Course Preview: Professional Certificate in Machine Learning and Artificial Intelligence from Imperial College Business School Executive Education

20 October 2022

[Video Transcript] Professional Certificate in Machine Learning and Artificial Intelligence from Imperial College Business School Executive Education

Ready to Learn More? Apply to Enrol in: Professional Certificate in Machine Learning and Artificial Intelligence

Hello and welcome to Imperial College's Professional Certificate in Machine Learning and Artificial Intelligence.

I'm Wolfram Wiesemann, Professor of Analytics and  Operations at Imperial College Business School as well as by courtesy of the Department of Computing at Imperial College London and I'm one of the four faculty for this programme. We're excited to work with you over the next 25 modules to build your skills and understanding of the machine learning and artificial intelligence industry. To get you started, I'd like to share a bit more about the structure of this programme. The programme includes three distinct phases.

The first one is on the foundations of machine learning and artificial intelligence. The second one focuses on methods. And the third one is on advanced topics such as deep learning, neural networks, and more. We structured this curriculum including the lectures, activities, and resources so that you will start with foundational skills and competencies that are vital to the machine learning and artificial intelligence community. As you progress, you will learn more about the most common as well as some pretty advanced machine learning methods. And as well as some of the popular applications of machine learning technology. You'll also learn and apply a variety of different strategies for evaluating the output of those methods, as well as selecting the best among several different models.

You'll see me throughout the different phases of this programme where we cover four different aspects. First of all, I will cover the foundations of machine learning such as the distinction between training sets and validation sets, and test sets. I will cover some of the underlying mathematics such as generalisation theory. I will discuss how to assess the performance of the machine learning method, as well as a whole variety of different machine learning techniques ranging from k-nearest neighbours and Naive Bayes to decision trees, support vector machines as well as clustering. Now, let me introduce you to the other professors of this programme.

First, we have Alex Ribeiro-Castro from the Imperial College Business School.

Hi, I'm Alex Ribeiro-Castro. Welcome to the programme, I'm looking forward to working with you. I will be covering first the foundational modules on statistics and probability,  to enable you to speak the language of AI. Later in the programme, I will also cover the foundational material on deep learning and reinforcement learning. By using very simple building blocks, we'll be able to architect very interesting learning machines to tackle tasks ranging from image identification to which marketing campaign is most effective. It's even possible to create a blackjack-playing robot that learns from playing against itself.

All that's to say, there are exciting things ahead. Next, I would like to introduce you to my colleague Ruth Misener from Imperial College's Department of Computing.

Hello, I'm Ruth Misener, a professor in Computational Optimisation at the Imperial  College Department of Computing. So, I'll be joining colleagues Wolfram and Alex from the Business School to bring an additional computer science perspective to this programme. You'll hear me on several of the modules. I get to teach Bayesian optimisation, logistic regression, principal component analysis, and transparency and interpretability in AI. But additionally, I get to lead you through the Capstone project, we'll work on this project throughout the programme. The capstone project is important for your machine learning and AI careers for two reasons. First off, I very much hope you'll use your project well after this programme is finished. So, parameter tuning is important in many practical applications of AI and hopefully you'll use this in your jobs. But secondarily, I'll be introducing you to the world of AI and machine learning competitions. This world is a lot of fun and I hope you enjoy it. So,  last but not least please meet Chris Tucci, the fourth professor for this programme from the Imperial College Business School.

Ready to Learn More? Apply to Enrol in: Professional Certificate in Machine Learning and Artificial Intelligence

Hi, I'm Chris Tucci, Professor of Digital Strategy and Innovation at Imperial College  Business School. Throughout this programme, I'm going to pop in to share case studies and business applications for the skills and techniques you're going to be learning from Wolfram, Alex, and Ruth. I used to work in AI research in my past life and  I got more and more interested in how companies manage the innovation process to bring about efficiencies as well as new products and services. In any case, in this programme I'm going to introduce some really interesting case studies where crowdsourcing participants use AI techniques to solve real problems in the industry such as the Netflix prize and the Zillow prize. We'll go through the challenges that were posed and talk about how well the solutions worked. We'll also talk about other use cases for AI and machine learning such as for reducing credit card fraud, the benefits and pitfalls of automating medical diagnoses, and analysis of drone video for insurance claims.

I'm also going to interview people who work in AI, data science, and business analytics and ask them how they got interested in the topic, their career development paths, and how they used the specific tools and techniques that we'll be going over every week in their jobs. Looking forward to it. Now that you had a chance to meet the faculty, I hope you are as excited to work with us as we are to work with you. One final thing to keep in mind. This programme includes dedicated support for technical issues as well as programme-related questions.

You'll also have the opportunity to learn from the programme's learning facilitators.  These learning facilitators have experience in machine learning and AI, and they will be able to respond to your content-related inquiries. We hope you'll attend their office hours and take full advantage of the hands-on help that is available. Please review the materials in this orientation module for more details on these support channels that are available throughout your enrolment. Let's get started.

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