- Course Introduction
- Intro to Specialization
End-to-End Machine Learning with TensorFlow on GCP
Join End-to-End Machine Learning with TensorFlow on GCP by Coursera to understand and build innovative, correct models for organised data.
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based
End-to-End Machine Learning with TensorFlow on GCP is the successor of the first course Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization. This programme is included in a 5-course specialization that focuses on the topics of advanced machine learning that uses Google Cloud Platform. This course would give real-life experience by improving, establishing, and measuring production.
Through this course, the candidates would learn to build innovative, correct, and manufacturing-ready models for organised data, time series, natural language text, and image text. The course will end on recommendation systems. This programme does not have any schedule adherence; the candidates can look at the study materials according to their availability. Along with theoretical concepts, the candidates would also learn about the practical approach of advanced machine learning.
- Offered by Google Cloud
- 13 hours course duration
- Certificate can be shared electronically
- Accessibility in different languages
- Advanced level
- Subtitles in French, Portuguese (Brazilian), Russian, English, Spanish
- Flexible deadline
- Online classes
- Practice quizzes
- Course readings
- Pre recorded modules
- Self paced learning
Course and certificate fees
Fee detail for the course End-to-End Machine Learning with TensorFlow on GCP is given below. The candidate will have to pay Rs. 2,877 after a 7-days free trial
End-to-End Machine Learning with TensorFlow on GCP Fees Details
Type of Fee
Rs. 2,877 (post 7 days free trial)
certificate providing authority
The candidate applying for End-to-End Machine Learning with TensorFlow on the GCP programme should have knowledge about Python, TensorFlow and Basic SQL.
Certification Qualifying Details
Candidates will get the certificate of completion for End-to-End Machine Learning with TensorFlow on the GCP certification course, once the course is completed successfully. Apart from seeing the pre-recorded modules, the candidates will have to complete the required assignments as well. The given certificate could be shared with potential employers and within the candidates’ professional network.
What you will learn
- After completing the course, the candidates will gain specialization in advanced machine learning with TensorFlow.
- The candidates will gain experience on projects which include topics like Google Cloud Platform products and many others.
- The candidates will have an understanding of the components and practical approach of the best performing ML system in manufacturing scenarios.
Follow these steps to apply for End-to-End Machine Learning with TensorFlow on GCP:
Step 1: Visit the course page.
Step 2: Select “Enroll for free” and get started with 7-Day Free Trial. But before that, the candidate needs to sign up and log in to get a dashboard. s
Step 3: After the 7-Day Free Trial, the candidates will have to pay a certain amount to continue looking at the course.
Step 4: To pay the fee, provide the billing details and choose a payment method.
Step 5: You will receive a confirmation of your enrollment once the transaction is complete.
Welcome to the course
How to send feedback
Machine Learning on Google Cloud Platform
- Fully managed ML
- Effective ML
Explore the Data
- Exploring the dataset
- Getting Started with Google Cloud Platform and Qwiklabs
- Lab 1 Intro: Exploring the dataset
- Lab 1 demo and review
- BigQuery and AI Platform Notebooks
AI Platform Notebooks
Create the dataset
- Lab 2 Intro: Create a sample dataset
- Creating a dataset
- Lab 2: demo and review
- Module Quiz
Build the Model
- Lab 3 Intro: Creating a TensorFlow model
- Build the model
- Lab 3: demo and review
- Module Quiz
Operationalize the model
- Lab 4 Intro: Preprocessing with Cloud Dataflow
- Train and deploy with Cloud AI Platform
- Lab 4 demo and review
- Operationalizing the model
- Deploying and Predicting with Cloud AI Platform
- BigQuery ML
- Lab 5: Training on Cloud AI Platform
- Lab Introduction
- Lab 5 demo and review
- Lab Solution BigQuery ML
- Lab 6: demo and review
- Lab 6 Intro: Deploying and Predicting with Cloud AI Platform
- Lab 7: demo and review
- Lab 7: Building an App Engine app to serve ML predictions
- Cloud AI Platform
- Cloud AI Platform
- Module Quiz
End-to-End Machine Learning with TensorFlow on the GCP programme does not provide scholarships at the moment but has provision for financial support. Candidates who can’t afford the fee can seek financial support. Click on the financial aid link, fill in the application and they will receive a notification from Coursera once the request is approved.
How it helps
Coursera, in collaboration with Google Cloud, is helping various organizations working towards motivating their employees and serving their customers. End-to-End Machine Learning with TensorFlow on the GCP programme has been designed to train the students regarding Machine Learning with TensorFlow on the platform of Google Cloud. This specialization course would help in improving skills. It would train the candidates to follow the process of establishing machine learning in a manufacturing environment. The candidates would learn to explore documents through BigQuery and Datalab. This programme is created as a workshop to apply the technologies and concepts applied while in production. According to the previous study, 71% of the participants started a new career on completion of the course, 62% got an increase in the payment, and 80% of the participants got a tangible benefit.
The course subtitles are available in different languages for foreign students such as English, Russian, Spanish, Portuguese (Brazilian), and French.
Before applying for this course, the candidate must know basic SQL and be familiar with TensorFlow and Python as it is an advanced programme.
Unfortunately, this course by Coursera doesn’t offer the benefit of university credit. But Coursera offers benefits like Mastertrack Certificates and Online Degrees to earn university credit. Few universities do accept Certificates for credit.
After the enrollment in the course, the candidate would get access to all other courses in Specialization and once the learning is completed the candidate would get a certificate. The e-certificate would be added to the accomplishment page and the candidates can also add it to their LinkedIn profile.
The programme will require 13 hours approximately to complete the course.
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