Hello guys, if you are learning TensorFlow for AI and Machine Learning and looking for best resources to learn TensorFlow in depth then you have come to the right place. Earlier, I have shared best TensorFlow courses for beginners and in this article, I am going to review, one of the top TensorFlow Course from Coursera, DeepLearning.AI TensorFlow Developer Professional Certificate. This is one of the popular and well structure Coursera course to learn TensorFlow and earn a certificate and we will review this to find out whether its really worth it or not.
Nowadays, Artificial intelligence is dominating every industry and almost every device we use, from IoT to phones. If you are curious about this science and machine learning, data science, then you probably heard of python languages and their AI frameworks like PyTorch Keras and Tensorflow.
Most people use TensorFlow to build machine learning and deep learning models for object detection, object recognition, language translation, and more. Google also uses it to develop RankBrain, which is responsible for the search process in Google.
Tensorflow is probably the most popular framework for building artificial intelligence software and was developed by Google and is available for people to use even for commercial purposes. There are many courses online to learn this framework. Still, I recommend one called DeepLearning.AI TensorFlow Developer Professional Certificate because it is easy for beginners to understand and create by experts.
Review - Is DeepLearning.AI TensorFlow Developer Professional Certificate on Coursera Worth it?
So far, we have looked that how TensorFlow certification can help you to outshine your competition and learn TensorFlow in depth. Now let's deep dive into this course to find out more. We will review this course on three parameters, instructor quality, course content and public opinion. These are my three pillars to find good course and It almost always work.
1. The Instructors Review
This course's instructor is Laurence Moroney, one of the most popular Coursera instructor for AI And Machine Learning. Lawrence have taught more than 318k learners in the Coursera platform with 15 courses.
Laurence Moroney also leads AI Advocacy at Google, with a vision to make AI easy for developers and to widen access to Machine Learning careers for everyone.
Laurence Moroney has also written many books about programming and machine learning, and artificial intelligence. he most recent being ‘AI and ML for Coders’ at O’Reilly, which is also one of the most recommended book to learn AI and Machine Learning.
In short, you are in good hands as you will learn TensorFlow from an expert who really knows what is talking about and have tested the battlefield himself.
2. Course Content and Structure
2.1. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
You will start this section by understanding machine learning and deep learning and how they offer a new programming paradigm by learning from the data without explicitly being programmed every time to solve a problem.
Next, you will learn how to use deep learning and machine learning to solve computer vision problems with just a few lines of code and code a computer vision neural network.
You’ve seen how to create a basic neural network for computer vision, but it wasn’t that accurate. You will now learn how to optimize this neural network and implement pooling and convolutional layers. Finally, learn about how to deal with larger datasets and use the image Generator function.
2.2. Convolutional Neural Networks in TensorFlow
After you learned so much about the convolutional neural networks (CNN) and how to use them, you will dive deeper into this CovNet model and how to e its performance, especially when performing classification.
Next, you will learn a technique called augmentation that is used to expand the size of your training dataset, meaning creating other images based on the images you already have.
Later, you will learn about transfer learning, how to use pre-trained models on an extensive dataset to solve your deep learning problems, and how to code your own model using transfer learning. Finally, learn the multi-class classification instead of classifying two objects like cats and dogs in most previous examples.
2.3. Natural Language Processing in TensorFlow
Natural language processing (NLP) is the science that lets computers interact with the human language like reading the text, translating the text, talking to humans, measure sentiment, and more and you will start this section by understanding the sentiment in text and the word base encoding and working with tokenization.
Next, you will learn about word embedding, which is a word representation, and the same word that shares the same meaning will have the same representation and apply this concept on the IMBD reviews dataset.
Later, you will need the sequence model that will make the sentiment analysis more accurate. You will implement LSTM models in the code and use convolutional networks. Finally, use what you’ve learned to generate poetry.
2.4. Sequences, Time Series, and Prediction
This time you will dive more into the sequences and predictions and see some considerations when working with sequential models like the values that often change like the temperature and make forecasting.
Next, create a deep neural network to recognize and predict time series using a single-layer neural network.
Later, you will use the recurrent neural network (RNN) and long-short term memory (LSTM) to classify and predict sequential data. Finally, use what you have learned in this specialization to make a model that predicts the sunspot using real data.
3. People's Review
That's all on this review of TensorFlow Developer Professional Certificate on Coursera. TensorFlow gained too much popularity among companies and researchers since it is open-source. Hence, all people worldwide contribute to the development and its easiness to be deployed and use on the web. This course can be your start in the journey of learning artificial intelligence using the TensorFlow framework.
- Top 10 Coursera Certifications to start your career
- 15 Free Coursera Courses for Beginners to Join in 2022
- 7 Best Johns Hopkins course to learn Data Science
- 10 Coursera Specialization and Certifications to learn Python
- Review is Web Applications for Everybody worth it?
- 18 Coursera Courses to learn from top Tech Companies like Google and IBM
- Top 10 Coursera Projects for Programmers and Developers
- Udemy vs. CodeCademy vs. OneMonth?
- Top 5 Computer Science Degrees you can join online on Coursera
- Udemy vs. Educative vs. CodeCademy? Which is better for beginners
- 8 Projects You can do to learn Python in 2022
- Udemy vs Coursera? which is better to learn Tech and Programming
- Coursera Plus Review - A better way to learn on Coursera
- Do Coursera Certificates help in Job and Career?
- Udemy vs Pluralsight? Which is a better learning platform?
- 7 Best courses to learn Artificial Intelligence in 2022
- 5 Data Science degrees you can earn on Coursera Online
- 5 Best Coursera Professional Certificates for Programmers
Thanks for reading this article so far. If you like this review of TensorFlow Developer Professional certificate on Coursera please share them with your friends and colleagues. If you have any questions or feedback then, please drop a note.
Post a Comment