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10 Free Online Courses Offered By Google With Certification
Google is currently offering free online courses with certification in various fields. Irrespective of your location around the globe, you are eligible to take these free courses and get your certificate after completion. In this article, scholarship180.com will guide you through the ten(10) free online courses that you can enroll in your comfort zone, complete, and get a certificate/badge. The guide includes: the courses available, modules, duration of completion, and how to enroll.
1. Machine Learning Crash Course
This course consists of 12 modules that can be completed in 15 hours using video explainers of ML concepts, real-world examples, and interactive visualizations.
Note that:
Because each module in the Machine Learning Crash Course is self-contained, you can jump straight to the subjects you wish to learn if you already know a lot about machine learning. We advise completing the modules listed below if you're new to machine learning.
There are 12 Modules under this course:
A. ML Models:
1. linear regression
2. Logistic regression
3. classification
B. Data:
4. Working with numerical data
5. Working with categorical data
10. Production ML systems
11. AutoML
12. ML fairness
To take this course, Click Here
2. Responsible AI: Applying AI Principles with Google Cloud
Note that it takes only 2 hours to complete this course.
It consists of 7 modules, with access to a certificate after completing the 7 modules and earning a badge.
The Seven (7) modules are:
A. Introduction: This will take you through
- The impact of AI technology and Google's approach to responsible AI
- Introduced to Google's AI Principles.
B. The business case for responsible AI
C. AI’s Technical Considerations and Ethical Concerns
D. Creating AI Principles
E. Operationalizing AI Principles: Setting Up and Running Reviews
F. Operationalizing AI Principles: Issue Spotting and Lessons Learned
G. Continuing the Journey Towards Responsible AI
CLICK HERE TO TAKE THIS COURSE FOR FREE
3. Machine Learning
The main aim of this course is to explore ML techniques and innovative ML approaches like deep learning and neural networks as well.
Some Modules include:
A. Introduction to ML, under which you will learn:
- What is machine learning?
- The 7 steps of machine learning, part 1 and 2
- The teachable machine
B. Background of ML, under which you will also learn:
- What is Kaggle? And getting started on Kaggle.
- Courses on Kaggle (Python), etc
C. Pretrained Models under which you will learn Machine Learning APIs by example, explore the galaxy of images with cloud vision API, machine learning APIs, using machine learning ti enhance your Apps, etc.
D. AutoML
You will learn AutoML vision, part 1 and 2, AutoML tables, AutoML vision in action on GCP, etc.
E. How is ML done
F. Beginner projects
G. Advanced topics
CLICK HERE TO TAKE THE COURSE ONLINE
4. Prompt Design in Vertex AI
You will get knowledge of multimodal generating approaches within Vertex AI, picture analysis, and prompt engineering after finishing this course. Learn how to create compelling prompts, direct the production of generative AI, and use Gemini models in practical marketing situations.
It will take you only 3 hours and 45 minutes to complete this course.
Modules under the course include:
- Generative AI with Vertex AI: Prompt Design
- Get Started with Vertex AI Studio
- Getting Started with Google Generative AI Using the Gen AI SDK
- Prompt Design in Vertex AI: Challenge Lab
To take this course, click HERE
5. Smart Analytics, Machine Learning, and AI on Google Cloud
This course explains how to incorporate machine learning into Google Cloud data pipelines. This course covers AutoML with little or no customisation. This lecture covers Notebooks and BigQuery machine learning (BigQuery ML), which provide more specialized machine learning capabilities. This course also discusses how to use Vertex AI to productionize machine learning solutions.
The modules include:
- General Introduction to the course and agenda
- Introduction to Analytics and AI
- Prebuilt ML Model APIs for Unstructured Data
- Big Data Analytics with Notebooks
- Production ML Pipelines
- Custom Model Building with SQL in BigQuery ML
- Custom Model Building with Vertex AI AutoML
- Summary of what has been taught
Recommended: UCC Postgraduate Distance Programs Admission Forms for 2025/2026 and How to Apply
6. Introduction to Responsible AI
It takes only 30 minutes to complete this course.
This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in its products. It also introduces Google's 7 AI principles.
- You go through one module, which is a 9-minute Video Introduction to Responsible AI
- After the video, you then take a 20-minute Quiz on Introduction to Responsible AI
Apply Here
7. Google Cloud Big Data and Machine Learning Fundamentals
It takes five (5) hours to complete this course.
This course introduces Google Cloud's big data and machine learning technologies and services for the data-to-AI lifecycle. It delves into the steps, problems, and advantages of using Vertex AI on Google Cloud to develop a big data pipeline and machine learning models.
Modules include:
- Introduction to the course
- Big Data and Machine Learning on Google Cloud
- Data Engineering for Streaming Data
- Big Data with BigQuery
- Machine Learning Options on Google Cloud
- The Machine Learning Workflow with Vertex AI
- Summary of all that has been taught
Click HERE to apply
8. Integrate Generative AI Into Your Data Workflow
This learning route is intended for data professionals who wish to include generative AI into their workflow. Discover how to leverage BigQuery Machine Learning for inference, interact directly with Gemini models in BigQuery, and increase your productivity with Gemini's help. Finally, put your knowledge to the test by building machine learning models using BigQuery ML in a hands-on lab.
Modules include:
- Gemini for Data Scientists and Analysts
- Using BigQuery Machine Learning for Inference
- Work with Gemini Models in BigQuery
- Boost Productivity with Gemini in BigQuery
- Create ML Models with BigQuery ML
9. Introduction to Large Language Models
It takes only 1 hour to complete this course.
This is an introduction micro-learning course that explains what large language models (LLMs) are, what use cases they may be used for, and how prompt tuning can be used to improve LLM performance. It also covers Google tools for creating your own Gen AI applications.
Modules to complete:
- Introduction to Large Language Models, video introduction
- Introduction to Large Language Models, document/reading introduction
- Introduction to Large Language Models-Quiz
To apply for this course, Click Here
10. Generative AI for Educators
It will take you two hours to complete this short course.
This course will teach you about generative AI, a sort of AI that generates new content such as writing, graphics, and other media. You'll learn how to use generative AI technologies to help you save time on daily tasks, personalize training to match student needs, and improve classes and activities in novel ways. Gemini and ChatGPT are examples.
- Explore the course overview
- Investigate the potential of AI in your practice
- How to write an AI prompt
- Iterate to refine prompts
- Write an original prompt and evaluate its output
- Prepare to incorporate outputs into your work
- Save time on everyday tasks
- Differentiate instruction to meet student needs
- Develop your own instructional resource using an AI tool
- Enhance lessons and activities in creative ways
- Understand AI in your world
- Discover generative AI and AI tools
- Ensure responsible use of AI
Click here to read more and apply for this course.
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