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Artificial Intelligence

This intermediate-level course introduces the principles of deep learning and artificial intelligence and addresses their main applications.


Starts 20th June 2024

About This Course

This course provides an intermediate level of study in artificial intelligence and learning models. It is designed to help students, data sciences and allied professions to understand critical concepts to their work. It is mainly focusing on different deep learning networks which can be used in different applications such as computer vision as well as natural language processing. The first part will review main concepts of machine and deep learnings, it discusses some essential methods to get you started. Further, the course will cover deep learning in computer vision application, convolutional neural nets. Next, will focus on recurrent neural nets which are mainly used in natural language processing, followed by generative models. Finally, we will finish by doing some hands-on coding practice to each aspect of the course.

Who Is This Course For

The course is well suited for the individual with Undergraduate and Postgraduate degrees in STEM.

What you'll learn

  • Learning the basics of machine learning and deep learning
  • Gain familiarity with many of the most common techniques in computer vision
  • Explore the use of powerful CNN networks in image analysis
  • Learning about RNN with applications in natural language processing
  • Practical session that students will learn to implement, train and test different neural networks and how to design their own models

Course Content

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Meet Your Instructor

Dr. Roushanak Rahmat

Dr. Roushanak Rahmat is an AI research scientist with research interests in medical imaging and cancer research. She was working on deep learning modeling for early detection of lung cancer at the Institute of Cancer Research (ICR), London. Before joining ICR, she was researching at the department of Neurosurgery, University of Cambridge and the School of Computer Science of the St. Andrews University. She obtained her PhD in Electrical, Electronics and Computer Engineering at Heriot-Watt University.

Our Partners

We are proud to partner with the leading In2scienceUK as a step towards achieving our mission of imparting quality education and knowledge across the globe.

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Usually, there are no general prerequisites when enrolling for any individual courses on However, some courses are certainly more advanced than others that are of introductory and intermediate level. For advanced-level courses, prior knowledge on the topic will be helpful for understanding complex concepts but not mandatory.

The relevant information about the suggested knowledge and background that might be helpful to follow each course is provided on the respective course registration page.

Yes, the courses are flexible and self-paced to suit your schedule. The term “self-paced” implies that the courses do not follow a pre-assigned schedule for learning within the course duration. You will be able to access all the course materials for each course that you have enrolled in as soon as the course begins.

The course completion certificate is CPD accredited. For more informations please visit