Learning Path

Deep Learning Track

A Deep Learning engineer builds models using deep learning neural networks to draw business insights, which can be used to make business decisions.

10 Courses
104 Hours in Total
10 Case Studies
Lifetime access to course Content

Market Opportunity

The U.S. Bureau of Labor Statistics indicated that computer and information research scientists would experience a job growth rate of 11% from 2014 to 2024.

Career Opportunity

An average annual income of $109,087 was reported for these professionals by Glassdoor.com for US Market.

Rare skills

What You Will Learn

  • Understand the intuition behind Artificial Neural Networks and apply them in practice
  • Understand the intuition behind Convolutional Neural Networks and apply them in practice
  • Understand the intuition behind Recurrent Neural Networks and apply them in practice
  • Understand the intuition behind Self-Organizing Maps and apply them in practice
  • Make a virtual Self Driving Car with Deep Q-Learning
  • Make AI beat games with Deep Convolutional Q-Learning and AC3
  • Optimize business processes with Thompson Sampling
  • Maximize revenues and minimize costs with Deep Q-Learning
  • Build a Hybrid Intelligent Systems
  • Learn and apply Mixture Density Network, Genetic Algorithms, Evolution Strategies.
Deep Learning A-Z™: Hands-On Artificial Neural Networks
1
22 hours
Deep Reinforcement Learning 2.0
2
9 hours
Modern Natural Language Processing in Python
2
6 hours
Natural Language Processing
Computer Vision
A Complete Guide on TensorFlow 2.0 using Keras API
3
13 hours
TensorFlow 2.0 Practical
4
12 hours
Learn BERT - most powerful NLP algorithm by Google
3
5 hours
TensorFlow 2.0 Practical Advanced
5
13 hours
Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs
2
11 hours
Natural Language Processing (NLP) with BERT Practical [FREE]
4
1 hours
Deep Learning and NLP A-Z™: How to create a ChatBot
5
12 hours

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An AI engineer builds AI models using machine learning algorithms and deep learning neural networks to draw business insights, which can be used to make business decisions.

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TensorFlow 2.0 Track

A TensorFlow specialist utilizes the vast knowledge of the TensorFlow library to create everything from neural networks to chat bots as a means to solve a myriad of problems in data science.

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