UDACITY - Become a Machine Learning Engineer Nanodegree Program Full Course Free Download

UDACITY - Become a Machine Learning Engineer Nanodegree Program Full Course Free Download 2019-06-04

[NEW] Become a Machine Learning Engineer Nanodegree Program
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udacity machine learning nanodegree

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Start with Intro to Machine Learning if you are a beginner.
Start with Machine Learning Engineer if you already have some experience.​

The Intro to Machine Learning program is for students with Python experience, and covers foundational machine learning algorithms. The Machine Learning Engineer program is for students with some ML background, and covers production and deployment.

Intro to Machine Learning

Learn foundational machine learning algorithms, starting with data cleaning and supervised models. Then, move on to exploring deep and unsupervised learning. At each step, get practical experience by applying your skills to code exercises and projects.

This program is intended for students with experience in Python, who have not yet studied Machine Learning topics.

PREREQUISITE KNOWLEDGE

To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and basic knowledge of probability and statistics.See detailed requirements.
  • Supervised Learning
    In this lesson, you will learn about supervised learning, a common class of methods for model construction.
  • Deep Learning
    In this lesson, you’ll learn the foundations of neural network design and training in PyTorch.
  • Unsupervised Learning
    In this lesson, you’ll learn to implement unsupervised learning methods for different kinds of problem domains.
Program Two: Machine Learning Engineer

Machine Learning Engineer
Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry.

This program is intended for students who already have knowledge of machine learning algorithms.

PREREQUISITE KNOWLEDGE

To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and intermediate knowledge of machine learning algorithms.See detailed requirements.
  • Software Engineering Fundamentals
    In this lesson, you’ll write production-level code and practice object-oriented programming, which you can integrate into machine learning projects.

  • Machine Learning in Production
    Learn how to deploy machine learning models to a production environment using Amazon SageMaker.
  • Machine Learning Case Studies
    Apply machine learning techniques to solve real-world tasks; explore data and deploy both built-in and custom-made Amazon SageMaker models.
  • Machine Learning Capstone
    In this capstone lesson, you’ll select a machine learning challenge and propose a possible solution.
Build a solid foundation in Supervised, Unsupervised, and Deep Learning. If you do not have experience with machine learning, take this before the Data Scientist Nanodegree program.

Learn advanced machine learning techniques and algorithms, including deployment to a production environment

Intro to Machine Learning Nanodegree Program

Machine learning is changing countless industries, from health care to finance to market predictions. Currently, the demand for machine learning engineers far exceeds the supply. In this program, you’ll apply machine learning techniques to a variety of real-world tasks, such as customer segmentation and image classification. This program is designed to teach you foundational machine learning skills that data scientists and machine learning engineers use day-to-day.

This program emphasizes practical coding skills that demonstrate your ability to apply machine learning techniques to a variety of business and research tasks. It is designed for people who are new to machine learning and want to build foundational skills in machine learning algorithms and techniques to either advance within their current field or position themselves to learn more advanced skills for a career transition.

This program assumes that you have had several hours of Python programming experience. Other than that, the only requirement is that you have a curiosity about machine learning. Do you want to learn more about recommendation systems or voice assistants and how they work? If so, then this program is right for you.

Machine Learning Engineer Nanodegree Program

As more and more companies are looking to build machine learning products, there is a growing demand for engineers who are able to deploy machine learning models to global audiences. In this program, you’ll learn how to create an end-to-end machine learning product. You’ll deploy machine learning models to a production environment, such as a web application, and evaluate and update that model according to performance metrics. This program is designed to give you the advanced skills you need to become a machine learning engineer.

Students in the Machine Learning Engineer Nanodegree program will learn about machine learning algorithms and crucial deployment techniques, and will be equipped to fill roles at companies seeking machine learning engineers and specialists. These skills can also be applied in roles at companies that are looking for data scientists to introduce machine learning techniques into their organization.

This program assumes that you are familiar with common supervised and unsupervised machine learning techniques. As such, it is geared towards people who are interested in building and deploying a machine learning product or application. Are you interested in deploying an application that is powered by machine learning? If so, then this program is right for you.

Intro to Machine Learning Nanodegree Program

It is recommended that you have the following knowledge, prior to entering the program:

Intermediate Python programming knowledge, including:
  • At least 40hrs of programming experience
  • Familiarity with data structures like dictionaries and lists
  • Experience with libraries like NumPy and pandas is a plus
Basic knowledge of probability and statistics, including:
  • Experience calculating the probability of an event
  • Knowing how to calculate the mean and variance of a probability distribution is a plus
Machine Learning Engineer Nanodegree Program

Intermediate Python programming knowledge, including:
  • At least 40hrs of programming experience
  • Familiarity with data structures like dictionaries and lists
  • Experience with libraries like NumPy and pandas
Intermediate knowledge of machine learning algorithms, including:
  • Supervised learning models, such as linear regression
  • Unsupervised models, such as k-means clustering
  • Deep learning models, such as neural networks
intro to machine learning nanodegree

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