Machine Learning with Jupyter Notebooks in Amazon AWS

Machine Learning with Jupyter Notebooks in Amazon AWS, available at $49.99, has an average rating of 4.2, with 46 lectures, 4 quizzes, based on 86 reviews, and has 13065 subscribers.

You will learn about Be able to define machine learning Learn about the different types of machine learning algorithms Get a closer look at deep learning and reinforcement learning Learn how Jupyter Notebooks work Learn how AWS Sagemaker does machine learning Go through the process of implement a machine learning model on data Learn how AWS Comprehend contributes to Machine Learning Learn how to analyze documents with AWS Comprehend This course is ideal for individuals who are Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game or Anyone who is curios about machine learning It is particularly useful for Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game or Anyone who is curios about machine learning.

Enroll now: Machine Learning with Jupyter Notebooks in Amazon AWS

Summary

Title: Machine Learning with Jupyter Notebooks in Amazon AWS

Price: $49.99

Average Rating: 4.2

Number of Lectures: 46

Number of Quizzes: 4

Number of Published Lectures: 46

Number of Published Quizzes: 4

Number of Curriculum Items: 50

Number of Published Curriculum Objects: 50

Original Price: $119.99

Quality Status: approved

Status: Live

What You Will Learn

Be able to define machine learning
Learn about the different types of machine learning algorithms
Get a closer look at deep learning and reinforcement learning
Learn how Jupyter Notebooks work
Learn how AWS Sagemaker does machine learning
Go through the process of implement a machine learning model on data
Learn how AWS Comprehend contributes to Machine Learning
Learn how to analyze documents with AWS Comprehend

Who Should Attend

Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game
Anyone who is curios about machine learning

Target Audiences

Beginner IT professionals who want to get in the forefront of the Artificial Intelligence and Machine Learning game
Anyone who is curios about machine learning

Are you a company or a IT administrator, data center architect, consultant, enterprise architect, data protection officer, programmer, data security specialist, or big data analyst and want to gain fundamental and intermediate level skills and enjoy a fascinating high paying career?

Or maybe you just want to learn additional tips and techniques taking to a whole new level?

Welcome to Machine Learning, Reinforcement Learning and AWScourse For Beginners. A one of its kind course

The flipped classroom model with hand-on learning will help you experience direct into the course as your begin your learning journey. Be sure to watch the preview lectures that set course expectations

In this course, you’ll learn and practice:

Machine Learning topics
Jupyter Notebooks
Reinforcement Learning
Machine Learning Services in AWS
AWS Sage maker
Dynamic Programming
Q-Learning
Understand best practices, and much more

You will also get complete resources, toolkit, and code where applicable with this course! We’ve built this course with our Team ClayDesk of industry recognized developers and consultants to bring you the best of everything

So, if you would like to:

start your freelancing career and consult companies, this course is for you
gain marketable skills as an IT expert and professional, this course is for you

This course is not designed for advanced level students

This Machine Learning, Reinforcement Learning and AWS course is exactly what you need, and more. You’ll even get a certification of completion

See what our students say “It is such a solid course that covers all important areas of machine learning, and I now know hoe to predict future products based on their features. Simply awesome!.” – Alex Neuman

“This is such an awesome course. I loved every bit of it. Wonderful learning experience!” Ankit Goring.

Join thousands of other students and share valuable experience

Why take this course?

As an enterprise architect consulting with global companies, technology evangelist, and brand innovator, I have designed, created, and implemented enterprise level projects, I am excited to share my knowledge and transfer skills to my students.

Enroll now in Machine Learning, Reinforcement Learning and AWS today and revolutionize your learning. Stay at the cutting edge of Machine Learningand Data Science —and enjoy bigger, brighter opportunities with AWS.

Qasim Shah

Team ClayDesk

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Agenda

Lecture 2: Where is Machine Learning and AI going

Lecture 3: Creating a billing alert

Lecture 4: AWS Unified Search – New in AWS Management Console

Lecture 5: *NEW* EC2 Dashboard Experience

Chapter 2: Working with Jupyter Notebooks

Lecture 1: What is a notebook and installing Jupyter

Lecture 2: Creating your first Jupyter Notebook through Anaconda

Lecture 3: A closer look at Jupyter Kernals

Lecture 4: Data analysis in Jupyter

Lecture 5: Plotting with Matplotlib in Jupyter

Chapter 3: Test your Jupyter Knowledge

Chapter 4: Machine Learning

Lecture 1: Reinforcement Learning

Lecture 2: Reinforcement Learning in action

Lecture 3: Basics of Machine Learning

Lecture 4: Supervised Learning

Lecture 5: Unsupervised Learning

Lecture 6: Deep Neural Networks

Lecture 7: Neural Network Techniques

Chapter 5: Machine Learning Quiz

Chapter 6: Reinforcement Learning

Lecture 1: Modeling a Reinforcement Learning environment

Lecture 2: What is dynamic programming

Lecture 3: A deeper look at Q-Learning

Lecture 4: Q-Learning: Place the Queen

Lecture 5: Q-Learning: trying to find the shortest path

Lecture 6: Dynamic programming in action

Chapter 7: Reinforcement Learning Quiz

Chapter 8: Machine Learning in AWS

Lecture 1: The AWS Machine Learning Service

Lecture 2: First steps in building a ML Model

Lecture 3: Understanding AWS Datasources

Lecture 4: ML Training Models

Lecture 5: Importance of Feature Transformation

Lecture 6: Evaluating Models

Lecture 7: Preparing data for Machine Learning

Lecture 8: Creating a datasource and model in AWS

Lecture 9: Serverless ML Inference with AWS Lambda

Chapter 9: AWS SageMaker

Lecture 1: What is SageMaker

Lecture 2: Setting up AWS to use SageMaker

Lecture 3: Machine Learning in SageMaker

Lecture 4: Intro to Linear Learner

Lecture 5: Preparing data for Linear Learner algorithm

Lecture 6: Training data using Linear Learner

Lecture 7: Creating a hyperparameter tuning job

Chapter 10: SageMaker Quiz

Chapter 11: Learning Resources – Conducting Machine Learning experiments in Microsoft Azure

Lecture 1: Converting data with Windows PowerShell

Lecture 2: Getting started with ML Studio

Lecture 3: Uploading data onto Azure ML Studio

Lecture 4: How to process data

Lecture 5: Conducting an experiment

Lecture 6: How to deploy a web service

Lecture 7: ML Business Use case

Instructors

Qasim Shah
Enterprise Architect, Digitization Expert & Teacher
Syed Raza
Best Selling Instructor, Enterprise Architect, 8x AWS, PhD

Rating Distribution

1 stars: 7 votes
2 stars: 4 votes
3 stars: 23 votes
4 stars: 23 votes
5 stars: 29 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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