Tensorflow 2.0: Deep Learning and Artificial Intelligence
- Created by Lazy Programmer Team
- Course Duration 23.5 hours
- Price USD$1.499.000 VND
- User Rating 4.6
- Platform Udemy
- Course Link Explore Course

Machine Learning & Neural Networks for Computer Vision, Time Series Analysis, NLP, GANs, Reinforcement Learning, +More!
Introduction
Are you ready to dive into the fascinating world of deep learning and artificial intelligence? Look no further! The Tensorflow 2.0: Deep Learning and Artificial Intelligence course is designed to equip you with the knowledge and skills needed to harness the power of deep neural networks. Whether you’re a beginner or an advanced student, this course offers a comprehensive learning experience that will take you from the fundamentals to advanced concepts. Let’s embark on this exciting journey together!
Course Overview
In this section, we’ll provide an overview of the Tensorflow 2.0 course, highlighting its key features and what you can expect to learn. With a focus on breadth and hands-on projects, this course strikes a balance between theory and practical application. You’ll delve into various topics such as natural language processing, computer vision, generative adversarial networks (GANs), recommender systems, and deep reinforcement learning. Get ready to build state-of-the-art AI models!
What You’ll Gain
By enrolling in the Tensorflow 2.0 course, you’ll acquire a wide range of skills and knowledge that will empower you to excel in the field of deep learning and AI. Here’s a glimpse of what you’ll gain:
- Master artificial neural networks (ANNs) and deep neural networks (DNNs).
- Predict stock returns and explore time series forecasting.
- Develop computer vision capabilities for image recognition.
- Build a deep reinforcement learning stock trading bot.
- Create generative adversarial networks (GANs) for various applications.
- Design recommender systems for personalized recommendations.
- Implement natural language processing (NLP) techniques.
- Understand the power of transfer learning and its applications.
- Utilize Tensorflow serving for model deployment with RESTful APIs.
- Export models for mobile and embedded devices using Tensorflow Lite.
- Harness Tensorflow’s distribution strategies for parallelized learning.
- Dive into low-level Tensorflow, gradient tape, and custom model creation.
Who This Course is For
The Tensorflow 2.0: Deep Learning and Artificial Intelligence course caters to a wide range of students, from beginners to advanced learners. Whether you’re taking your first steps in the world of AI or seeking to expand your existing knowledge, this course is designed to accommodate your learning needs. The content is structured to provide a seamless progression from foundational concepts to advanced techniques. So, regardless of your skill level, this course offers something valuable for everyone!
Course Content
Now, let’s take a closer look at the comprehensive content you’ll encounter throughout the Tensorflow 2.0 course. Here’s a glimpse of what you’ll explore:
1. Introduction to Tensorflow 2.0
- Discover the evolution and significance of Tensorflow as Google’s library for deep learning and AI.
- Uncover the remarkable achievements enabled by deep learning, from GANs and deep reinforcement learning to computer vision and natural language processing.
- Understand why Tensorflow is the go-to library for deep learning and how it’s shaping the AI landscape.
2. Deep Learning Foundations
- Lay the groundwork by exploring the fundamentals of machine learning and neural networks.
- Dive into artificial neural networks (ANNs) and deep neural networks (DNNs) to understand their architecture and functioning.
- Gain essential knowledge about derivatives and probability for theoretical understanding.
3. Computer Vision and Image Recognition
- Develop computer vision skills using Tensorflow 2.0.
- Master convolutional neural networks (CNNs) for image processing tasks.
- Unlock the potential of transfer learning to create state-of-the-art image classifiers.
- Explore image recognition techniques and their applications.
4. Natural Language Processing (NLP)
- Delve into the world of natural language processing using deep learning.
- Discover how to apply NLP techniques for tasks such as sentiment analysis, text generation, and language translation.
- Dive into deep learning architectures for NLP, including recurrent neural networks (RNNs).
5. Reinforcement Learning and Stock Trading Bot
- Unleash the power of deep reinforcement learning for stock trading.
- Build a deep reinforcement learning stock trading bot from scratch using Tensorflow 2.0.
- Understand the theoretical foundations of reinforcement learning and apply them in practical scenarios.
6. Generative Adversarial Networks (GANs)
- Embark on an exciting journey into the realm of GANs.
- Learn how to generate realistic images using GANs.
- Explore the potential applications of GANs in various domains.
7. Recommender Systems
- Gain expertise in building recommender systems.
- Understand the techniques behind personalized recommendations.
- Explore collaborative filtering and content-based filtering approaches.
8. Advanced Tensorflow Topics
- Dive into advanced concepts and topics in Tensorflow 2.0.
- Discover how to deploy models with Tensorflow Serving in the cloud.
- Learn about Tensorflow Lite for mobile and embedded applications.
- Explore distributed Tensorflow training using distribution strategies.
- Harness the power of low-level Tensorflow, gradient tape, and custom model creation.
Conclusion
Congratulations! You’ve been introduced to the exciting Tensorflow 2.0: Deep Learning and Artificial Intelligence course. This comprehensive online program empowers students at all skill levels to master the world of deep neural networks and AI. From computer vision to NLP, GANs to reinforcement learning, you’ll gain the expertise needed to build cutting-edge AI models. Don’t miss this opportunity to join the ranks of AI practitioners. Enroll today and unlock the potential of Tensorflow 2.0!
FAQs
Q1: What are the prerequisites for enrolling in the Tensorflow 2.0 course? A: It is recommended to have prior coding experience in Python and familiarity with Numpy. For the theoretical sections, understanding derivatives and probability is helpful but not mandatory.
Q2: Is this course suitable for beginners? A: Absolutely! The Tensorflow 2.0 course caters to both beginners and advanced students. The content is structured to accommodate learners at different skill levels, ensuring a smooth learning experience for everyone.
Q3: Can I apply the knowledge from this course to real-world projects? A: Yes! Throughout the course, you’ll work on various hands-on projects that simulate real-world scenarios. These projects will equip you with the practical skills needed to apply deep learning and AI techniques to real-world problems.
Q4: Will I receive a certificate upon completing the course? A: Yes! Upon successfully completing the Tensorflow 2.0 course, you will receive a certificate of completion. This certificate will validate your achievement and can be showcased to demonstrate your expertise in deep learning and AI.
Q5: How can I access the course materials? A: The course materials, including 23.5 hours of on-demand video content, can be accessed anytime and anywhere. You’ll have full lifetime access to the course, allowing you to learn at your own pace and revisit the materials whenever needed.
Now that you’ve learned more about the Tensorflow 2.0: Deep Learning and Artificial Intelligence course, it’s time to embark on this transformative journey. Don’t miss out on the opportunity to master the power of deep neural networks and AI. Enroll now and unlock a world of possibilities!