Machine Learning with TensorFlow on Google Cloud
Learn TensorFlow on Google Cloud with hands-on, structured modules
Build real-world ML skills with practical projects and labs
Learn from industry experts with proven credentials
Gain a globally recognized certification to enhance your credibility
Enjoy flexible learning options that fit your schedule
Master scalable ML models using TensorFlow and Google Cloud
4.7/53259 EnrolledEnrolled Learners
4.7/53259 EnrolledEnrolled Learners
Overview
What our training includes:
- Master TensorFlow 2.x and Keras for building machine learning models
- Train models with Google Cloud’s AI Platform for scalable machine learning solutions
- Optimize models using loss functions, performance metrics, and hyperparameter tuning
- Implement feature engineering with BQML, TensorFlow, and Cloud Dataprep
- Analyze data with Cloud Dataflow and preprocess using TensorFlow’s tf.data
- Provide teams hands-on experience with real-world machine learning applications
Upcoming sessions
Curriculum
1
Develop a data strategy around machine learning
2
Examine use cases that are then reimagined through an ML lens
3
Recognize biases that ML can amplify
4
Leverage Google Cloud Platform tools and environment to do ML
5
Learn from Google's experience to avoid common pitfalls
6
Carry out data science tasks in online collaborative notebooks
7
Invoke pre-trained ML models from Cloud AI Platform
1
Describe how to improve data quality
2
Perform exploratory data analysis
3
Build and train supervised learning models
4
Optimize and evaluate models using loss functions and performance metrics
5
Mitigate common problems that arise in machine learning
6
Create repeatable and scalable training, evaluation, and test datasets
1
Create TensorFlow 2.x and Keras machine learning models
2
Describe Tensorflow 2.x key components
3
Use the tf.data library to manipulate data and large datasets
4
Use the Keras Sequential and Functional APIs for simple and advanced model creation
5
Train, deploy, and productionalize ML models at scale with Cloud AI Platform
1
Compare the key required aspects of a good feature
2
Combine and create new feature combinations through feature crosses
3
Perform feature engineering using BQML, Keras, and TensorFlow 2.x
4
Understand how to preprocess and explore features with Cloud Dataflow and Cloud Dataprep
5
Understand and apply how TensorFlow transforms features
1
Optimize model performance with hyperparameter tuning
2
Experiment with neural networks and fine-tune performance
3
Enhance ML model features with embedding layers
1
Summary
Meet your Trainer
Our Trainers
Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.
We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.
Learning Outcomes
Upon finishing the training, you will:
1
Master TensorFlow 2.x and Keras to build advanced machine learning models
2
Build and refine machine learning models using TensorFlow and Google Cloud
3
Implement feature engineering with Cloud Dataprep and TensorFlow for data optimization
4
Optimize model performance through hyperparameter tuning and advanced evaluation metrics
5
Gain hands-on experience deploying real-world ML models with Google Cloud tools
6
Train teams to build and deploy scalable AI solutions using TensorFlow effectively
KHDA Certificate
Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
Overall ratings by our students
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Frequently asked questions
The Machine Learning with TensorFlow on Google Cloud course is designed to teach you how to build, train, and deploy machine learning models using TensorFlow and Google Cloud tools. You gain hands-on experience with Google Cloud's AI Platform, TensorFlow 2.x, and Keras to create scalable machine learning models.
This course helps you develop real-world skills that are in high demand across various industries, opening up lucrative career opportunities in machine learning and AI fields.
Our training program provides you with the skills to design, build, and deploy end-to-end machine learning pipelines using TensorFlow and Google Cloud. You gain expertise in scalable model development, data processing, and cloud-based deployment. We prepare you to lead AI initiatives, guide technical teams, and architect production-ready ML solutions within your organization.
Yes, Data Analysts with 2–3 years of experience often have strong foundations in data manipulation, making it easier to transition into ML roles. This training helps you with TensorFlow, Keras, feature engineering, and model deployment skills. We enable you to take on roles like Junior Machine Learning Engineer or ML Operations Analyst.
This course is open to individuals with a background in programming, data analysis, or a related field. Familiarity with Python programming is required, as it is the primary language used in TensorFlow.
While prior experience in machine learning or data science can be beneficial, beginners with basic knowledge of coding and data analysis are welcome. Additionally, proficiency in English is essential as course materials and instructions are in English.
In this course, you work with key tools and technologies such as TensorFlow 2.x, Keras, Google Cloud’s AI Platform, Cloud Dataflow, and Cloud Dataprep. You also use the TensorFlow framework for building and deploying machine learning models. We help you gain experience with advanced data preprocessing, model optimization, and cloud-based deployments. These tools are critical for handling real-world machine learning projects at scale.
The key topics covered in this training course include:
- Mastering TensorFlow 2.x and Keras for building machine learning models
- Applying feature engineering using Cloud Dataprep
- Performing hyperparameter tuning and model optimization
- Implementing scalable machine learning solutions using Google Cloud's AI Platform
- Using Cloud Dataflow for data processing workflows
- Deploying real-world machine learning models
- Exploring real-time applications of machine learning across various industries
Upon completing the Machine Learning with TensorFlow on Google Cloud course, graduates can explore the following career paths:
• Machine Learning Engineer: Design and optimize machine learning models for a variety of applications.
• Data Scientist: Analyze large datasets and provide data-driven insights using machine learning techniques.
• AI Specialist: Develop AI solutions to address business challenges across different sectors.
• Cloud Solutions Architect: Build scalable cloud-based architectures for deploying machine learning models.
These roles are highly sought after in industries like technology, finance, healthcare, and retail, with senior positions requiring advanced skills in AI and machine learning.
Unlike many other courses, our Machine Learning with TensorFlow on Google Cloud course focuses on practical, hands-on learning with real-world applications. Participants use TensorFlow 2.x and Google Cloud tools to build scalable machine learning solutions, which sets this training apart from competitors that offer more theoretical content.
Additionally, we provide in-depth exposure to cloud-based model deployment and optimization. This makes our course highly relevant for today’s AI-driven job market.
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