The Machine Learning Academy

Every Wednesday, 17:45-21:00, 2nd October – 13th November 2019, at IDEALondon, 69 Wilson Street, EC2A 2BB

Deadline for applications: Friday 20th September 2019

The Machine Learning Academy is a free 6 week program running every Wednesday evening from the 2nd October – 13th November, 17:45 – 21:00, designed to introduce founders, entrepreneurs and startup employees who don’t come from a technical background to the basics of Machine Learning and how it can be incorporated successfully into their company. 

The course will start by covering the academic basics of Machine Learning presented by Dr Alastair Moore who teaches Predictive Analytics at UCL and is Head of Analytics and Machine Learning at Mischon de Reya, and guest presenters from companies currently using cutting edge ML applications who will explain practical examples of how it is currently being applied, how it can be applied, and what is theoretically possible with this technology, providing participants with a real world context for the academics they’re taught. The first 3 weeks will delve into the major techniques and technologies under the umbrella of artificial intelligence. We will walk you through the main types of machine learning (namely supervised and unsupervised learning), as well as neural networks and deep learning models.

By the end, you should know the intuitions and business use cases of main algorithms under each type as well as key concepts of model training and optimisation strategies in developing a machine learning pipeline.

“MLA allowed me to explore what ML is and how it can be applied to my business. By combining theoretic approaches with a brief touch on technical knowledge the course allowed me, with a non-technical background, to grasp key aspects of ML. The course expanded my basic knowledge of statistics and demonstrated how these basics support ML methods. I’m now more encouraged to use these in my own business as well as form teams to approach these types of problems. The lectures are well structured and informative supported by further reading to assist with topics being covered. MLA made me think differently about Evidefy and about the architectural profession as a whole. No matter your background or level of knowledge, you need this understanding to have a chance in a world where machine learning and AI are radically changing every industry.”

Bethany Penman

CEO, Evidefy

Once we’ve covered the basics and attendees have grasped an initial understanding of what Machine Learning is and how it functions, we will move on to the final three weeks of the course, focused on actually applying ML in your own business. The last 3 weeks will prepare you to think about transforming a business to adopt the power of artificial intelligence; or as an entrepreneur, how to launch an AI business. During the lectures, you will gain hands-on experience from heads or senior managers of data science and analytics on how to develop AI strategy, build and manage an in-house AI team, provide broad AI training, and more.

Every session will begin with 2 hour long lectures on that week’s subject, followed by mingling and networking over free beer and pizza provided. We encourage our cohort to discuss and connect with each other and our guest presenters!


“Having attempted taking an online Machine Learning course, I struggled to grasp the concept. What this course did was break it down, week after week in a classroom environment where questions are asked and answered and world leading practitioners come in and demonstrate ML at work in various industries and disciplines. What’s even more important to point out is we were not just taught the technical aspect, half the course we we were taught business, strategy and implementation. This is a course I strongly recommend to anyone thinking about being ahead of the curve, whatever your industry might be. Alastair Moore is one of the world leading experts in AI so you can be rest assured you are learning from the best. A special gratitude to Capital Enterprise for putting this together!!! The beer and pizza at the end of each session is a great added bonus…”

Berne Omolafe

CEO, Spaceandtime

The programme’s first iteration received nearly 200 applications, and we expect it to be even more competitive this time around! The programme is part funded by the European Regional Development Fund, and free to start-ups and scale-ups who meet the ERDF SME criteria. Attendees will be selected based on those who genuinely wish to apply ML in their business. We limit places to a maximum of two people per company in order to ensure a diverse crowd and to enable us to provide this course to the maximum amount of people. We suggest you therefore apply as a company and specify in your application how many places you are applying for. 

We strongly discourage applicants who cannot commit to a minimum of 5 of the 6 sessions. If you attend the course and cannot complete the required minimum number of sessions, we cannot provide you with a certificate of attendance. 

To apply for one of our 30 places, you must meet the following requirements:

  • Your company must be an SME registered on Companies House with a London address, OR an SME that has proof of trading in London.
  • Your company must be an SME employing fewer than 250 people, with an annual turnover below €50m, and a balance sheet below €43m.
  • We cannot accept your application if anyone from your company attended the previous MLA
The Machine Learning Academy: every Wednesday, 17:45-21:00, 2nd October – 13th November 2019, at IDEALondon, 69 Wilson Street, EC2A 2BB

Detailed course overview:

Each week will consist of two hour long lectures, followed by the chance to network and mingle over free pizza and beer.

Wednesday 2nd October:
Dr Alastair Moore on “The Basics: From Data to Models” and “Designing Predictive Systems: End to End Machine Learning Pipeline”

Machine Learning (ML) has seen significant improvements in recent times, but the discipline has been down many false turns over the years. In the very first lecture Alastair will give some background to the history of the subject and different areas of expertise to put the other weeks in context. We will learn first hand about the bewildering array of applications that ML is now being used for. After a short break, the second lecture will be spent looking at end to end ML pipeline so we can get a feel for the different components of an ML system. We’ll think a bit about the difference between ML and other software systems, and consider what real world ML deployment looks like, how to create scalable ML pipelines and think about production systems.

Wednesday 9th October:
Dr Alastair Moore on “Advanced methods: The Deep Learning Landscape from ANNs to GANs”; Guest speaker TBC.

In the second week we’ll start by looking at the full gamut of modern ML algorithms. We’ll think about their strengths and weaknesses and look at how and where they can be made to work best. This will flesh out the algorithm taxonomy presented in Week 1. Following a short break, in the second lecture we’ll see some real world examples of Deep Learning and find out what it takes to make it work in practise, not just the lab, from a founder who’s startup uses a real application of deep learning.

Wednesday 16th October:
Lucy Caines and Taylor Brownlow from Count; Panel Participants TBC

The third week is designed to present participants with further examples of businesses that successfully use deep learning. Our first lecture will be from the startup ‘Count’, showing a direct application of the data analysis possible with ML. This session will be a hands on workshop working together to explore a dataset using

Count’s new data exploration language. Following the usual short break, we will hear from a panel of startups discussing how they implemented ML in their business, chaired by Capital Enterprise CEO John Spindler.

Wednesday 23rd October:
Business Strategy in a World of Machine Learning

To start the second half of the course we’ll think about how business processes can be viewed as predictive systems and how ML might provide a broad framework for improving processes. We’ll introduce some business strategy frameworks that can be used for a broader conversation about the application of ML as a technology, and look at a broad range of horizontal and vertical examples of where ML can be applied within an organisation.
Designing a Data Enabled Business
In Week 5 we’ll expand on the ideas presented the week previously to look at a few examples of ML strategy. Examples include looking at the use of data mining in ILC business patterns, and frameworks for adopting technologies like Chatbots.

Wednesday 30th October:
Guest Presenter Tim Gordon from Best Practice AI; second guest presenter TBC

Our first lecture this week will walk you through how to actually deploy AI and ML in your organisation and build a competitive advantage with it.
Through discussion and the example of a few case studies, you will learn how to practically implement the ML knowledge you have gained in the rest of the course within your business. The second lecture (TBC) will cover how to make AI safe, and how to make algorithms fair and explainable.

Wednesday 6th November:
Dr Alastair Moore on “Building Machine Learning Teams” and Guest Presenter Adam West from Satalia

In the last week we’ll think about how to build ML teams, revisit some of the differences with conventional software systems, and think about how production systems must be operated and maintained. Our guest presenter, Adam, will speak on the future of AI – using real-life examples and relatable anecdotes to demystify the hype, and align audiences on what it is, what it is not, and what impact it will have in on individuals, organisations, and society. Adam also discusses innovation in the context of AI, and questions whether typical organisational structures and process are setup to attract, retain and empower AI talent. Finally, Adam touches on AI applications both externally and within organisations, including how it’s being used to decentralise decision making, and even set salaries.