Machine Learning with TensorFlow on Google Cloud Training in Oman
Learn TensorFlow on Google Cloud with hands-on, structured modules
Build real-world ML skills with practical projects & lab activities
Learn from industry experts with proven credentials
Earn a globally recognised certification to enhance your credibility
Enjoy flexible learning options that fit your schedule
Master scalable ML models using TensorFlow & Google Cloud
Overview
What you will learn:
- Teaches using TensorFlow 2.x & Keras to develop machine learning models
- Guides to train scalable solutions with Google Cloud’s robust AI Platform
- Builds model optimization skills through tuning, metrics analysis, & loss functions
- Prepares for feature engineering using TensorFlow, BQML, & Cloud Dataprep
- Offers techniques for analysing & preprocessing data via tf.data & Cloud Dataflow
- Provides real-world project experience to apply learned ML concepts in practical settings
Upcoming sessions
Curriculum
Develop a data strategy around machine learning
Examine use cases that are then reimagined through an ML lens
Recognize biases that ML can amplify
Leverage Google Cloud Platform tools and environment to do ML
Learn from Google's experience to avoid common pitfalls
Carry out data science tasks in online collaborative notebooks
Invoke pre-trained ML models from Cloud AI Platform
Describe how to improve data quality
Perform exploratory data analysis
Build and train supervised learning models
Optimize and evaluate models using loss functions and performance metrics
Mitigate common problems that arise in machine learning
Create repeatable and scalable training, evaluation, and test datasets
Create TensorFlow 2.x and Keras machine learning models
Describe Tensorflow 2.x key components
Use the tf.data library to manipulate data and large datasets
Use the Keras Sequential and Functional APIs for simple and advanced model creation
Train, deploy, and productionalize ML models at scale with Cloud AI Platform
Compare the key required aspects of a good feature
Combine and create new feature combinations through feature crosses
Perform feature engineering using BQML, Keras, and TensorFlow 2.x
Understand how to preprocess and explore features with Cloud Dataflow and Cloud Dataprep
Understand and apply how TensorFlow transforms features
Optimize model performance with hyperparameter tuning
Experiment with neural networks and fine-tune performance
Enhance ML model features with embedding layers
Summary
Learning Outcomes
Upon finishing the training, you will:
1
Attain skills in TensorFlow 2.x & Keras to build advanced machine learning models
2
Create scalable ML solutions using TensorFlow & Google Cloud’s AI Platform
3
Use Cloud Dataprep & TensorFlow for data prep & feature engineering
4
Improve models with tuning methods & strong evaluation techniques
5
Deploy real-world ML models using key Google Cloud tools
Overall ratings by our students
Related courses
Learn now, pay later
Dive into your course now and pay in installments


Frequently asked questions
The Machine Learning with TensorFlow on Google Cloud Training in Oman is all about teaching professionals how to build, train, and deploy machine learning models using TensorFlow and Google Cloud tools. You learn concepts like data preparation and model building, tuning, and deploying actual applications. You work with tools like Cloud Dataflow and AI Platform to build scalable ML solutions, which provides you with practical experience.
During our Machine Learning with TensorFlow on Google Cloud course in Oman, professionals practice working with the following tools -
- TensorFlow 2.x
- Keras
- Google Cloud’s AI Platform
- Cloud Dataprep
- Cloud Dataflow
- Model tuning
- Evaluation tools
Our training is available in several different modes, including -
- Instructor-led group sessions
- Personalized one-on-one training
- Live interactive online classes
Earning the Machine Learning with TensorFlow on Google Cloud Certification in Oman makes professionals eligible to apply for several roles, like -
- Machine Learning Engineer
- Data Scientist
- AI Developer
- Cloud Solutions Engineer
- Data Engineer with ML focus
The course teaches professionals the following processes to improve data quality -
- Clean and analyze data before modeling
- Identify and resolve data issues
- Create quality training, evaluation, and test sets
- Perform exploratory data analysis effectively
Do you want to learn more about Learners Point Academy?
- Learn more about courses
- Understand about our methodology
- Let’s talk about Corporate trainings
- Anything else that you want to know, we are here for you!



