Google Cloud Big Data and Machine Learning Fundamentals en Français from Coursera

What's inside

Syllabus

Présentation du cours

Cette section accueille les participants au cours Big Data and Machine Learning Fundamentals et leur offre un aperçu de sa structure et de ses objectifs.

Big data et machine learning sur Google Cloud

Cette section aborde les composants clés de l'infrastructure Google Cloud. Elle présente un grand nombre des produits et services Google Cloud pour le big data et le machine learning, tous compatibles avec le cycle de vie "des données à l'IA".

Ingénierie des données pour la diffusion de données

Cette section présente la solution de Google Cloud pour gérer les flux de données. Elle examine un pipeline de bout en bout, y compris l'ingestion de données avec Pub/Sub, le traitement des données via Dataflow, et la visualisation des données avec Looker et Data Studio.

Big data avec BigQuery

Cette section présente BigQuery, l'entrepôt de données sans serveur entièrement géré de Google. Elle aborde également BigQuery ML, ainsi que les processus et les commandes clés permettant de créer des modèles de machine learning personnalisés.

Options de machine learning sur Google Cloud

Cette section explore quatre options différentes pour créer des modèles de machine learning sur Google Cloud. Elle présente également Vertex AI, la plate-forme unifiée de Google permettant de créer des projets de ML et de gérer leur cycle de vie.

Workflow de machine learning avec Vertex AI

Cette section se concentre sur les trois phases clés d'un workflow de machine learning dans Vertex AI : préparation des données, entraînement du modèle et évaluation du modèle. Les participants ont l'occasion de s'entraîner à créer un modèle de machine learning avec AutoML.

Résumé du cours

Cette section revient sur les sujets abordés pendant le cours. Il oriente également les participants vers des ressources supplémentaires qui leur permettront d'approfondir leurs connaissances.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Correspond aux chefs de projet, data scientist et analystes, qui souhaitent exploiter et analyser des volumes élevés de données, créer et déployer des modèles de machine learning

Reviews summary

Great for hands-on, needs improvement

This course excels at providing hands-on learning experiences and presenting well-structured content. However, some students have experienced frustrating bugs within quizzes and labs that have hindered their progress. The relevance of the certificate has also been brought into question, as it is not heavily tied to assessment scores.

Well-structured and informative content

"Les cours sont bien faits."

Valuable hands-on learning opportunities

"J'ai particulierement apprécié l'aspect "Atelier" qui m'a permis de me confronter factuellement à de la delivrance de resultats mesurables via les immenses ressources informatiques de Google Cloud Platform"

Certificate may not accurately reflect learning

"très bon cours mais certificat sans valeurs : les quiz ne sont pas utilisés pour l'attribution du certificat et les ateliers sont validés après un certain temps passé dans le lab sans réelle évaluation"

Bugs and issues within quizzes and labs

"Pity there are so many bugs in the quizz (and for months, it seems!), the content in itself is very good, imho."

"le code pySpark dans l'un des ateliers n'est pas expliquÃ© du tout."

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 Cloud Big Data and Machine Learning Fundamentals en Français with these activities:

Review Advanced Computing Concepts

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Review fundamental principles of advanced computing concepts such as distributed systems and cloud computing to strengthen your foundation for the course.

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Review textbooks or online resources
Summarize key concepts
Complete practice exercises

Explore Google Cloud Platform Tutorials

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Familiarize yourself with Google Cloud Platform services by following guided tutorials to gain hands-on experience.

Browse courses on Google Cloud Platform

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Identify relevant tutorials
Complete tutorials
Experiment with different services

Join Study Groups or Online Forums

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Engage with peers to discuss course material, share perspectives, and get support.

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Identify relevant study groups or forums
Participate in discussions
Share knowledge and ask questions

Five other activities

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Solve Machine Learning Practice Problems

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Enhance your problem-solving skills by practicing machine learning algorithms and techniques through online platforms or practice exercises.

Browse courses on Machine Learning

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Identify reputable platforms or resources
Select problems aligned with course concepts
Solve problems and review solutions

Attend Industry Meetups or Conferences

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Network with professionals in the field to learn about industry trends, share ideas, and explore career opportunities.

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Identify relevant meetups or conferences
Prepare for networking opportunities
Attend and engage in discussions

Contribute to Open-Source Machine Learning Projects

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Enhance your knowledge and gain practical experience by contributing to open-source machine learning projects.

Browse courses on Machine Learning

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Identify relevant projects
Read documentation and code
Identify areas for contribution
Propose and implement changes

Design a Data Management Plan

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Develop a comprehensive plan outlining your approach to data management, including data storage, processing, and security.

Browse courses on Data Management

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Gather data requirements
Identify data sources
Design data storage and processing architecture
Define data security measures
Document your plan

Create a Portfolio of Machine Learning Projects

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Showcase your skills and understanding by creating a portfolio of machine learning projects that demonstrate your ability to apply course concepts.

Browse courses on Machine Learning

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Select projects that highlight different machine learning techniques
Develop and implement projects
Document and present your projects

Career center

Learners who complete Google Cloud Big Data and Machine Learning Fundamentals en Français will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers build, test, and deploy machine learning models to solve real-world problems. Google Cloud's Big Data and Machine Learning Fundamentals provides a solid foundation in these tasks, specifically on its Vertex AI platform.

See salaries and explore the career path for Machine Learning Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineers design, develop, and maintain AI systems. Google Cloud's Big Data and Machine Learning Fundamentals provides a solid foundation in machine learning concepts and technologies for those seeking this role.

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Machine Learning Operations Engineer

Machine Learning Operations Engineers maintain and monitor machine learning models in production. Google Cloud's Big Data and Machine Learning Fundamentals would provide valuable knowledge of machine learning pipelines for this role.

See salaries and explore the career path for Machine Learning Operations Engineer

Data Scientist

Data Scientists use scientific methods and algorithms to extract knowledge and insights from data. Google Cloud's Big Data and Machine Learning Fundamentals can provide a solid foundation for a Data Scientist, covering topics like data engineering, model training, and evaluation.

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Data Analyst

Data Analysts explore, transform, and visualize raw data. They present findings to stakeholders in an understandable, usable format. Google Cloud's Big Data and Machine Learning Fundamentals will help you build a foundation in these areas.

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Business Analyst

Business Analysts analyze data and provide insights to help businesses make informed decisions. Google Cloud's Big Data and Machine Learning Fundamentals can provide valuable knowledge in data handling and interpretation for this role.

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Data Visualization Specialist

Data Visualization Specialists translate data into visual representations to make it more accessible and understandable. Google Cloud's Big Data and Machine Learning Fundamentals provides knowledge in data visualization tools and techniques that can be useful for this role.

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Research Scientist

Research Scientists conduct research in various fields, including data science and machine learning. Google Cloud's Big Data and Machine Learning Fundamentals can provide a foundation for those seeking this role, introducing them to key concepts and technologies.

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Data Engineer

Data Engineers design, build, and maintain data processing systems. They play a crucial role in making data available and usable for analysis. Knowledge gained by completing Google Cloud's Big Data and Machine Learning Fundamentals may be useful in this role.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. Google Cloud's Big Data and Machine Learning Fundamentals provides a foundation in data analysis and machine learning which may be helpful for those seeking this role.

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Statistician

Statisticians collect, analyze, interpret, and present data. Google Cloud's Big Data and Machine Learning Fundamentals provides a foundation in statistical concepts and machine learning techniques that may be helpful for this role.

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Data Architect

Data Architects design and manage data systems. Google Cloud's Big Data and Machine Learning Fundamentals may be helpful for those seeking this role, as it covers topics such as data modeling, data quality, and data governance.

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Software Engineer

Software Engineers design, develop, and maintain software systems. Google Cloud's Big Data and Machine Learning Fundamentals may be useful for Software Engineers as it provides knowledge in managing and processing large datasets and implementing machine learning models.

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Database Administrator

Database Administrators manage and maintain databases. Google Cloud's Big Data and Machine Learning Fundamentals may be useful for those seeking this role, as it provides knowledge in data management and processing.

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Product Manager

Product Managers are responsible for the development and launch of new products and features. The knowledge gained in Google Cloud's Big Data and Machine Learning Fundamentals may be helpful for Product Managers to understand data-driven decision-making.

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