Machine Intelligence - an Introductory Course

Learn the cutting-edge Algorithms in the field of Machine Learning, Deep Learning, Artificial Intelligence, and more!
Rating: 4.2 out of 5 (111 ratings)
11,585 students
English
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Machine Learning algorithms
Artificial Intelligence algorithms
Information Retrieval algorithms
Deep Learning algorithms
Quantum Computing algorithms
Computer Vision algorithms
Natural Language Processing algorithms

Requirements

  • Understanding of Calculus and Linear Algebra will help better understand most of the concepts discussed here. But you can look for helpful resources alongside studying this course.

Description

This course focuses on the theoretical aspects of the field of Data Science and Machine Learning. It helps the students to quickly gain an in-depth overview of different algorithmic techniques used in various domains and applications. This course features external links to further enhance the experience and reinforce the concepts acquired. It also provides easy explanations of popular and useful research papers that are driving this field forward.

Who this course is for:

  • Aspiring and Professional Data Scientists and Machine Learning Engineers.
  • Students pursuing their PhD and looking for a refresher course.

Course content

2 sections10 lectures40m total length
  • Introduction to Survival Analysis
    02:38
  • Censorship
    03:49
  • The Survival Function and the Hazard Function
    02:36
  • Kaplan-Meier Estimate and Nelson Aalen Fitter
    03:09
  • Survival Regression - Cox Proportional Hazard Regression Model
    06:39

Instructor

Machine Learning Engineer
Taimur Zahid
  • 4.1 Instructor Rating
  • 652 Reviews
  • 35,856 Students
  • 3 Courses

I am a Machine Learning Engineer, with three years of experience in the field of Data Science and Machine Learning. I am a Former Teaching Assistant for the Deep Learning Master's Degree Course and the Natural Language Processing Course. I have worked on a wide range of projects including, but not limited to, Real-time Vehicle Detection and Tracking, Financial Time-Series Forecasting, and Anomaly Detection in Images.

My goal with these courses is to help you stand out in the field of Data Science and Engineering. I follow the agile development methodologies to design, create, and publish my courses. I follow incremental sprints to update my courses regularly by either adding new content to existing courses or creating an entirely new course. This allows me to not only respond to and structure my courses based on direct student feedback, but also, to add the latest skill in demand as quickly as possible.