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. 👇

👉👉 🔗 DeepLearning.AI – All Short Courses [+]

🙂   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

AI for Good

Instructor: Robert Monarch

DeepLearning.AI

What you'll learn

  • Master a step-by-step framework for the development of AI projects.

  • Analyze data and build AI models for projects focused on air quality, wind energy, biodiversity monitoring, and disaster management.

  • Explore real-world case studies related to public health, climate change, and disaster management.

Learn through real-world projects

Develop an AI model to make wind power generation more predictable by providing forecasts 24 hours into the future.

Develop an AI model to make wind power generation more predictable by providing forecasts 24 hours into the future.

Use neural networks and other AI techniques to estimate air quality throughout the city of Bogotá, Colombia.

Use neural networks and other AI techniques to estimate air quality throughout the city of Bogotá, Colombia.

Build an image classification pipeline to perform damage assessment using satellite images taken after Hurricane Harvey in the U.S. in 2017.

Build an image classification pipeline to perform damage assessment using satellite images taken after Hurricane Harvey in the U.S. in 2017.

Use natural language processing techniques to analyze trends in a corpus of text messages sent in the aftermath of the 2010 earthquake in Haiti.

Use natural language processing techniques to analyze trends in a corpus of text messages sent in the aftermath of the 2010 earthquake in Haiti.

Apply computer vision techniques to detect and classify animals for the purpose of biodiversity monitoring.

Apply computer vision techniques to detect and classify animals for the purpose of biodiversity monitoring.

Course Outline

Course 1Course 2Course 3

AI and Public Health

This course is part of AI for Good

Week 1: Introduction to AI for Good
Week 2: AI for Good Project Framework
Week 3: Air Quality in Bogotá Colombia

Instructor

Robert Monarch

Robert Monarch

In partnership with Microsoft’s AI for Good Lab

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These courses were built in partnership with researchers at the Microsoft AI for Good Lab who offered their subject matter expertise throughout the development of the program.

Who should join?

The AI for Good Specialization is designed to be accessible for everyone. We recommend some experience working with data, and performing some basic analysis on your data using tools such as spreadsheets. Whether you’re a student, professional, or someone passionate about making a positive impact on society and the environment, this program provides the tools and knowledge you will need to work on AI for Good initiatives.

Skills you will gain

Learner reviews

Alex F.

I found the AI and Climate Change course extremely interesting and useful. It was a unique combination of two of the most important topics of our time – artificial intelligence and climate change. The course material was deep and insightful, providing me with valuable knowledge and practical skills. I learnt how to use AI to analyse and predict climate change, which I am sure will be an important tool in my future career. Overall, I highly recommend this course to anyone interested in AI and climate change.

Vinay K.

I was always interested in climate change and have been involved in Climate Tech startups in the past. This course has inspired me to consider a new AI tech startup in the area. Appreciate your guidance and explaining the case studies that can help me formulate a few ideas of my own.

David M.

I deeply appreciate your comments about how defining the problem you’re trying to solve can take weeks or months, and also appreciated the inclusion that the system you built did not work out in the end in AI and Public Health. Both are excellent lessons for students to learn.

The lab notebooks are wonderfully clear, and there are some neat techniques in your utils.py files.

Overall, it was a great course. 

David L.

This is a fantastic course. Really inspirational. And the code is an excellent way to learn how to sustainably fish for yourself! Thanks and all the best, David

Darshan D.

I am a mother of 2 teenager girls and we all are involved in finding solutions for problems defined under the UN sustainable goal development.

I loved the course, you made it so easy to follow along with Python code and through project-based learning.

Learner Reviews

Course Slides

You can download the annotated version of the course slides below.

*Note: The slides might not reflect the latest course video slides. Please refer to the lecture videos for the most up-to-date information. We encourage you to make your own notes.

Download The Course Slides

Frequently Asked Questions

Why should I take this specialization?

Whether you’re a student, professional, or someone passionate about making a positive impact on society and the environment, this program provides the tools and knowledge you will need to work on AI for Good initiatives.

What background knowledge is necessary for AI for Good?

This is a beginner-friendly specialization with minimal background knowledge required. Some prior experience in working with data (spreadsheets, etc) is recommended. Python will be used for ungraded labs, but previous experience is not required. This is a great place to start if you’re new to AI and want to learn how it can be applied to real-world challenges.

I don’t have any programming experience, can I take this specialization?

Yes. Programming experience is not required to take this course.

I have intermediate Python experience, is this specialization for me?

If you’re looking to apply those skills in an AI for Good project, then yes! Although the labs for this specialization will be beginner-level, you’ll be able to dig into the code behind each case study and get more creative and manipulate the data and models used in this specialization in more advanced ways.

I’m looking for a course that will help me build my technical skills in AI, is AI for Good for me?

If you’re looking for only AI skill-building, we recommend starting with AI for Everyone or the Machine Learning Specialization. AI for Good is designed to build conceptual skills in AI, and focuses on their use in AI for Good contexts.

Do I need to take the courses in a specific order?

We recommend taking the courses in the prescribed order for a logical and consistent learning experience.

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
Will I receive a certificate at the end of the specialization?

You will receive a certificate at the end of each course if you complete all the quizzes and assessments. If you complete all 3 courses in the Specialization, you will also receive an additional certificate showing that you completed the entire Specialization.

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