AI: Machine Learning with Python

Learn to create Machine Learning Algorithms in Python and use your Data to Predict Future events.

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data.

Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.
Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.
Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.
Google famously announced that they are now "machine learning first", meaning that machine learning is going to get a lot more attention now, and this is what's going to drive innovation in the coming years. It's embedded into all sorts of different products.
Machine learning is used in many industries, like finance, online advertising, medicine, and robotics.
It is a widely applicable tool that will benefit you no matter what industry you're in, and it will also open up a ton of career opportunities once you get good.
Machine learning also raises some philosophical questions. Are we building a machine that can think? What does it mean to be conscious? Will computers one day take over the world?
In this course, you will learn how Python developers and data scientists use machine learning to predict the likelihood of events based on data. Throughout this course, you will use Python and the scikit-learn library. Specifically, you will learn how to format your problem to be solvable, how to prepare your data for use in a prediction, and finally how to combine that data with algorithms to create models that can predict the future, all performed in the Jupyter Notebook environment. By the end of this course, you will have a better understanding of how machine learning can help you put your data to good use in predicting future events, and you'll also know how to use Python to make it happen.
This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.


Course Curriculum


  Section 1 Welcome
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  Section 2 Introduction to Machine Learning
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  Section 3 Understanding the Machine Learning Workflow
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  Section 4 How to ask questions
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  Section 5 Preparing Your Data
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  Section 6 Algorithm
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  Section 7 Training the Model
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  Section 8 Testing Your Model's Accuracy
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  Section 9 Outro
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  Working Files
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Bill Gates Says These Are the Jobs He Would Drop Out of College for Today

If he were to go into computer sciences today, Gates said, the area that he thought had the most potential was artificial intelligence. Gates brought up a recent victory by Google DeepMind over the top player in the world at Go, a game some predicted a computer could never master. He called it a remarkable achievement that signaled there is more to come in advancement in artificial intelligence. And he said the research being done in the field now is "profound" and on the verge of making new breakthroughs. "The ability for artificial agents to read and understand material is going to be phenomenal," says Gates. "Anything connected with that would be an exciting lifetime career."

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Frequently Asked Questions


When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

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