TensorFlow courses can help you learn neural networks, deep learning techniques, and model deployment strategies. You can build skills in data preprocessing, hyperparameter tuning, and performance evaluation. Many courses introduce tools like Keras for building models, TensorBoard for visualization, and various APIs for integrating AI into applications.
DeepLearning.AI
Skills you'll gain: Tensorflow, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Computer Vision, Model Evaluation, Transfer Learning, Image Analysis, Keras (Neural Network Library), Natural Language Processing, Time Series Analysis and Forecasting, Deep Learning, Embeddings, Artificial Neural Networks, Generative AI, Applied Machine Learning, Classification Algorithms, Predictive Modeling, Data Preprocessing, Forecasting, Machine Learning
Intermediate · Professional Certificate · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: Tensorflow, Computer Vision, Model Evaluation, Image Analysis, Convolutional Neural Networks, Keras (Neural Network Library), Deep Learning, Artificial Neural Networks, Artificial Intelligence, Data Preprocessing, Machine Learning
Intermediate · Course · 1 - 4 Weeks

Skills you'll gain: Transfer Learning, PyTorch (Machine Learning Library), Model Evaluation, Vision Transformer (ViT), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Convolutional Neural Networks, Unsupervised Learning, Autoencoders, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Logistic Regression, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Image Analysis, Data Preprocessing, Model Deployment, Computer Vision
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, Transfer Learning, PyTorch (Machine Learning Library), Model Evaluation, Retrieval-Augmented Generation, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Vision Transformer (ViT), Computer Vision, Keras (Neural Network Library), LLM Application, Supervised Learning, Vector Databases, Machine Learning, Python Programming, Data Science
Build toward a degree
Intermediate · Professional Certificate · 3 - 6 Months

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

Skills you'll gain: Keras (Neural Network Library), Reinforcement Learning, Convolutional Neural Networks, Unsupervised Learning, Deep Learning, Autoencoders, Tensorflow, Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Transfer Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Performance Tuning
Intermediate · Course · 1 - 3 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: 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

Skills you'll gain: Model Evaluation, Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Computer Vision, Machine Learning, Classification Algorithms
Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Model Evaluation, Convolutional Neural Networks, Data Preprocessing, Keras (Neural Network Library), Image Analysis, Deep Learning, Tensorflow, Computer Vision, Artificial Neural Networks, Recurrent Neural Networks (RNNs), Data Manipulation, Data Transformation, Financial Forecasting, Data Visualization, Time Series Analysis and Forecasting, Exploratory Data Analysis, Python Programming, Customer Analysis, Applied Machine Learning, Cloud Computing
Beginner · Specialization · 1 - 3 Months
TensorFlow is an open-source framework for machine learning (ML) programming originally created by Google Brain, Google’s deep learning and artificial intelligence (AI) research team. It has become one of the most popular software platforms for machine learning due to its flexibility and a comprehensive ecosystem of tools and resources. For example, TensorFlow.js allows for JavaScript-based ML applications that can run in browsers; TensorFlow Lite can run on mobile devices for federated learning applications; and TensorFlow Hub provides an extensive library of reusable ML models.
The flexibility of TensorFlow and breadth of its machine learning applications have been important in enabling a wide range of uses. TensorFlow is frequently used for computer vision applications, including facial recognition in social media, automatic X-ray scanning in healthcare, and autonomous vehicle driving. Similarly, natural language processing (NLP) applications can understand and respond to spoken and written text, making possible the creation of helpful chatbots and other digital agents as well as the automatic reading and summarization of text. Recommendation engines used by music streaming services and online retailers may also be built in TensorFlow.
These are all just a few examples of the power of machine learning applications and the ways that TensorFlow can be leveraged to enable them. If you’re interested in pushing the boundaries of this fast-changing field even further, learning TensorFlow is essential.
Expertise in TensorFlow is an extremely valuable addition to your skillset, and can open the door to many exciting careers. As one of the most popular and useful platforms for machine learning and deep learning applications, TensorFlow skills are in demand from companies throughout the tech world, as well as in the automotive industry, medicine, robotics, and other fields. This high level of demand for skills in TensorFlow and machine learning translates into high levels of pay; according to Glassdoor, machine learning engineers in America earn an average salary of $114,121.
Absolutely - in fact, Coursera is one of the best places to learn TensorFlow skills online. You can take individual courses as well as Specializations spanning multiple courses from deeplearning.ai, one of the pioneers in the field, or Google Cloud, an industry leader. You can also take courses from top-ranked universities from around the world, including Imperial College London and National Research University Higher School of Economics. Guided Projects from Coursera offer another way to learn, with hands-on Tensorflow tutorials presented by experienced instructors.
You need to have a basic understanding of Python before starting to learn TensorFlow, so it's best to start with an introductory course to this programming language first. Python is the language used to design TensorFlow. It's also helpful to have knowledge of artificial intelligence (AI) concepts as well. You should have strong math skills, especially in algebra so that you'll be familiar with the calculations and algorithms required in TensorFlow. Foundational knowledge of vectors, scalars, and matrices is also very helpful as you start learning TensorFlow, as well as basic statistics. And it's important to know the basics of machine learning as well.
People who are best suited for roles in TensorFlow have an interest in machine learning or deep learning. Important soft skills include communication skills, problem-solving skills, time management, teamwork, and a thirst for learning. Someone who uses TensorFlow in their job likely works with a team of professionals like software engineers, research scientists, marketing teams, data scientists, and product teams, so they must be able to communicate clearly, prioritize tasks, and work toward a common goal. And since fields that use TensorFlow—such as AI, machine learning, and deep learning—are constantly evolving, people who adapt well to change and are eager to learn or develop the next new technology are well suited for these roles.
If you are currently in the machine learning field or aspire to be, learning about TensorFlow is most likely right for you. The same applies if you want to enter the deep learning field in positions like deep learning scientist, deep learning software engineer, or deep learning researcher since TensorFlow is a good starting point for deep learning. If you're in a deep learning internship, learning TensorFlow is right for you as well.
Online TensorFlow courses offer a convenient and flexible way to enhance your knowledge or learn new TensorFlow skills. Choose from a wide range of TensorFlow courses offered by top universities and industry leaders tailored to various skill levels.
When looking to enhance your workforce's skills in TensorFlow, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.