Update the readme with details now that the course is out.

Author: mikeckennedy

README.md

@@ -1,5 +1,38 @@
-# Async Techniques and Examples in Python Course
+# [Async Techniques and Examples in Python Course](https://training.talkpython.fm/courses/explore_async_python/async-in-python-with-threading-and-multiprocessing)
 
-![](https://raw.githubusercontent.com/talkpython/async-techniques-python-course/master/readme_resources/async-python.png)
+[![](https://raw.githubusercontent.com/talkpython/async-techniques-python-course/master/readme_resources/async-python.png)](https://training.talkpython.fm/courses/explore_async_python/async-in-python-with-threading-and-multiprocessing)
 
-Coming soon: [training.talkpython.fm](https://training.talkpython.fm/)
+## Course Summary
+
+Python's async and parallel programming support is highly underrated. In this course, you will learn the entire spectrum of Python's parallel APIs. We will start with covering the new and powerful async and await keywords along with the underpinning module: asyncio. Then we'll move on to Python's threads for parallelizing older operations and multiprocessing for CPU bound operations. We'll close out the course with a host of additional async topics such as async Flask, task coordination, thread safety, and C-based parallelism with Cython.
+
+## What's this course about and how is it different?
+
+This is *the* definitive course on parallel programming in Python. It covers the tried and true foundational concepts such as threads and multiprocessing as well as the most modern async features based on Python 3.7+ with async and await.
+
+In addition to the core concepts and APIs for concurrent programming, you will learn best practices and how to choose between the various APIs as well as how to use them together for the biggest advantage.
+
+In this course, you will: 
+
+* See how concurrency allows improved performance and scalability
+* Build async-capable code with the new async and await keywords
+* Add asynchrony to your app without additional threads or processes
+* Work with multiple threads to run I/O bound work in Python
+* Use locks and thread safety mechanisms to protect shared data
+* Recognize a dead-lock and see how to prevent them in Python threads
+* Take full advantage of multicore CPUs with multiprocessing
+* Unify the thread and process APIs with execution pools
+* Add massive speedups with Cython and Python threads
+* Create async view methods in Flask web apps
+* And lots more
+
+
+## Who is this course for?
+
+Anyone who would like to write Python code that does more, scales better, and takes better advantage of modern, multicore CPUs. Whether you're a web developer or data scientists, you will find a host of techniques to do more faster.
+
+The course is not a beginner Python course, so students with little to no Python language experience should take a foundational course first. We recommend our [Python Jumpstart by Building 10 Apps](https://training.talkpython.fm/courses/explore_python_jumpstart/python-language-jumpstart-building-10-apps) as a prerequisite if needed.
+
+## Take the course today
+
+[**Visit the course page**](https://training.talkpython.fm/courses/explore_async_python/async-in-python-with-threading-and-multiprocessing) and get started today.