Udacity: Aws Machine Learning Engineer

You’ll master the skills necessary to become a successful ML engineer. Learn the data science and machine learning skills required to build and deploy machine learning models in production using Amazon SageMaker.

SKU: UdacityAWSMachineLearningEngineer Categories: , Tags: ,

Additional information

Course Page

https://www.udacity.com/course/aws-machine-learning-engineer-nanodegree–nd189

Program Length

5 Months At 5-10 hours/week

Instructors

Matt Maybeno, Joseph Nicolls, Charles Landau, Soham Chatterjee, Bradford Tuckfield

Cohort-Based Course?

yes

Course Features

-Real-world projects from industry experts With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want. -Technical mentor support Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track. -Career services You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role. -Flexible learning program Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Program Format

Recorded

Prerequisites

A well prepared student will be familiar with Python programming knowledge, including: At least 40 hours of programming experience Familiarity with data structures like dictionaries and lists Experience with libraries like NumPy and pandas Knowledge of functions, variables, loops, and classes Exposure to Python through Jupyter Notebooks is recommended Experience with constructing and calling HTTP API endpoints is recommended Basic knowledge of machine learning algorithms, including: Basic understanding of the machine learning workflow Basic theoretical understanding of ML algorithms such as linear regression, logistic regression, neural network Basic understanding of model training and testing processes Basic knowledge of commonly used metrics for ML models evaluation such as accuracy, precision, recall, and mean square error (MSE)

Who is this course for?

The course is for individuals who are looking to advance their engineering careers with cutting-edge machine learning skills

Pricing

Yes

Financing Options

1. Learn now, pay later with affirm 2. Buy with payments as low as $113 per month at 0% APR 3. Pay monthly using bank, check or debit card.

Refund Policy

You can cancel and unenroll within the first 2 days from your first month’s subscription purchase date in order to be eligible for a full refund. Unless you have graduated from the Nanodegree program, single paid course, or Executive Program within this timeframe. Only one refund may be granted per student per Nanodegree program, single paid course, or Executive Program. If you cancel your subscription and subsequently re-enroll for the same program or course, you will not be entitled to an additional 2-day refund period. You may cancel your subscription at any time after this 2-day refund period and you will not be charged again after the billing period in which you cancelled. You will remain actively enrolled in the program until the end of this billing period.

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