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Courtlyn

Promotion and Events Specialist

Professional Certificate in Machine Learning and Artificial Intelligence

Leverage the power of data to accelerate your career.

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Course Date
LAST DAY TO ENROL

Course Duration

DURATION

25 weeks, online
15–20 hours per week

Course Fee

PROGRAMME FEE

£3,995 and get £399 off with a referral

Course Information Flexible payment available
Course Fee

For Your Team

Enrol your team and learn with your peers

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Explore financing options available for this programme.
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Apply, automate and achieve your AI and ML career goals

Machine learning (ML) and artificial intelligence (AI) are pushing the limits of possibility and transforming the world around us. Today, to stay ahead of the curve and seize opportunities for innovation, businesses are quickly realising they must anticipate future trends in ML and AI – and to do so, they must engage professionals who can bridge the gap between vision and execution.

The Professional Certificate in Machine Learning and Artificial Intelligence, a joint programme from Imperial College Business School Executive Education and the Imperial College London's Department of Computing was designed with this need in mind. This 25-week online programme provides an immersive, world-class learning experience delivered by leading experts in the field. It will equip you with a unique combination of advanced technical expertise and business acumen that will give you a competitive edge and help you navigate your job search to find exciting career opportunities in ML and AI.

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Programme highlights

The programme covers cutting-edge skills and business strategies in machine learning and artificial intelligence. It will enable you to:

  • Understand foundational and advanced concepts and trends in artificial intelligence, as well as potential real-world implications
  • Determine when machine learning is feasible and can be meaningfully applied to specific business challenges
  • Leverage the power of data and evaluate common machine learning methods to improve predictive performance and refine decision-making strategies
  • Develop and refine machine learning models using Python and industry standard tools to measure and improve performance
  • Identify real-world problems and devise innovative solutions using machine learning models

97 Million

The projected number of jobs created globally by 2025 due to the acceleration of AI

Source: DataProt

£61,000

The average salary for a machine learning engineer with three years or less of experience

Source: Understanding Recruitment

6X

The expected growth of the global AI market between 2021 and 2028

SOURCE: FORTUNE BUSINESS INSIGHTS
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Who is this programme for?

The Professional Certificate in Machine Learning and Artificial Intelligence requires a background in coding or mathematics. It is particularly relevant for professionals including:

  • IT and Engineering professionals looking to receive hands-on training in ML and AI and upskill themselves in a high-growth field. Job titles may include software engineers and software developers.
  • Data and business analytics professionals who wish to learn about the latest AI tools, techniques and applications to stay ahead of the curve and gain better growth trajectories. Job titles may include business analysts, senior data analysts and data scientists.
  • Recent science, technology, engineering and mathematics (STEM) graduates and academics who are interested in being a part of a cutting-edge field with high growth potential and using technology to make a positive impact on the world.

Applicants must have:

  • A bachelor's degree or higher
  • Strong mathematics skills
  • Some programming experience

Also recommended:

  • An educational background in STEM fields
  • Technical work experience
  • Some experience with Python,R, or SQL
  • Some experience with statistics and calculus

Tools and platforms used in the programme

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What you will learn

Section 1: Foundations of Machine Learning and Artificial Intelligence
In the first seven modules, you will gain an introduction to the underlying elements of machine learning and its statistical nuances, hone your analytical skills and learn leading-edge techniques for evaluating the performance of a machine learning model.


  • Module 1: Programme Orientation
  • Module 2: Introduction to Machine Learning
  • Module 3: Probability for Machine Learning
  • Module 4: Statistics for Machine Learning
  • Module 5: Generalisation Theory and the Bias-Variance Trade-Off
  • Module 6: Evaluating Predictive Performance
  • Module 7: Advanced Topics in Performance Evaluation

Section 2: Methods for Learning from Data
In these modules, you will explore how decision trees can be leveraged to classify or predict outcomes and solve real-world problems, dive deep into the predictive power of logistic regression and determine which machine learning methods are best suited for solving real-life problems unique to your industry.


  • Module 8: Nearest Neighbour Methods
  • Module 9: Decision Trees, Part I
  • Module 10: Decision Trees, Part II
  • Module 11: Naïve Bayes
  • Module 12: Bayesian Optimisation
  • Module 13: Logistic Regression
  • Module 14: Support Vector Machines
  • Module 15: Unsupervised Learning
  • Module 16: Principal Component Analysis

Section 3: Advanced Topics in Artificial Intelligence and Machine Learning
In the final modules, you will explore deep learning and its relationship to machine learning and artificial intelligence, discover the underlying elements of convolutional neural networks and finally practise the skills required for real-world model optimisations in your capstone project.


  • Module 17: Introduction to Deep Learning
  • Module 18: Neural Networks
  • Module 19: Hyperparameters
  • Module 20: Transparency and Interpretability
  • Module 21: Convolutional Neural Networks
  • Module 22: Biological Basis for Convolutional Neural Networks
  • Module 23: Reinforcement Learning
  • Module 24: Hyperparameter Tuning
  • Module 25: Capstone Competition
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Case studies

Case studies and industry examples are drawn from world-class brands and paired with key concepts throughout the programme, providing you the opportunity to examine how machine learning methods can be applied to successfully address business goals.

Capstone competition

For your capstone project, you will challenge your knowledge by developing and/or tuning a code base for a custom-designed machine learning competition modeled after the popular Black-Box Optimisation Challenge. You will practise the skills required for real-world model optimisations for a problem of your choice.

The competition takes place during the last 12 weeks of the programme, enabling you to see how tuning your code base improves optimisation on the competition’s leaderboard.

At the conclusion of the programme, you will have built a resume-boosting code base and amassed the skills needed to enter future competitions for prestige, cash prizes and career recognition.

Programme experience

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Job-ready ML/AI skills in a high-demand field

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Real-world insights from Imperial College London faculty and industry experts

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A hands-on capstone project to share with potential employers

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A verified digital certificate of completion from Imperial College Business School Executive Education

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Associate alumni status from Imperial College London on programme completion

Career preparation and guidance

Breaking into the field of machine learning and artificial intelligence requires a precise combination of technical knowledge and business acumen. Our programme will guide you in developing a career path by assisting you in crafting your elevator pitch and sharpening your interview skills. These services are provided by Emeritus, our learning collaborator for the programme. The support team includes programme leaders and career coaches who will help you reach your learning goals and navigate your job search. The primary goal is to equip you with the skills needed to prepare for a career in machine learning and artificial intelligence. However, we do not guarantee a job placement.

Emeritus offers assistance with the following career services:

  • Live career coaching and open Q&A sessions, resume feedback, mock interviews and career development exercises
  • Access to resume referrals to our employer partners
  • A birds's-eye view of the current job market landscape and five-year market trajectory
  • Assistance in crafting your elevator pitch and preparing for job interviews
  • Insights on negotiating your salary and opportunity to network with global peers and instructors
  • Insights into key industry players, latest trends and industry-specific interviews

Programme faculty

Faculty Member PROFESSOR WOLFRAM WIESEMANN

PROFESSOR WOLFRAM WIESEMANN

Professor, Analytics & Operations; Academic Director, MSc Business Analytics; Associate Director, Centre for Process Systems Engineering; Fellow, Computational Optimisation Group; Fellow, Imperial Business Analytics Department of Computing, Imperial College Business School

Wolfram Wiesemann is a professor and group leader of the Computational Optimisation Group in the Department of Computing at Imperial College London. His teaching focuses on linear, discrete and nonlinear optimisation;... More info

Faculty Member PROFESSOR RUTH MISENER

PROFESSOR RUTH MISENER

Professor, Computational Optimisation Department of Computing, Imperial College London

Ruth Misener is a Professor of Computational Optimisation in the Department of Computing at Imperial College London. Her research focuses on numerical optimisation algorithms and computational software frameworks,... More info

Faculty Member ALEX RIBEIRO-CASTRO

DR ALEX RIBEIRO-CASTRO

Data Scientist, Senior Teaching Fellow Operations Management Department, Imperial College London

Alex Ribeiro-Castro is a Data Scientist and Senior Teaching Fellow with the Operations Management Department at Imperial College Business School. He also teaches in the Global Business Analytics MSc.... More info

Faculty Member PROFESSOR CHRISTOPHER TUCCI

PROFESSOR CHRISTOPHER TUCCI

Professor, Digital Strategy and Innovation Imperial College Business School

Christopher Tucci is a Professor of Digital Strategy and Innovation at Imperial College Business School. Professor Tucci’s teaching focuses on design thinking, digital strategy and innovation management.... More info

Faculty Member PROFESSOR WOLFRAM WIESEMANN

PROFESSOR WOLFRAM WIESEMANN

Professor, Analytics & Operations; Academic Director, MSc Business Analytics; Associate Director, Centre for Process Systems Engineering; Fellow, Computational Optimisation Group; Fellow, Imperial Business Analytics Department of Computing, Imperial College Business School

Wolfram Wiesemann is a Professor and Group Leader of the Computational Optimisation Group in the Department of Computing at Imperial College London. His teaching focuses on linear, discrete and nonlinear optimisation; the theory, algorithms and applications of machine learning; and prescriptive analytics.

Professor Wiesemann holds a joint master’s degree in management and computing from Darmstadt University of Technology and a PhD in operations research from Imperial College London. In addition to his role at Imperial College London, he has been a visiting researcher at several other renowned institutions including Vienna University of Economics and Business, Princeton University, Columbia University and KU Leuven (Belgium).

Professor Wiesemann will serve as faculty lead during weeks covering machine learning concepts and methods.

Faculty Member PROFESSOR RUTH MISENER

PROFESSOR RUTH MISENER

Professor, Computational Optimisation Department of Computing, Imperial College London

Ruth Misener is a Professor of Computational Optimisation in the Department of Computing at Imperial College London. Her research focuses on numerical optimisation algorithms and computational software frameworks, with current applications including bioprocess optimisation under uncertainty and petrochemical process network design and operations.

Professor Misener earned a BS in chemical engineering from Massachusetts Institute of Technology and a PhD in chemical engineering from Princeton University. She is the recipient of numerous awards and fellowships and is currently an EPSRC Early Career Research Fellow at Imperial College London.

Professor Misener will serve as faculty lead during weeks covering topics related to artificial intelligence.

Faculty Member ALEX RIBEIRO-CASTRO

DR ALEX RIBEIRO-CASTRO

Data Scientist, Senior Teaching Fellow Operations Management Department, Imperial College London

Dr Alex Ribeiro-Castro is a Data Scientist and Senior Teaching Fellow with the Operations Management Department at Imperial College Business School. He also teaches in the Global Business Analytics MSc. In addition, he has more than 10 years of teaching experience in pure and applied mathematics at institutions across the globe. He also has more than 5 years of consultancy experience—including machine learning and optimisation problems—in industries such as fintech, health, energy and more recently in retail.

Alex Ribeiro-Castro holds an MA and a PhD in mathematics from the University of California (Santa Cruz) and previously held a professorship in mathematics from the Pontifical Catholic University (PUC-Rio).

Alex Ribeiro-Castro will serve as faculty lead during weeks covering mathematical concepts and the use of Python for ML/AI model development.

Faculty Member PROFESSOR CHRISTOPHER TUCCI

PROFESSOR CHRISTOPHER TUCCI

Professor, Digital Strategy and Innovation Imperial College Business School

Christopher Tucci is a Professor of Digital Strategy and Innovation at Imperial College Business School. Professor Tucci’s teaching focuses on design thinking, digital strategy and innovation management. His primary area of interest is in how companies transition to new business models, technologies and organizational forms. His research focuses on crowdsourcing, Internetworking and digital innovations. Prior to his role at Imperial College London, he was an industrial computer scientist who worked on developing Internet protocols and applying artificial intelligence tools.

Professor Tucci holds a BS in mathematical sciences, a BA in music and an MS in computer science from Stanford University; an MS in technology and policy from Massachusetts Institute of Technology; and a PhD in management from MIT’s Sloan School of Management.

Professor Tucci will serve as faculty lead during weeks covering strategic applications of machine learning methods.

Become an associate alumni

Take your partnership with Imperial College Business School to the next level by becoming an associate alumnus. Complete the programme to claim your associate alumni status and join our active community.

The Imperial learning experience

Human

At Imperial College Business School, we create people-centric learning experiences. From conception through to delivery, we are guided by the principle that learning is a creative, personal and above all, human process. Our high quality, crafted learning environments are highly interactive, community-orientated and actively tutored. Our programmes offer an engaging experience designed to facilitate natural learning behaviours.

Real

No compromises. Our online programmes offer the absolute equivalent of our campus-based programmes. They adopt the same rigorous academic standards, are delivered via our world-leading faculty and offer a comparable high-touch approach to the classroom experience.

Certificate

Certificate

Upon completion of the programme, participants will be awarded a verified digital certificate by Imperial College Business School Executive Education and the Imperial College London Department of Computing.

FAQs

  • How do I know if this programme is right for me?

    After reviewing the information on the programme landing page, we recommend you submit the short form above to gain access to the programme brochure, which includes more in-depth information. If you still have questions on whether this programme is a good fit for you, please email learner.success@emeritus.org, and a dedicated programme advisor will follow up with you very shortly.


    Are there any prerequisites for this programme?

    Some programmes do have prerequisites, particularly the more technical ones. This information will be noted on the programme landing page, as well as in the programme brochure. If you are uncertain about programme prerequisites and your capabilities, please email us at learner.success@emeritus.org for assistance.


    What are the requirements to earn a certificate?

    This is a graded programme. You will be required to complete a combination of individual assignments, quizzes, and a final project. Each component carries a certain number of points and a cumulative score of 75% is required to pass and obtain your professional certificate.


    Will I be guaranteed a job upon completion of the programme?

    The primary objective of this programme is to give you the skills you need to be prepared for a job in this field. While eligible participants will receive career coaching and support and may receive introductions to our hiring partners, job placement is not guaranteed.

  • How much time will I be expected to devote to this programme?

    Each programme includes an estimated learner effort per week. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page.


    How will I spend my time in this programme?

    You will divide your learning time between viewing recorded coding demos, video lectures, contributing to class discussions, completing assignments, projects, and knowledge checks, and attending optional weekly live sessions with industry experts and programme leaders.


    How is the programme administered? Can the programme be accessed anytime?

    The programme is accessed through the custom learning portal. This portal will give you access to all programme-related content such as video lectures, assignments, and discussions. Live office hours will be conducted using a webinar tool.

    The video lectures and assignments are accessible weekly throughout the programme. In the event you miss a live session, a recording will be made available.


    Do I need to attend live sessions every week?

    Faculty video lectures are recorded, allowing you to watch these on your own schedule. However, participation in optional weekly live sessions and discussion boards is highly encouraged. Live sessions will give you the opportunity to draw on the coding experience of our industry-experienced course leaders to answer your questions and help reach your learning goals. The discussion boards are also an integral part of the learning experience, giving you and your peers the opportunity to learn together, along with guidance from the moderators.


    Can I download the programme videos?

    You can download video transcripts, assignment templates, readings, etc. However, the video lectures are only available for streaming and require an internet connection.


    How do I interact with other programme participants?

    You can communicate with other participants through our learning platform. You will be able to form groups based on your interests and location. A direct messaging feature is also available through the platform.


    What is it like to learn online with the learning collaborator, Emeritus?

    More than 300,000 learners across 200 countries have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programmes said that their learning outcomes were met or exceeded.

    All the contents of the course would be made available to students at the commencement of the course. However, to ensure the programme delivers the desired learning outcomes the students may appoint Emeritus to manage the delivery of the programme in a cohort-based manner the cost of which is already included in the overall course fee of the course.

    A dedicated programme support team is available 24/5 (Monday to Friday) to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.

  • What are the requirements to earn the certificate?

    Each programme includes an estimated learner effort per week, so you can gauge what will be required before you enrol. This is referenced at the top of the programme landing page under the Duration section, as well as in the programme brochure, which you can obtain by submitting the short form at the top of this web page. All programmes are designed to fit into your working life.

    This programme is scored as a pass or no-pass; participants must complete the required activities to pass and obtain the certificate of completion. Some programmes include a final project submission or other assignments to obtain passing status. This information will be noted in the programme brochure. Please contact us at learner.success@emeritus.org if you need further clarification on any specific programme requirements.


    What type of certificate will I receive?

    Upon successful completion of the programme, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools, or potential employers. You can use it on your cover letter, resume, and/or display it on your LinkedIn profile.
    The digital certificate will be sent approximately two weeks after the programme, once grading is complete.


    Can I get the hard copy of the certificate?

    No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, and Twitter.


    Do I receive alumni status after completing this programme?

    No, there is no alumni status granted for this programme. In some cases, there are credits that count toward a higher level of certification. This information will be clearly noted in the programme brochure.


    How long will I have access to the learning materials?

    You will have access to the learning platform and all programme materials (videos excluded) for one full year following the programme end date. Access to the learning platform is restricted to registered participants per the terms of agreement.

  • What equipment is needed or the technical requirements for this programme?

    To successfully complete this programme online, you must have access to a device meeting the minimum requirements, found here. In addition, Microsoft Office or similar product and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts in all programmes. Technical programmes might have additional tech requirements. Please check the learning platform on the first day of class.


    Do I need to be online to access the programme content?

    Yes, the learning platform is accessed via the internet and video content is not available for download. You can download files of video transcripts, assignment templates, readings, etc. Video lectures must be streamed via the internet and webinars and small group sessions will require an internet connection.

  • What is the programme fee for the programme and what forms of payment do you accept?


    • The programme fee is shown at the top of this page and payment is accepted only in US dollars.
    • Flexible payment options, group enrolment benefits and referral bonus are available.
    • Tuition assistance may be available for participants who qualify. Please contact your programme advisor to discuss.

    What if I don’t have a credit card – is there another mode of payment accepted?

    Yes, you can do the bank remittance in USD via wire transfer. Please contact your programme advisor for more details.


    Is there an option to make flexible payments for this programme?

    Yes. Flexible payment options are available for this programme. We partner with loan partners to offer you flexible and transparent loan options. More information about loan financing is available here. Installment payments are also available—you can find the options here.


    Does the programme fee include taxes? Are there any additional fees?

    Yes, the programme fee is inclusive of any taxes with the exception of GST for Singapore residents.

  • What is your refund policy?

    After a participant has withdrawn, they will no longer be able to attend live sessions or 1:1 sessions with course leaders, mentors, or career coaches; submit work for review; or access their programme dashboard or curriculum.


    Time of Refund Request

    • Within 21 days after course commencement
    • 22 to 45 days after course commencement
    • More than 45 days after course commencement

    Amount Refunded

    • Full refund of course fee (assuming no prior course deferral)
    • 50% of course fee (assuming no prior course deferral)
    • No refund of course fee

    How do I request a refund?

    Participants who would like to cancel their enrolment should email ProgramSupport@Emeritus.org or visit the “Support” tab in the learning platform to obtain a copy of the Withdrawal Request Form. This form must be submitted by midnight UTC of the last day of the trial period to be eligible for a full refund. No cancellations will be processed unless this form is received. Refunds will be issued within 30 days after the effective date of withdrawal or dismissal.



    Can I defer to a future cohort?

    Participants have the option to request a deferral to a future cohort within the first 30 days from their programme start date. Cohort changes may be made only once per enrolment and are subject to the availability of cohorts and scheduled at the discretion of Emeritus. Participants requesting a deferral must be in good academic standing. Participants who would like to defer their enrolment should email ProgramSupport@Emeritus.org or visit the “Support” tab in the learning platform to obtain a copy of the Deferral Request Form.

Financing Options Available

UK Residents

  • Knoma – Interest-free financing options available.

Rest of the World

You can opt for any one of the financing options to cover up to the full cost of the programme tuition. If you are considering financing your programme through one of our partners, the enrolment process can only be completed with the assistance of your programme advisor.

Please note that loan applications should be submitted no later than four business days prior to the enrolment deadline due to processing time.

Didn't find what you were looking for? Write to us at learner.success@emeritus.org or Schedule a call with one of our Academic Advisors or call us at +44 151 453 0734 (UK) / +1 315 897 5158(US) / +65 3129 5150 (SG)

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Flexible payment options available. Learn more.