It takes a lot of effort to become a TensorFlow expert. Candidates will be taught how to develop models using computer vision, convolutional neural networks (CNNs), and natural language processing (NLP). This certification is useful for developers who want to construct applications that use Machine Learning techniques. That’s why we’ve put together a list of resources and study materials to help you master the basics of TensorFlow. But before we go into the resources, let’s speak about the exam and certification for a minute.
What does TensorFlow developer certification aim to achieve?
In the AI-driven employment market, this certificate is an authoritative certification of your TensorFlow proficiency in handling deep learning and machine learning difficulties. If you have the capacity to design Deep Neural Networks and solve problems with them, you can take the test to earn the credential.
Why should you take the exam?
The certification marked the beginning of your educational journey. Although you may have some TensorFlow experience, working on problems you haven’t encountered before can be difficult. This will need you to code and solve a set of difficulties that you must prepare for.
The exam is an online performance-based test in which you must use TensorFlow models to answer questions. This exam can be taken on any machine that meets the requirements for the PyCharm IDE. You’ll need a decent internet connection to take the test, and you may take it whenever it’s convenient for you. The exam measures your ability to tackle issues including image classification from real-world pictures, natural language processing, and time series forecasting using Tensorflow 2X.
Top 7 Free Resources to prepare for TensorFlow Developer Certification: The 7 Free Resources for TensorFlow Developer Certification are listed below.
- TensorFlow Tutorials: The TensorFlow team has made this tutorial available on their website. The tutorials are prepared in Jupyter notebook format and can be executed directly in Google Colab. It will help both beginners and advanced practitioners because it allows them to learn everything from the fundamentals to sophisticated customization, as well as distributed instruction.
- Kaggle Competitions: It’s an excellent library and competition setting for keeping track of one’s progress, evaluating one’s knowledge, and determining whether one’s model is good enough to earn a spot on the leaderboard. On the site, there are numerous courses on Natural Language Processing, Neural Networks, and Computer Vision. After completing the course, the student receives a certificate. On the platform, machine learning models are also available, allowing users to make hundreds of thousands of dollars while also tracking their progress. TensorFlow and its applications are also debated in Kaggle’s active community.
- Intro to Machine Learning by Tensorflow by Udacity: Over the course of three months, this Udacity course is taught in collaboration with Kaggle and Amazon Web Services. Learners should have 40 hours of programming experience and a solid understanding of data structures such as dictionaries and lists before enrolling in the course. Knowing how to use NumPy and Pandas, as well as having a basic understanding of probability and statistics, is beneficial. TensorFlow training and a basic understanding of neural network design are necessary. After completing the course, students will have hands-on experience with deep learning models such as state-of-the-art image classifiers.
- Convolutional Neural Network in TensorFlow by Coursera: The training requires a basic understanding of artificial intelligence, machine learning, neural network construction, and Python scripting. After completing this course, students will have a better understanding of the tools needed to create an AI-powered algorithm, as well as the best practices for using TensorFlow. The training also covers advanced methodologies for enhancing computer vision models and processing real-world picture data. It helps researchers investigate overfitting prevention strategies like augmentation and dropout.
- Machine Learning with TensorFlow on Google Cloud Platform Specialization: “Machine Learning with TensorFlow on Google Cloud Platform Specialization” is a Coursera course offered by Google Cloud. This course will introduce you to the principles of machine learning as well as the problems that it can solve. You’ll also learn how to scale distributed machine learning models with Tensorflow. It also helps the student scale up the training of those models by delivering high-performance predictions and other services.
- Introduction to TensorFlow for AI, ML & Deep Learning by Coursera: This 30-hour course, led by Laurence Moroney, Google’s legal AI champion, is for folks who have never used TensorFlow before. However, it does require a basic understanding of Python as well as high-school algebra. While having some knowledge of Machine Learning models is beneficial, it is not needed. After completing the course, students will be able to construct and use scalable models to solve real-world problems using TensorFlow principles. The course also covers how to design and train primary neural networks for Computer Vision applications using TensorFlow.
- Sequences, Time-series, and Prediction by Coursera: After completing this course, students will be able to prepare time series data using best practices. Learners will be able to examine the use of RNNs and ID ConvNets for prediction. Finally, students will be able to develop a sunspot prediction model using real-world data. This course will cover forecasting, machine learning, TensorFlow, time series, and prediction.
Final Thoughts: That’s all there is to know about TensorFlow resources. If you want to learn more, there are thousands of TensorFlow tutorial videos on YouTube to help you out. Use Career Ninja‘s Learn Tube for hand-holding training on YouTube. Learn Tube organizes the results of your YouTube search into a course framework. If you type “TensorFlow training,” search that term on youtube, Learn Tube will show you a bunch of videos like an online course. As a beginner, you’ll click through the videos from the first to the last, as if you were taking an online course tailored specifically for you on YouTube.
