DeepLearning.AI
Skills you'll gain: Tensorflow, Transfer Learning, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Natural Language Processing, Computer Vision, Time Series Analysis and Forecasting, Keras (Neural Network Library), Embeddings, Image Analysis, Deep Learning, Scalability, Applied Machine Learning, Predictive Modeling, Artificial Intelligence, Data Preprocessing, Artificial Neural Networks, Text Mining, Forecasting, Machine Learning
Intermediate · Professional Certificate · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: Tensorflow, Convolutional Neural Networks, Computer Vision, Image Analysis, Deep Learning, Scalability, Artificial Intelligence, Artificial Neural Networks, Machine Learning, Data Processing
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Convolutional Neural Networks, Deep Learning, Unsupervised Learning, Model Evaluation, Recurrent Neural Networks (RNNs), Tensorflow, Vision Transformer (ViT), Generative Adversarial Networks (GANs), Transfer Learning, Image Analysis, Autoencoders, Applied Machine Learning, Artificial Neural Networks, Generative AI, Time Series Analysis and Forecasting, Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Deployment
Intermediate · Professional Certificate · 3 - 6 Months
DeepLearning.AI
Skills you'll gain: Generative Adversarial Networks (GANs), Autoencoders, Generative AI, Tensorflow, Computer Vision, Image Analysis, Transfer Learning, Convolutional Neural Networks, Generative Model Architectures, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Classification Algorithms, Model Evaluation, Distributed Computing, Visualization (Computer Graphics), Performance Tuning, Network Architecture
Intermediate · Specialization · 3 - 6 Months

Imperial College London
Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Autoencoders, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Transfer Learning, Convolutional Neural Networks, Applied Machine Learning, Bayesian Statistics, Supervised Learning, Natural Language Processing, Computer Vision, Model Deployment, Artificial Neural Networks, Data Preprocessing, Probability Distribution
Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, PyTorch (Machine Learning Library), Model Evaluation, Retrieval-Augmented Generation, Supervised Learning, LLM Application, Unsupervised Learning, Computer Vision, PySpark, Generative Model Architectures, Keras (Neural Network Library), Convolutional Neural Networks, Generative AI, Deep Learning, Applied Machine Learning, Machine Learning, Python Programming, Data Science
Build toward a degree
Intermediate · Professional Certificate · 3 - 6 Months

Skills you'll gain: Tensorflow, Google Cloud Platform, Scripting, Artificial Neural Networks, Machine Learning, Supervised Learning, Deep Learning, Cloud Computing, Development Environment
Beginner · Project · Less Than 2 Hours

Skills you'll gain: Deep Learning, Unsupervised Learning, Keras (Neural Network Library), Tensorflow, Convolutional Neural Networks, Generative Adversarial Networks (GANs), Transfer Learning, Recurrent Neural Networks (RNNs), Generative AI, Time Series Analysis and Forecasting, Reinforcement Learning, Computer Vision
Intermediate · Course · 1 - 3 Months

DeepLearning.AI
Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Natural Language Processing, Keras (Neural Network Library), Embeddings, Artificial Neural Networks, Text Mining, Applied Machine Learning, Data Preprocessing, Machine Learning, Predictive Modeling
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Recurrent Neural Networks (RNNs), Transfer Learning, Tensorflow, Artificial Neural Networks, Embeddings, Keras (Neural Network Library), Deep Learning, Time Series Analysis and Forecasting, Image Analysis, Classification Algorithms, Convolutional Neural Networks, Natural Language Processing, Computer Vision, Forecasting, Supervised Learning, Machine Learning Algorithms, Machine Learning, Predictive Analytics, Model Evaluation, Predictive Modeling
Intermediate · Specialization · 1 - 3 Months

Imperial College London
Skills you'll gain: Tensorflow, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Convolutional Neural Networks, Transfer Learning, Supervised Learning, Computer Vision, Model Deployment, Artificial Neural Networks, Data Preprocessing
Intermediate · Course · 1 - 3 Months

DeepLearning.AI
Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Transfer Learning, Convolutional Neural Networks, Keras (Neural Network Library), Deep Learning, Classification Algorithms, Model Evaluation, Visualization (Computer Graphics), Network Architecture
Intermediate · Course · 1 - 4 Weeks
TensorFlow is an open-source machine learning framework developed by Google that allows developers to create complex neural networks and machine learning models. It is important because it provides a flexible and comprehensive ecosystem for building and deploying machine learning applications. TensorFlow supports various tasks, from simple linear regression to advanced deep learning applications, making it a versatile tool for data scientists and developers alike.
With skills in TensorFlow, you can pursue various job roles in the tech industry. Common positions include Machine Learning Engineer, Data Scientist, AI Researcher, and Software Developer specializing in AI applications. These roles often involve designing and implementing machine learning models, analyzing data, and developing algorithms that can learn from and make predictions based on data.
To effectively learn TensorFlow, you should focus on several key skills. First, a solid understanding of Python programming is essential, as TensorFlow is primarily used with this language. Additionally, knowledge of machine learning concepts, linear algebra, and statistics will greatly enhance your ability to work with TensorFlow. Familiarity with neural networks and deep learning principles is also crucial, as these are fundamental to many TensorFlow applications.
There are many excellent online courses available for learning TensorFlow. Notable options include the DeepLearning.AI TensorFlow Developer Professional Certificate, which provides a comprehensive introduction to TensorFlow and its applications. Another great choice is the Deep Learning with TensorFlow Specialization, which covers various aspects of deep learning using TensorFlow.
Yes. You can start learning TensorFlow on Coursera for free in two ways:
If you want to keep learning, earn a certificate in TensorFlow, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
To learn TensorFlow, start by exploring introductory courses that cover the basics of machine learning and TensorFlow itself. Engage with hands-on projects to apply what you learn in real-world scenarios. Utilize online resources, such as tutorials and documentation, to deepen your understanding. Joining community forums can also provide support and insights from other learners and professionals.
Typical topics covered in TensorFlow courses include the fundamentals of machine learning, building and training neural networks, working with TensorFlow APIs, and deploying models. Advanced courses may explore specialized areas such as computer vision, natural language processing, and reinforcement learning, providing a well-rounded education in machine learning.
For training and upskilling employees, the IBM Deep Learning with PyTorch, Keras and Tensorflow Professional Certificate is an excellent choice. It equips learners with practical skills in deep learning and TensorFlow, making it suitable for organizations looking to enhance their workforce's capabilities in AI and machine learning.