DeepLearning.AI TensorFlow Developer Professional Course

Q: 2. What key skills and technologies will I learn?

The four-course series covers: Introduction to TensorFlow and deep neural networks Computer Vision with CNNs , data augmentation, dropout, transfer learning Natural Language Processing , including tokenization, RNNs, GRUs, LSTMs Time Series & Forecasting , including predictive modeling applications

Q: 3. How long does the program take, and how flexible is it?

Estimated completion is 2 months at 10 hours per week , though pacing is flexible—some complete faster.

Q: 4. Does the certificate include hands-on projects or assignments?

Yes—this is a practical, hands-on program. It includes 16 Python assignments and encourages building models, hands-on experimentation, and preparing for the (now-closed) Google TensorFlow Developer exam.

Q: 5. How valuable is this certification for advancing my AI/ML career?

Widely recognized in data science and ML. Over 32% of participants say it helped them start a new career, and it's highly rated (~4.7/5).

An exceptional program that equips learners with practical TensorFlow skills, bridging the gap between theory and real-world application in deep learning.

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access	Lifetime
level	Beginner
certificate	Certificate of completion
language	English

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Description
Additional information
FAQs

What you will learn in DeepLearning.AI TensorFlow Developer Professional Course

Build and train deep neural networks using TensorFlow.
Apply convolutional neural networks (CNNs) for computer vision tasks.
Develop natural language processing (NLP) systems with RNNs, GRUs, and LSTMs.

Implement time series forecasting models using real-world data.
Understand best practices for using TensorFlow in machine learning applications.

Program Overview

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

⏱️ 22 hours

Learn the basics of TensorFlow and how to build neural networks.
Train a neural network for a computer vision application.

Convolutional Neural Networks in TensorFlow

⏱️18 hours

Explore how to work with real-world images and improve your models.
Implement strategies to prevent overfitting, including data augmentation and dropout.

Natural Language Processing in TensorFlow

⏱️ 16 hours

Build NLP systems using TensorFlow.
Apply RNNs, GRUs, and LSTMs to process text data.

Sequences, Time Series, and Prediction

⏱️ 18 hours

Learn how to build time series models in TensorFlow.
Implement best practices to prepare time series data and build prediction models.

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Job Outlook

Proficiency in TensorFlow is essential for roles such as Machine Learning Engineer, Data Scientist, and AI Specialist.
Skills acquired in this program are applicable across various industries, including technology, healthcare, finance, and more.
Completing this Professional Certificate can enhance your qualifications for positions that require expertise in deep learning and TensorFlow.

Explore More Learning Paths

Take your deep learning and AI expertise to the next level with these curated programs designed to expand your TensorFlow skills and build advanced machine learning models.

Related Courses

TensorFlow: Data and Deployment Specialization Course – Learn how to manage data pipelines and deploy TensorFlow models in real-world applications.
TensorFlow Advanced Techniques Specialization Course – Dive into cutting-edge TensorFlow techniques for building high-performance neural networks.
Natural Language Processing in TensorFlow Course – Explore NLP workflows and implement state-of-the-art models using TensorFlow.

Related Reading
Gain deeper insight into machine learning frameworks and model management:

What Is Data Management? – Understand how proper data handling supports reliable AI and deep learning model performance.

9.8Expert Score

Highly Recommended

The DeepLearning.AI TensorFlow Developer Professional Certificate offers a comprehensive and practical introduction to deep learning using TensorFlow. It's particularly beneficial for individuals seeking to apply deep learning techniques in various domains.

Value

9.5

Price

9.3

Skills

9.8

Information

9.9

PROS

Taught by experienced instructors from DeepLearning.AI.
Hands-on projects and assignments to solidify learning.
Flexible schedule accommodating self-paced learning.
Applicable to both academic and industry settings.

CONS

Requires prior experience in Python and a basic understanding of machine learning concepts.
Some learners may seek more advanced topics beyond the scope of this certificate.

Specification: DeepLearning.AI TensorFlow Developer Professional Course

access	Lifetime
level	Beginner
certificate	Certificate of completion
language	English

FAQs

1. Can beginners with no deep learning experience enroll?

It’s accessible but recommended for learners with Python skills. The program is intermediate level, designed for those with some programming proficiency.
High-school math skills are sufficient, and prior exposure to machine learning helps—but deep learning knowledge isn’t mandatory.

2. What key skills and technologies will I learn?

The four-course series covers:

Introduction to TensorFlow and deep neural networks
Computer Vision with CNNs, data augmentation, dropout, transfer learning
Natural Language Processing, including tokenization, RNNs, GRUs, LSTMs
Time Series & Forecasting, including predictive modeling applications

3. How long does the program take, and how flexible is it?

Estimated completion is 2 months at 10 hours per week, though pacing is flexible—some complete faster.

4. Does the certificate include hands-on projects or assignments?

Yes—this is a practical, hands-on program. It includes 16 Python assignments and encourages building models, hands-on experimentation, and preparing for the (now-closed) Google TensorFlow Developer exam.

5. How valuable is this certification for advancing my AI/ML career?

Widely recognized in data science and ML. Over 32% of participants say it helped them start a new career, and it’s highly rated (~4.7/5).

DeepLearning.AI TensorFlow Developer Professional Course

Description
Additional information
FAQs

Explore This Course

DeepLearning.AI TensorFlow Developer Professional Course