Google AI for JavaScript developers with TensorFlow.js from edX

Are you a web engineer, designer, or creative thinker looking to apply AI or use Machine Learning in your next web application but are unsure where to begin? Or maybe you’re overwhelmed by other courses that focus more on the mathematical proofs than actually enabling you to use these new technologies for real world applications? This course offers a solution and the knowledge to be the "missing manual" for JavaScript users without a background in Machine Learning.

Machine Learning (ML) on the web is growing faster than ever so now is the time to take your first steps too. Learn what the difference is between Artificial Intelligence, Machine Learning, and Deep Learning but also how to use such techniques practically through real examples using TensorFlow.js - Google's leading ML library for JavaScript.

Supercharge your next web app with superpowers - from classifying text in a blog post comment to automatically block spam, to using sensors like a webcam on your mobile device to alert you when your dog is on the couch after you left the house. The knowledge you learn could be applied to any business OR creative idea you have for your next project no matter what industry you may be working in.

Better yet, JavaScript is one of few programming languages that can run everywhere enabling you to leverage the knowledge from this course and apply it client side, server side, via native apps, and even IoT devices allowing you to reuse what you learn across multiple environments.

This course aims to educate, inspire, and enable you to rapidly create your next ML powered idea in this rapidly emerging industry while providing you with a solid foundation to understand the field and confidence to explore the industry further.

Web applications are evolving, so sign up, join the fun, and get an edge over the competition. No background in ML is required to take the course. A basic, working knowledge of web technologies such as HTML, CSS, and JavaScript is highly recommended.

What's inside

Learning objectives

Common terms and what they mean
How machine learning works (without formal mathematical definitions)
Overview of the tensorflow.js library
Advantages of using ml in javascript
Ways to consume or create machine learning models
How to use pre-made “off the shelf” models
What tensors are in machine learning
How to use tensors with ml models

How to write a simple custom model
Perceptrons (artificial neuron) and how they work
Linear regression to predict numbers using single neuron
Multi layered perceptrons for handling more complex data
How to use models that use convolutional neural networks for images
How to convert python models to javascript
Transfer learning - reusing existing trained models with your own data
Inspiring projects others are creating to seed your own future ideas

Common terms and what they mean
How machine learning works (without formal mathematical definitions)
Overview of the tensorflow.js library
Advantages of using ml in javascript
Ways to consume or create machine learning models
How to use pre-made “off the shelf” models
What tensors are in machine learning
How to use tensors with ml models
How to write a simple custom model
Perceptrons (artificial neuron) and how they work
Linear regression to predict numbers using single neuron
Multi layered perceptrons for handling more complex data
How to use models that use convolutional neural networks for images
How to convert python models to javascript
Transfer learning - reusing existing trained models with your own data
Inspiring projects others are creating to seed your own future ideas

Syllabus

1. Welcome to TensorFlow.js

1.1 Course overview and how people are applying skills you will learn

1.2 Who is the course aimed at

1.3 Introduce yourself

1.4 What will you be making?

1.5 Your background

2. Introduction to ML & TensorFlow.js

2.1 What's the difference - AI / ML / Deep Learning

2.2 Demystifying Machine Learning

2.3 Test your knowledge

2.4 What is TensorFlow.js

2.5 Three ways to use ML

2.6 Test your knowledge

3. Using Pre-Made models

3.1 What are pre-made models?

3.2 Selecting the right model to use

3.3 Quiz

3.4 Case study - using a pre-made model for object detection

3.5 Make your own smart security camera

3.6 Loading saved TensorFlow.js models directly

3.7 Tensors in Tensors out

3.8 Coding practice

4. Writing custom models

4.1 Rolling your own models

4.2 Starting simple: Predicting a number

4.3 Going deeper: Perceptrons

4.4 Using a perceptron to predict numbers

4.5 Implementing a perceptron for linear regression

4.6 Test your knowledge

4.7 Going deeper: Multi-layered perceptron

4.8 Implementing a multi-layered perceptron

4.9 Training a multi layered perceptron for classification task

4.10 Test your knowledge

4.11 Beyond perceptrons

4.12 Researching other ML architecture types

5. Transfer Learning

5.1 Reusing existing models

5.2 Make Teachable Machine yourself

5.3 Project ideas

5.4 Test your knowledge

6. Reusing models from Python

6.1 Benefits of model reuse

6.2 Converting Python saved models6.10 Test knowledge

6.3 Convert a model yourself

6.4 Comment Spam detection

6.5 Choosing an appropriate model

6.6 Use converted model to check spam in real application

6.7 Dealing with edge cases

6.8 Retraining a model to deal with custom edge cases

6.9 What models would you convert?

7. To the future and beyond

7.1 Machine Learning as a Web Engineer

7.2 Find a friend to continue hacking

7.3 Course summary and how to join the TensorFlow.js community

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches the core fundamentals of ML and Tensorflow.js, which is an essential library for JavaScript developers seeking to leverage ML

Instructed by Jason Mayes, who has extensive experience in Machine Learning and web engineering, ensuring learners are guided by an expert in the field

Suitable for aspiring web developers and designers who lack a strong background in ML, enabling them to bridge this knowledge gap and expand their skillset

Offers hands-on, practical examples that demonstrate the real-world applications of ML in web development, making learning immediately applicable

Covers a range of ML concepts, including pre-made models, custom model creation, and transfer learning, providing a comprehensive foundation in ML

Promotes creativity and innovation by showcasing inspiring projects created using the skills taught in the course, encouraging learners to think outside the box

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 Google AI for JavaScript developers with TensorFlow.js with these activities:

Review JavaScript Fundamentals

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Reinforce your foundational understanding of JavaScript, including syntax, data types, and control flow.

Browse courses on JavaScript Fundamentals

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Review core JavaScript concepts
Practice writing simple JavaScript programs

Connect with a Mentor in the Machine Learning Field

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Accelerate your learning and career growth by seeking guidance from an experienced machine learning professional.

Browse courses on Mentorship

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Identify potential mentors
Reach out and introduce yourself
Establish a regular communication schedule

Curate a Collection of Machine Learning Resources

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Enhance your learning experience by compiling a comprehensive list of helpful machine learning resources, including books, articles, websites, and tutorials.

Browse courses on Learning Materials

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Identify and gather relevant resources
Organize the materials by topic or category
Share your compilation with other students

Five other activities

Expand to see all activities and additional details

Show all eight activities

Follow Along with TensorFlow.js Tutorials

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Complement the course content by following step-by-step tutorials from the TensorFlow.js website or other reputable sources.

Browse courses on TensorFlow.js

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Identify relevant TensorFlow.js tutorials
Follow the tutorials and implement the examples
Experiment with different model structures

Solve Coding Challenges on LeetCode

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Sharpen your problem-solving skills and cement your understanding of machine learning concepts by solving coding challenges related to ML.

Browse courses on Data Structures

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Identify appropriate LeetCode problems
Practice solving the problems
Analyze your solutions and identify areas for improvement

Contribute to an Open-Source Machine Learning Project

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Gain practical experience and give back to the community by contributing to an open-source machine learning project, such as TensorFlow.js or PyTorch.

Browse courses on Open Source

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Identify a project that aligns with your interests
Learn about the project's codebase and contribution guidelines
Make a meaningful contribution

Build a Simple Image Classifier

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Apply the concepts you've learned by building a real-world machine learning project from scratch, such as a mobile app that can classify images.

Browse courses on Image Classification

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Define the problem and gather data
Choose an appropriate model
Train and evaluate the model
Integrate the model into your project

Participate in a Machine Learning Hackathon

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Challenge yourself and expand your knowledge by participating in a machine learning hackathon, where you can collaborate with others and build innovative ML solutions.

Show steps

Find a hackathon that aligns with your interests
Form a team or work independently
Develop a creative and impactful project

Career center

Learners who complete Google AI for JavaScript developers with TensorFlow.js will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers create and deploy machine learning models to solve business problems. They work with data scientists to understand the business need and to develop the appropriate model. Machine Learning Engineers also work with software engineers to integrate the model into the production environment. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course is a valuable resource for anyone who wants to become a Machine Learning Engineer, and it is particularly relevant for JavaScript developers who want to use machine learning in their web applications.

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Data Scientist

Data Scientists use data to solve business problems. They collect, clean, and analyze data to identify patterns and trends. Data Scientists also develop and deploy machine learning models to make predictions and recommendations. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course is a valuable resource for anyone who wants to become a Data Scientist, and it is particularly relevant for JavaScript developers who want to use machine learning in their web applications.

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Software Engineer

Software Engineers design, develop, and maintain software systems. They work with users to understand the requirements of the system and to develop the appropriate software solution. Software Engineers also work with other engineers to integrate the software system into the overall system. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course is a valuable resource for anyone who wants to become a Software Engineer, and it is particularly relevant for JavaScript developers who want to use machine learning in their web applications.

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Web Developer

Web Developers design and develop websites and web applications. They work with users to understand the requirements of the website or application and to develop the appropriate solution. Web Developers also work with other developers to integrate the website or application into the overall system. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course is a valuable resource for anyone who wants to become a Web Developer, and it is particularly relevant for JavaScript developers who want to use machine learning in their web applications.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify patterns and trends. They also develop and deploy machine learning models to make predictions and recommendations. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course is a valuable resource for anyone who wants to become a Data Analyst, and it is particularly relevant for JavaScript developers who want to use machine learning in their web applications.

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Business Analyst

Business Analysts work with businesses to understand their needs and to develop solutions to their problems. They use data analysis and modeling to identify opportunities and to develop recommendations. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Business Analysts who want to use machine learning to improve their work.

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Product Manager

Product Managers work with customers and other stakeholders to define the requirements for a product. They also work with engineers and designers to develop the product and to bring it to market. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Product Managers who want to use machine learning to improve their products.

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Project Manager

Project Managers plan and execute projects. They work with stakeholders to define the project scope and to develop the project plan. They also work with the project team to execute the project and to deliver the project results. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Project Managers who want to use machine learning to improve their project management skills.

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Technical Writer

Technical Writers create documentation for software and other technical products. They work with engineers and other technical staff to understand the product and to develop the appropriate documentation. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Technical Writers who want to learn about machine learning so that they can better document products that use machine learning.

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Teacher

Teachers teach students about a variety of subjects. They work with students to develop their knowledge and skills. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Teachers who want to learn about machine learning so that they can teach their students about this important topic.

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Consultant

Consultants provide advice to businesses and other organizations. They work with clients to identify opportunities and to develop solutions to their problems. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Consultants who want to use machine learning to improve their consulting services.

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Researcher

Researchers conduct research to advance knowledge and understanding. They work in a variety of fields, including science, engineering, and medicine. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Researchers who want to use machine learning to improve their research.

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Entrepreneur

Entrepreneurs start and run their own businesses. They work with customers to identify opportunities and to develop products and services that meet those needs. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Entrepreneurs who want to use machine learning to improve their businesses.

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Artist

Artists create works of art. They work with a variety of materials, including paint, clay, and metal. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Artists who want to use machine learning to create new and innovative works of art.

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Musician

Musicians create and perform music. They work with a variety of instruments, including guitars, drums, and keyboards. This course provides an overview of machine learning concepts and techniques, and it teaches how to use TensorFlow.js to develop and deploy machine learning models. This course may be useful for Musicians who want to use machine learning to create new and innovative music.

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