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Structuring Machine Learning Projects Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
1 days
Duration
1 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

In the Structuring Machine Learning Projects course offered by Coursera in partnership with Deeplearning, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. 

Overview

By the end of the Structuring Machine Learning Projects course offered by Coursera in partnership with Deeplearning, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning.

This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience.

The Deep Learning Specialization is our foundational programme that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.

You will gain

  • Deep Learning
  • Inductive Transfer
  • Machine Learning
  • Multi-Task Learning
  • Decision-Making

Programme Structure

Courses include:

  • ML Strategy

Key information

Duration

  • Part-time
    • 1 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Beginner Level

  • At the rate of 5 hours a week, it typically takes 4 weeks to complete this course. 
  • To obtain additional information about the programme, we kindly suggest that you visit the programme website, where you can find further details and relevant resources.  

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

Audit: free access to course materials except graded items|Certificate: a trusted way to showcase your skills|A year of unlimited access with Coursera Plus $199

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.

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