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Introduction to Vertex AI

Fractal Analytics

Welcome to "Introduction to Vertex AI"!

In this concise yet impactful microlearning course spanning around 4 hours, we're diving into the world of Vertex AI to equip you with fundamental insights and practical skills.

Read more

Welcome to "Introduction to Vertex AI"!

In this concise yet impactful microlearning course spanning around 4 hours, we're diving into the world of Vertex AI to equip you with fundamental insights and practical skills.

We'll unravel the essentials of Vertex AI, guiding you through the interface to empower you to navigate this powerful platform seamlessly. Get ready to grasp strategic insights that will enable you to effectively harness the capabilities of Vertex AI in your projects.

The course is best suited for aspiring data scientists, machine learning enthusiasts, and professionals eager to harness the potential of AI.

Understanding of Programming, Understanding of AI, and GenAI technology, and understanding Cloud computing, ML platform, DevOps, or LLMOps would be an added advantage.

You'll walk away with a clear understanding of Vertex.AI's basics, mastering its interface, and acquiring strategic insights to leverage this tool effectively. Elevate your AI journey and stay ahead in the dynamic landscape of machine learning with "Introduction to Vertex AI."

Let's get started!

Note: To be able to explore Vertex AI and its features, you would need a Gmail account and Vertex AI access. In case you want to create a free trial account before you start, you can follow the link (https://cloud.google.com/vertex-ai?hl=en) and create your account. Please read the information page before

Enroll now

What's inside

Syllabus

Course Introduction
This module is designed to provide a comprehensive understanding of Vertex AI, a powerful and unified platform for machine learning. Participants will gain insights into the fundamental concepts, components, and applications of Vertex AI, equipping them with the knowledge needed to leverage its capabilities in real-world scenarios.
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Exploring Vertex AI
This module provides a comprehensive exploration of Vertex AI platform, emphasizing its interface, key components, and practical applications in developing AI/ML solutions. Participants will gain insights into foundational models, their advantages, and the pivotal role of Vertex AI in enhancing machine learning operations (MLOps).

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops proficiency in using Vertex.AI and its components
Taught by Fractal Analytics, a leader in applied AI
Useful for beginners in data science and machine learning
Provides a high-level overview of Vertex.AI
Recommended for those with some background in programming and AI
Course duration is relatively short

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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 Introduction to Vertex AI with these activities:
Review AI Fundamentals
Reinforce your foundational knowledge in AI and Machine Learning to enhance your comprehension of Vertex AI's capabilities.
Browse courses on Machine Learning
Show steps
  • Revisit introductory materials on AI and ML concepts.
  • Review key algorithms and techniques used in ML.
  • Practice implementing basic ML models in a programming language.
Review Cloud Computing
Sharpen your understanding of cloud computing fundamentals to enhance your engagement with Vertex AI's interface.
Browse courses on Cloud Computing
Show steps
  • Revisit concepts of cloud computing, including its types (IaaS, PaaS, SaaS) and benefits.
  • Review case studies and examples of successful cloud computing implementations.
  • Explore key cloud computing providers and their offerings, comparing features and pricing.
Explore Vertex AI's Documentation and Tutorials
Delve deeper into Vertex AI's capabilities by delving into its comprehensive documentation and learning from expert-led tutorials.
Show steps
  • Browse Vertex AI's documentation to understand its features and offerings.
  • Follow guided tutorials that demonstrate how to use Vertex AI for common tasks, such as building and deploying machine learning models.
  • Refer to Vertex AI's knowledge base and ask questions in the community forum for additional support.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Attend a Vertex AI Workshop or Webinar
Engage with industry experts and fellow learners in a workshop or webinar dedicated to Vertex AI, expanding your knowledge and network.
Show steps
  • Search for upcoming Vertex AI workshops or webinars hosted by Google Cloud or other organizations.
  • Register for a workshop or webinar that aligns with your interests and learning goals.
  • Attend the workshop or webinar, actively participate in discussions, and ask questions to clarify concepts.
Compile Resources on Vertex AI
Solidify your understanding by organizing and reviewing a collection of resources related to Vertex AI, including documentation, tutorials, and best practices.
Show steps
  • Gather resources from various sources, such as Vertex AI's documentation, online forums, and industry blogs.
  • Categorize and organize these resources based on topics or themes.
  • Create a central repository or document where these resources can be easily accessed and reviewed.
Explore Vertex AI Tutorials
Deepen your understanding of Vertex AI by working through interactive tutorials and hands-on exercises.
Show steps
  • Access the Vertex AI documentation and tutorials.
  • Select a tutorial that aligns with your learning goals.
  • Follow the step-by-step instructions and complete the exercises.
Practice with Vertex AI
Solidify your understanding of Vertex AI's features and functionality by working on practical exercises.
Show steps
  • Set up a Vertex AI project and create a dataset.
  • Build and train a machine learning model using Vertex AI's AutoML capabilities.
  • Deploy and monitor your model using Vertex AI's MLOps tools.
Build a Simple Machine Learning Model using Vertex AI
Apply your Vertex AI skills to a practical project, solidifying your understanding and boosting your confidence.
Show steps
  • Choose a simple machine learning task, such as image classification or text sentiment analysis.
  • Prepare your training data and create a Vertex AI dataset.
  • Train a machine learning model using Vertex AI's AutoML or custom training options.
  • Evaluate the performance of your model and make adjustments as needed.
  • Deploy your model and make predictions.
Contribute to Vertex AI's Open-Source Projects
Deepen your understanding of Vertex AI and contribute to its development by participating in its open-source community.
Show steps
  • Explore Vertex AI's open-source projects on platforms like GitHub.
  • Identify areas where you can contribute based on your skills and interests, such as code improvements, documentation updates, or issue reporting.
  • Follow the project's contribution guidelines and submit a pull request with your modifications or suggestions.
Mentor a Peer in Vertex AI
Reinforce your Vertex AI knowledge by guiding a peer who is also learning the platform, fostering a collaborative learning environment.
Show steps
  • Identify a peer who is interested in learning about Vertex AI and is willing to receive guidance.
  • Establish a регуляр meeting time to provide mentorship and answer their questions.
  • Share your experiences and insights on using Vertex AI effectively.
Develop a Presentation on Vertex AI
Enhance your communication and presentation skills while solidifying your understanding of Vertex AI by creating a presentation that highlights its key concepts and applications.
Show steps
  • Research and gather information about Vertex AI's features, capabilities, and use cases.
  • Design and create a visually appealing and informative presentation, incorporating examples and case studies to illustrate key points.
  • Practice delivering your presentation to refine your communication and presentation skills.
Participate in a Vertex AI Hackathon or Competition
Challenge yourself and showcase your Vertex AI skills by participating in a hackathon or competition, fostering innovation and problem-solving.
Show steps
  • Search for upcoming Vertex AI hackathons or competitions and identify one that aligns with your interests and skill level.
  • Form a team or participate individually and prepare to dedicate time and effort to the challenge.
  • Develop a creative and innovative solution using Vertex AI to address the challenge.

Career center

Learners who complete Introduction to Vertex AI will develop knowledge and skills that may be useful to these careers:
AI Engineer
An AI Engineer designs, develops, and deploys artificial intelligence solutions. This course, "Introduction to Vertex AI," can help you build a foundation in AI and machine learning, providing you with the skills needed to succeed in this role. You will learn about the key components and applications of Vertex AI, as well as how to use it to develop and deploy AI/ML solutions.
Machine Learning Engineer
A Machine Learning Engineer develops and maintains machine learning models. This course, "Introduction to Vertex AI," will provide you with a comprehensive understanding of Vertex AI and how it can be used to develop and deploy machine learning models. You will learn about the different types of machine learning models, how to train and evaluate them, and how to deploy them to production.
Data Scientist
A Data Scientist uses data to solve business problems. This course, "Introduction to Vertex AI," will provide you with the skills needed to use Vertex AI to analyze data, build machine learning models, and make predictions. You will learn about the different types of data analysis techniques, how to use Vertex AI to perform data analysis, and how to communicate your findings to stakeholders.
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course, "Introduction to Vertex AI," may be useful for Software Engineers who want to learn more about developing and deploying AI/ML solutions. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to integrate AI/ML into software systems.
Product Manager
A Product Manager manages the development and launch of products. This course, "Introduction to Vertex AI," may be useful for Product Managers who want to learn more about developing and launching AI/ML products. You will learn about the different types of AI/ML products, how to use Vertex AI to develop and launch them, and how to market and sell AI/ML products.
Business Analyst
A Business Analyst analyzes business processes and systems to identify opportunities for improvement. This course, "Introduction to Vertex AI," may be useful for Business Analysts who want to learn more about using AI/ML to improve business processes. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to identify opportunities for business improvement.
Data Analyst
A Data Analyst analyzes data to identify trends and patterns. This course, "Introduction to Vertex AI," may be useful for Data Analysts who want to learn more about using AI/ML to analyze data. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to identify trends and patterns in data.
Statistician
A Statistician collects, analyzes, and interprets data. This course, "Introduction to Vertex AI," may be useful for Statisticians who want to learn more about using AI/ML to analyze data. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to analyze data and draw conclusions.
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve business problems. This course, "Introduction to Vertex AI," may be useful for Operations Research Analysts who want to learn more about using AI/ML to solve business problems. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to solve business problems.
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations. This course, "Introduction to Vertex AI," may be useful for Financial Analysts who want to learn more about using AI/ML to analyze financial data. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to analyze financial data and make investment recommendations.
Management Consultant
A Management Consultant helps businesses improve their performance. This course, "Introduction to Vertex AI," may be useful for Management Consultants who want to learn more about using AI/ML to improve business performance. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to identify opportunities for business improvement.
Marketing Manager
A Marketing Manager develops and executes marketing campaigns to promote products and services. This course, "Introduction to Vertex AI," may be useful for Marketing Managers who want to learn more about using AI/ML to develop and execute marketing campaigns. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to target and reach customers.
Sales Manager
A Sales Manager develops and executes sales strategies to sell products and services. This course, "Introduction to Vertex AI," may be useful for Sales Managers who want to learn more about using AI/ML to develop and execute sales strategies. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to target and reach customers.
Customer Success Manager
A Customer Success Manager ensures that customers are satisfied with a company's products and services. This course, "Introduction to Vertex AI," may be useful for Customer Success Managers who want to learn more about using AI/ML to improve customer satisfaction. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to use AI/ML to identify and resolve customer issues.
Technical Writer
A Technical Writer creates technical documentation for products and services. This course, "Introduction to Vertex AI," may be useful for Technical Writers who want to learn more about AI/ML. You will learn about the different types of AI/ML models, how to use Vertex AI to develop and deploy them, and how to write technical documentation for AI/ML products and services.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Vertex AI .
This practical guide offers hands-on experience with machine learning techniques using popular Python libraries. It covers supervised and unsupervised learning, feature engineering, and model evaluation, making it an excellent resource for gaining practical skills in machine learning.
This beginner-friendly book provides a gentle introduction to deep learning concepts and techniques using Python. It covers neural networks, convolutional neural networks, and recurrent neural networks, making it a great starting point for those interested in exploring deep learning.
This classic textbook provides a comprehensive treatment of pattern recognition and machine learning. It covers topics such as statistical models, Bayesian inference, and neural networks, making it a valuable resource for gaining a strong theoretical foundation in machine learning.
This textbook focuses on the algorithmic aspects of machine learning. It covers topics such as decision trees, support vector machines, and clustering algorithms, making it a valuable resource for understanding the mathematical underpinnings of machine learning.
This practical guide provides a hands-on approach to machine learning for practitioners with a hacking mindset. It covers topics such as data exploration, model building, and deployment, making it a valuable resource for those interested in applying machine learning techniques in real-world scenarios.
This practical guide provides a hands-on approach to machine learning using Python. It covers topics such as data preparation, feature engineering, and model evaluation, making it a valuable resource for gaining practical skills in machine learning.
This thought-provoking book explores the ethical and societal implications of AI. It discusses the potential risks and benefits of AI and argues for the importance of developing AI systems that are aligned with human values.
This comprehensive book provides a comprehensive overview of the history and future of AI. It discusses the different approaches to AI and argues that the development of a master algorithm that can solve any problem is the key to unlocking the full potential of AI.

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