this course—or any other short course on the DeepLearning.AI platform—and open it, you can click on 'My Learning' at the top right corner of the desktop view. There, you will be able to see all the short courses you have enrolled in and your progress in each one.

Additionally, your progress in each short course is displayed at the bottom-left corner of the learning page for each course (desktop view).

📱   Features to Use

🎞   Adjust Video Speed: Click on the gear icon (⚙) on the video and then from the Speed option, choose your desired video speed.

🗣   Captions (English and Spanish): Click on the gear icon (⚙) on the video and then from the Captions option, choose to see the captions either in English or Spanish.

🔅   Video Quality: If you do not have access to high-speed internet, click on the gear icon (⚙) on the video and then from Quality, choose the quality that works the best for your Internet speed.

🖥   Picture in Picture (PiP): This feature allows you to continue watching the video when you switch to another browser tab or window. Click on the small rectangle shape on the video to go to PiP mode.

√   Hide and Unhide Lesson Navigation Menu: If you do not have a large screen, you may click on the small hamburger icon beside the title of the course to hide the left-side navigation menu. You can then unhide it by clicking on the same icon again.

🧑   Efficient Learning Tips

The following tips can help you have an efficient learning experience with this short course and other courses.

🧑   Create a Dedicated Study Space: Establish a quiet, organized workspace free from distractions. A dedicated learning environment can significantly improve concentration and overall learning efficiency.

📅   Develop a Consistent Learning Schedule: Consistency is key to learning. Set out specific times in your day for study and make it a routine. Consistent study times help build a habit and improve information retention.

Tip: Set a recurring event and reminder in your calendar, with clear action items, to get regular notifications about your study plans and goals.

☕   Take Regular Breaks: Include short breaks in your study sessions. The Pomodoro Technique, which involves studying for 25 minutes followed by a 5-minute break, can be particularly effective.

💬   Engage with the Community: Participate in forums, discussions, and group activities. Engaging with peers can provide additional insights, create a sense of community, and make learning more enjoyable.

✍   Practice Active Learning: Don't just read or run notebooks or watch the material. Engage actively by taking notes, summarizing what you learn, teaching the concept to someone else, or applying the knowledge in your practical projects.

📚   Enroll in Other Short Courses

Keep learning by enrolling in other short courses. We add new short courses regularly. Visit DeepLearning.AI Short Courses page to see our latest courses and begin learning new topics. 👇

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🙂   Let Us Know What You Think

Your feedback helps us know what you liked and didn't like about the course. We read all your feedback and use them to improve this course and future courses. Please submit your feedback by clicking on "Course Feedback" option at the bottom of the lessons list menu (desktop view).

Also, you are more than welcome to join our community 👉👉 🔗 DeepLearning.AI Forum

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Welcome back!

Hi ,

We'd like to know you better so we can create more relevant courses. What do you do for work?

DeepLearning.AI
Professional CertificateBeginner

Generative AI for Software Development

Instructor: Laurence Moroney

DeepLearning.AI

  • Beginner
  • 50 Video Lessons
  • 4 Code Examples
  • Instructor: Laurence Moroney
    • DeepLearning.AI
    DeepLearning.AI

What you'll learn

  • Integrate Generative AI in Development: Learn to use generative AI tools like GitHub Copilot and ChatGPT from initial design to deployment, enhancing coding efficiency and creativity.

  • Optimize Your Code Quality: Improve your coding skills, whether you’re just starting out and need help with bug fixes or an experienced developer trying to break new ground.

  • Develop Innovative Solutions: Create advanced software solutions using AI for testing, debugging, dependency management, and documentation.

Why Enroll?

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.

Learn practical prompt engineering and pair programming with LLMs like ChatGPT to enhance your software development workflow. Through hands-on projects, you’ll gain techniques for using AI to help with common development tasks – from writing and testing code to creating documentation and managing dependencies. This program teaches you how to effectively prompt LLMs to assist with everything from basic coding tasks to implementing complex design patterns and database architectures.

Designed for both individual developers wanting to boost their productivity and team members looking to integrate AI tools into their development process. You’ll learn specific skills for using LLMs as a coding partner while still maintaining control over code quality and design decisions.

As AI-powered coding tools are set to transform the industry, with Gartner predicting 70% adoption by platform engineering teams by 2027, this course 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.

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.

What you'll learn in this course

  • Configuration-Driven Development (CDD): Understand and implement CDD principles in software design.
  • Database Design and Implementation: Learn to design database schemas, implement CRUD operations, and optimize database performance.
  • Design Patterns: Explore and apply Gang of Four design patterns, including Singleton, Factory, Template Method, and Strategy.
  • API Integration: Work with external APIs like DALL-E for image generation.
  • Data Serialization: Implement file serialization techniques using JSON and Pickle.
  • LLM-Assisted Coding: Leverage Large Language Models as pair programming partners throughout the software development process.

Key technologies and concepts you’ll use

  • Python: The primary programming language used throughout the course
  • SQLAlchemy: ORM for database operations
  • SQLite: Lightweight database for prototyping
  • JSON: Data format for configuration files
  • Pickle: Serialization tool for complex Python objects
  • DALL-E API: For image generation tasks
  • Design Patterns: Singleton, Factory, Template Method, Strategy
  • LLMs (e.g., GPT-4): For code generation and problem-solving assistance

Level up with hands-on projects

  • Build a configurable image generation application using the DALL-E API, implementing CDD principles.
  • Design and implement an e-commerce database system with full CRUD functionality.
  • Develop a financial services application that demonstrates the use of various design patterns.
  • Create and query a social network database as part of a graded exercise.

These projects will allow you to apply concepts of software design, database management, and API integration while using an LLM as a coding assistant.

Build foundational knowledge

  • 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.

Instructor

Laurence Moroney

Laurence Moroney

Former AI Lead at Google

Skills you will gain

Learner reviews from other DeepLearning.AI courses

Selami A.

What I loved about the “AI for Everyone” course was the comprehensive coverage of essential AI topics, guided by the expertise of Andrew Ng. The course provided a clear roadmap for initiating and managing AI projects, from project selection to implementation. It also offered insights into building AI teams and introduced the technical tools necessary for AI success

Chris C.

Simple enough to make it easy to understand in spite of being a complex topic, inspiring speaker. Time well spent, and a good fit with “lifelong learning” approach.

Adeel B.

What stood out to me about this course was the clarity and simplicity with which complex AI concepts were explained. The real-life examples and case studies helped me grasp the practical implications of AI in different sectors. The interactive nature of the course made learning engaging and enjoyable.

Krystal L.

I am an educator and looking to incorporate AI into my career and help my colleagues to do the same. The course did a great job explaining AI concepts to people like myself who are just learning about any of this for the first time.

John S.

I took this course purely out of curiosity. After becoming aware of ChatGPT and Midjourney and then taking a short course on engineering the prompts to get the desired result, I became more intrigued with the topic of AI. I found this most helpful with regards to getting an idea about what AI actually is as opposed to what Hollywood conditioned me to believe it might be.

Muhammad S.

Loved the content. It brought simplicity to the complex topic of AI, separated signal from noise, presented a great flow and covered the most relevant topics.

Andrew’s knowledge and passion about the subject of AI was amazing. It was inspiring to listen to him, even via recorded videos. Its really great to be in this era of technology, as it makes it possible to get access to the wealth of knowledge so easily.

Learner Reviews

Course Outline

Course 1Course 2Course 3

Introduction to Generative AI for Software Development

This course is part of Generative AI for Software Development

Module 1: Introduction to Generative AI
Module 2: Pair-coding with an LLM
Module 3: Leveraging an LLM for code analysis

Frequently Asked Questions

What is the focus of this course?

The course focuses on integrating generative AI tools into software development, covering machine learning techniques, transformer models, iterative code refinement, and advanced data structures.

Who should take this course?

This course is designed for software developers, engineers, and aspiring professionals with intermediate knowledge of software development and a basic understanding of AI concepts. The course is particularly valuable for those looking to enhance their skills in software architecture, database management, and AI integration in development workflows.

How long is the course?

The course is designed to be completed in about a month, with an estimated commitment of 5 hours per week.

What are the prerequisites?

Basic knowledge of software development. Familiarity in one or more programming languages like Python, JavaScript, or C#.

What kind of projects and exercises are included?

Practical, hands-on exercises include implementing linked lists and trees, generating and refining code with AI, and optimizing data structures for performance and security.

How will this course help in my career?

Improve coding efficiency and creativity, tackle complex coding challenges, optimize performance, and ensure security, making you more competitive in the job market.

Can I take this course at my own pace?

Yes, the course is designed to be self-paced.

I have questions about my DeepLearning.AI Pro subscription, whom can I ask?
How much does the DeepLearning.AI Pro membership cost?

The DeepLearning.AI Pro membership costs $25/mo billed annually and $30/mo billed monthly.

More pricing details are available on the membership page.

Important details:

  • All prices are listed in USD
  • Payments are processed securely via Stripe
  • Taxes may apply depending on your location

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