Description
Become an Expert in Deep Reinforcement Learning is a deep reinforcement learning course published by Udacity Academy. Deep reinforcement learning is one of the technologies related to artificial intelligence and deep learning that has been used in a wide range of industries, the most prominent of which are video games and robotics. Among the most important algorithms in this technique are DQN (Deep Q-Networks) and DDPG (Deep Deterministic Policy Gradients) which are used in various projects such as self-propelled vehicles. Using these algorithms, various operators and neural networks can be trained to perform very complex and time-consuming tasks with high precision. At the end of this training, you will build a complete portfolio and be ready to enter the job market.
Apple, Google, and Facebook are some of the most prominent companies that have made countless advancements by investing in deep learning algorithms. This course is an advanced and highly specialized course, and before starting this course, students should have a relative mastery of topics such as Python programming fundamentals, statistics and probability, machine learning and deep learning, etc.
What you’ll learn in Becoming an Expert in Deep Reinforcement Learning
- Principles and foundations of reinforcement learning
- Architecture and development models of deep learning systems
- Receive, store and interpret telecommunications data
- evolutionary algorithm
- Design and development of advanced algorithms to train and practice data on simulated and virtual robots
Course Specifications
Editor: audacity
Instructors: Alexis Cook, Arpan Chakraborty, Matt LeonardLuis Serrano, Cézanne Camacho, Dana Sheahan, Chhavi Yadav, Juan Delgado and Miguel Morales
French language
Advanced level
Number of lessons: 42
Duration: approx. 4 months
course topics
Part 01: Introduction to Deep Reinforcement Learning
Module 01: Introduction to Deep Reinforcement Learning
Part 02: Value-Based Methods
Module 01: Value-Based Methods
Module 02: Career Services
Part 03: Policy-based methods
Module 01: Policy-based methods
Module 02: Career Services
Part 04: Multi-agent reinforcement learning
Module 01: Multi-agent reinforcement learning
Part 05 (optional): Special topics on deep reinforcement learning
Module 01: Special Topics in Deep Reinforcement Learning
Part 06 (optional): Neural networks in PyTorch
Module 01: Neural Networks in PyTorch
Part 07 (optional): IT resources
Module 01: IT resources
Part 08 (optional): C++ programming
Module 01: C++ Basics
Module 02: Performance programming in C++
Become an expert in deep reinforcement learning
What are the registration conditions?
We recommend taking a Deep Learning course equivalent to the Deep Learning Nanodegree program before entering the program. You will need to be able to communicate fluently and professionally in written and spoken English.
In addition, you must have the following knowledge:
- Intermediate knowledge of Python programming, including:
Strings, numbers and variables Instructions, operators and expressions Lists, tuples and dictionaries Conditions, loops Generators and comprehensions Procedures, objects, modules and libraries Troubleshooting and debugging Research and documentation Problem solving Algorithms and data structures
Basic shell scripts:
- Run programs from a command line
- Debug error messages and comments
- Set environment variables
- Establish remote connections
Basic statistical knowledge, including:
- Populations, samples
- Mean, median, mode
- standard error
- Variation, standard deviations
- Normal distribution
Intermediate differential calculus and linear algebra, including:
- Derivatives and integrals
- Series extensions
- Matrix operations via eigenvectors and eigenvalues
What software and versions do I need in this program?
You will need a computer running a 64-bit operating system (most modern Windows, OS. Your network must allow secure connections to remote hosts (such as SSH). We will provide you with instructions for installing the required software packages.
Pictures
Become an expert in deep reinforcement learning Introductory video
installation guide
In order to view the course lessons in an organized and regular manner, run the index.html file and scroll through the videos through this file.
english subtitles
Quality: 720p
Download links
File password(s): free download software
size
2.2 GB