Embark on a transformative journey with the "Launching into Machine Learning" course by Google Cloud. This comprehensive program delves into the crucial aspects of machine learning, empowering participants with essential knowledge and practical expertise.
Throughout the course, participants will gain insights into enhancing data quality and performing exploratory data analysis. They will discover the power of Vertex AI AutoML and learn to develop, train, and deploy ML models effortlessly without coding. Additionally, the program covers the utilization of BigQuery ML and the optimization of ML models using loss functions and performance metrics.
The course fosters a deep understanding of supervised learning, linear regression, and logistic regression, providing a solid foundation for practical application. Participants will also delve into training AutoML models using Vertex AI and harness the capabilities of BigQuery Machine Learning to develop ML models within their data environment.
Moreover, the curriculum includes modules on optimization, generalization, and sampling, enabling learners to acquire crucial skills for assessing and improving the quality of ML models. With a focus on creating repeatable and scalable training, evaluation, and test datasets, the course ensures participants are equipped to navigate real-world machine learning challenges effectively.
By the end of the program, participants will possess the knowledge and skills required to proficiently operate in the machine learning domain. Whether you are an aspiring data scientist, AI enthusiast, or professional seeking to enhance your expertise, this course will undoubtedly elevate your proficiency in the fascinating realm of machine learning.
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The "Launching into Machine Learning" course comprises comprehensive modules covering data enhancement, ML model development, optimization techniques, and practical applications, equipping learners with valuable skills for real-world machine learning scenarios.
Course introduction provides an overview of the program's content and objectives, setting the stage for an enriching learning experience.
The "Get to Know Your Data" module imparts essential knowledge on improving data quality and conducting exploratory data analysis. Participants will engage in practical labs to enhance their skills.
Machine Learning in Practice equips learners with foundational knowledge of supervised learning, linear regression, and logistic regression. Hands-on labs ensure practical understanding and skill development.
The "Training AutoML Models Using Vertex AI" module delves into the intricacies of automated machine learning, enabling participants to develop, evaluate, and optimize AutoML models effectively.
The "BigQuery Machine Learning" module empowers participants to harness the capabilities of BigQuery ML for model development, hyperparameter tuning, and building recommendation systems.
Optimization provides crucial insights into model refinement, loss functions, performance metrics, and troubleshooting, enhancing participants' ability to optimize ML models effectively.
The "Generalization and Sampling" module equips learners with essential skills for assessing model quality, generalization, and creating repeatable samples in BigQuery, ensuring comprehensive understanding and practical proficiency.
The "Summary" module offers a comprehensive recap of the course content, reinforcing key learnings and providing a cohesive conclusion to the enriching learning journey.
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