Introduction to AI and Machine Learning on GC

What's inside

Syllabus

Introduction

Ce module a pour but d'aider les participants à explorer les outils de développement d'IA disponibles sur Google Cloud. Il présente également la structure du cours, qui repose sur un framework d'IA à trois couches sur Google Cloud.

Éléments de base de l'IA

Ce module présente les éléments de base de l'IA, comme l'infrastructure cloud de calcul et de stockage. Il aborde également les données et produits de développement d'IA principaux sur Google Cloud. Enfin, il explique comment utiliser BigQuery ML pour créer un modèle de ML afin de faciliter la transition des données vers l'IA.

Options de développement d'IA

Ce module explore les différentes options permettant de développer un projet de ML sur Google Cloud : les solutions prêtes à l'emploi telles que les API pré-entraînées, les solutions sans code ou nécessitant peu de programmation comme AutoML, ou encore les solutions basées sur du code telles que l'entraînement personnalisé. Il compare les avantages et les inconvénients de chaque option pour aider les utilisateurs à choisir les outils de développement adéquats.

Workflow de développement d'IA

Ce module présente l'intégralité d'un workflow de ML : préparation des données, développement du modèle et inférence sur Vertex AI. Il explique également comment convertir le workflow en pipeline automatisé en utilisant Vertex AI Pipelines.

IA générative

Ce module présente l'IA générative (la dernière avancée en matière d'IA) et les grands modèles de langage ou LLM (la technologie qui alimente ce type d'IA). Il explore également différents outils de développement d'IA générative disponibles sur Google Cloud, tels que Generative AI Studio et Model Garden. Enfin, il traite des solutions d'IA ainsi que des fonctionnalités d'IA générative intégrées.

Résumé

Ce module propose une synthèse du cours articulée autour des concepts, outils, technologies et produits les plus importants.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Valorise ses outils de développement d'IA disponibles sur Google Cloud

Approfondit les bases de l'IA, essentielles pour de nombreux secteurs

Propose différentes options de développement d'IA adaptées à chaque objectif

Accompagne l'utilisateur tout au long du workflow de développement d'IA, de la préparation des données au déploiement du modèle

Présente l'IA générative, une avancée majeure dans le domaine de l'IA

Intègre des solutions d'IA et des fonctionnalités d'IA générative prêtes à l'emploi

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 AI and Machine Learning on GC - Français with these activities:

Review Basics of Machine Learning

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Provides a helpful refresher for foundational machine learning concepts.

Browse courses on Machine Learning Basics

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Read through online resources or books covering the fundamentals of machine learning.
Work through practice problems and exercises to test understanding.

Review basic AI and ML concepts

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Review the foundational concepts of AI and ML to ensure a solid understanding before delving into the course material.

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Read through materials on AI and ML from reputable sources
Attend introductory workshops or webinars on AI and ML
Complete online tutorials on AI and ML concepts

Follow tutorials on using Google Cloud AI Platform

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Enhance your understanding of Google Cloud AI Platform's tools and services through practical hands-on tutorials.

Browse courses on Google Cloud AI Platform

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Explore and choose relevant tutorials from Google Cloud's documentation
Follow the tutorials step-by-step and experiment with the provided examples
Troubleshoot any issues encountered during the tutorials

Eight other activities

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Follow Video Tutorials on Google Cloud AI

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Offers practical guidance through step-by-step video instructions.

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Find video tutorials on Google Cloud AI.
Follow the instructions in the tutorials to build and train models.

Participate in Online Discussion Forums

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Fosters collaboration and exchange of ideas with fellow learners.

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Join online discussion forums related to the course.
Post questions and share insights.
Engage with others and provide support.

Practice building and deploying ML models on Google Cloud

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Reinforce your ML development skills by practicing building and deploying models on Google Cloud.

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Create a project on Google Cloud and set up the necessary infrastructure
Use AutoML or custom code to build and train ML models
Deploy the trained models and evaluate their performance
Troubleshoot and optimize the models as needed

Create a Sample ML Project

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Provides hands-on experience in applying ML concepts to real-world problems.

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Define a problem statement.
Collect and prepare a dataset.
Choose an ML algorithm and train a model.
Evaluate and refine the model.

Write a blog post or article on an AI or ML topic

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Deepen your understanding of AI and ML by researching a specific topic and sharing your insights through writing.

Browse courses on AI Applications

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Choose an AI or ML topic that interests you and aligns with the course
Research the topic thoroughly using reputable sources
Organize your thoughts and write a well-structured blog post or article
Proofread and edit your writing for clarity and accuracy
Publish your blog post or article on an online platform

Mentor junior or beginner learners in AI and ML

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Solidify your understanding of AI and ML by helping others learn and grow in these fields.

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Volunteer or find opportunities to mentor junior learners
Share your knowledge and expertise to guide them through AI and ML concepts
Provide feedback and support to enhance their learning journey

Contribute to open-source AI or ML projects

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Gain practical experience and contribute to the AI and ML community by participating in open-source projects.

Browse courses on Community Involvement

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Identify open-source AI or ML projects that align with your interests
Review the project documentation and codebase
Make code contributions, report bugs, or assist with project maintenance

Create a comprehensive study guide or resource compilation for this course

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Organize and synthesize course materials to enhance your understanding and retention of key concepts.

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Gather and review all course materials, including lecture notes, videos, and assignments
Summarize and condense the key points into a structured study guide
Include additional resources, such as recommended books, articles, and online tutorials
Revise and update the study guide regularly to incorporate new learnings and insights

Career center

Learners who complete Introduction to AI and Machine Learning on GC - Français will develop knowledge and skills that may be useful to these careers:

AI Engineer

AI Engineers research, develop, and implement AI solutions. This course offers a comprehensive introduction to AI and ML technologies on Google Cloud. It covers the entire AI development lifecycle, from data preparation to model deployment and monitoring. By gaining expertise in Google Cloud's AI and ML tools and platforms, learners can enhance their skills and advance their careers as AI Engineers.

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Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning models to solve complex business problems. This course provides a comprehensive overview of machine learning concepts, tools, and techniques on Google Cloud. By learning about model development, deployment, and automation, learners can gain the skills needed to succeed in this in-demand field.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use scientific methods and machine learning techniques to extract insights from data. This course provides a comprehensive foundation in the fundamentals of AI and ML on Google Cloud Platform. By learning about data preparation, model development, and evaluation, Data Scientists can enhance their skills and contribute to the development of innovative data-driven solutions.

See salaries and explore the career path for Data Scientist

Research Scientist

Research Scientists conduct research and development in various fields, including AI and ML. This course provides a strong foundation in the principles of AI and ML on Google Cloud. Researchers can benefit from the course's coverage of advanced topics such as generative AI and large language models, which are pushing the boundaries of AI capabilities.

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Cloud Architect

Cloud Architects design and manage complex cloud computing systems. This course provides a solid foundation in the fundamentals of AI and Machine Learning on Google Cloud, which are becoming increasingly important in modern cloud architectures. Understanding these technologies enables Cloud Architects to effectively design and optimize cloud solutions that leverage AI and ML capabilities.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical methods to analyze financial data and make investment decisions. This course provides a strong foundation in the principles of AI and ML on Google Cloud Platform. By learning about advanced topics such as time series analysis and natural language processing, Quantitative Analysts can enhance their skills and develop more sophisticated trading strategies.

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Software Engineer

Software Engineers design, develop, and maintain software applications. This course offers a valuable introduction to the integration of AI and ML into software development. By learning about Google Cloud's AI and ML services, Software Engineers can enhance their skills and create more intelligent and efficient software solutions.

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Financial Analyst

Financial Analysts evaluate and make recommendations on investment opportunities. This course provides a solid foundation in the fundamentals of AI and ML on Google Cloud Platform. By learning about natural language processing, sentiment analysis, and other AI-powered financial analysis techniques, Financial Analysts can enhance their skills and make more informed investment decisions.

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Business Analyst

Business Analysts analyze business processes and systems to identify areas for improvement. This course provides a solid understanding of AI and ML technologies on Google Cloud Platform. By gaining knowledge of how these technologies can automate tasks, improve decision-making, and enhance customer experiences, Business Analysts can make more informed recommendations and drive business value.

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Product Manager

Product Managers are responsible for developing and managing products. This course provides insights into the role of AI and ML in modern product development. By understanding the capabilities and limitations of these technologies, Product Managers can make informed decisions about incorporating AI and ML into their products and effectively communicate its value to stakeholders.

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Data Analyst

Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. With its coverage of data preparation, model development, and inference, the course provides a valuable foundation for understanding the data analysis process. Additionally, the course's emphasis on Google Cloud's AI and ML tools provides practical experience with industry-leading technologies.

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Marketing Analyst

Marketing Analysts analyze marketing campaigns and customer behavior to improve marketing strategies. This course provides a comprehensive introduction to the role of AI and ML in modern marketing. By learning about predictive analytics, customer segmentation, and other AI-powered marketing techniques, Marketing Analysts can enhance their skills and create more effective marketing campaigns.

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Risk Analyst

Risk Analysts assess and manage risks faced by organizations. This course provides a good understanding of the role of AI and ML in risk management. By learning about anomaly detection, fraud prevention, and other AI-powered risk management techniques, Risk Analysts can enhance their skills and contribute to the development of more effective risk management strategies.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in various industries. This course provides a good understanding of the role of AI and ML in operations research. By learning about optimization, simulation, and other AI-powered operations research techniques, Operations Research Analysts can enhance their skills and develop more efficient solutions.

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Consultant

Consultants provide expert advice and guidance to organizations on various business and technology topics. This course offers a comprehensive introduction to AI and ML technologies on Google Cloud Platform. By understanding the potential of these technologies, Consultants can offer more valuable insights and solutions to their clients, helping them leverage AI and ML to achieve their business objectives.

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