• Anytime
    Application Deadline
  • 3 days
    Duration
The MOST in-depth look at neural network theory, and how to code one with pure Python and Tensorflow in the Data Science - Deep Learning in Python Course offered by Udemy.

About

This Data Science - Deep Learning in Python Course offered by Udemy will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks right out of the gate using Python and Numpy. All the materials for this course are FREE.

You should take this course if you are interested in starting your journey toward becoming a master at deep learning, or if you are interested in machine learning and data science in general. We go beyond basic models like logistic regression and linear regression and I show you something that automatically learns features.

This course provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we'll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.

Detailed Programme Facts

  • Deadline and start date A student can apply at any time for this programme, there is no deadline.
  • Programme intensity Part-time
    • Average part-time duration 3 days
    • Duration description
      9.5 hours on-demand video
  • Languages
    • English
  • Delivery mode
    Online
  • More information Go to the programme website

Programme Structure

Courses include:

  • Preliminaries: From Neurons to Neural Networks
  • Classifying more than 2 things at a time
  • Training a neural network
  • Practical Machine Learning
  • TensorFlow, exercises, practice, and what to learn next
  • Project: Facial Expression Recognition
  • Backpropagation Supplementary Lectures
  • Appendix

Audience

  • Students interested in machine learning - you'll get all the tidbits you need to do well in a neural networks course
  • Professionals who want to use neural networks in their machine learning and data science pipeline. Be able to apply more powerful models, and know its drawbacks.

English Language Requirements

This programme may require students to demonstrate proficiency in English.

Academic Requirements

  • How to take partial derivatives and log-likelihoods (ex. finding the maximum likelihood estimations for a die)
  • Install Numpy and Python (approx. latest version of Numpy as of Jan 2016)
  • Don't worry about installing TensorFlow, we will do that in the lectures.
  • Being familiar with the content of my logistic regression course (cross-entropy cost, gradient descent, neurons, XOR, donut) will give you the proper context for this coursea

Tuition Fee

  • International

    180 EUR/full
    Tuition Fee
    Based on the original amount of 180 EUR for the full programme and a duration of 3 days.
  • EU/EEA

    180 EUR/full
    Tuition Fee
    Based on the original amount of 180 EUR for the full programme and a duration of 3 days.
We've labeled the tuition fee that applies to you because we think you are from and prefer over other currencies.
Udemy continuously offers discounts up to 94% off with full lifetime access to the course. Check the discounts available by clicking "Visit Programme Website".

Funding

Check the programme website for information about funding options.

StudyPortals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

The Global Study Awards: get funded with up to £10,000 to study abroad

Together with the ISIC Association and British Council IELTS, Studyportals offers you the chance to receive up to £10000 to expand your horizon and study abroad. We want to ultimately encourage you to study abroad in order to experience and explore new countries, cultures and languages.