Applied Machine Learning

Learn to build and scale industry-standard end-to-end deep learning systems, from data engineering to model design

About the programme

Our apprenticeship is led by a machine learning engineer from Meta and will include talks and workshops with data scientists from Deepmind, Meta Research and Google. This is an advanced programme aimed at experienced software engineers and academics.

Our next cohort starts in July 2023 in London.

The programme is split into two parts. The first part is a full-time in-person intensive. The second part is a year-long training where you'll meet one afternoon weekly for workshops, projects and paper reading. This programme is a level 7 AI apprenticeship, equivalent to a master's degree in AI. Our programme is funded through the apprenticeship levy and won't cost you anything as long as you are eligible for our funding.

If you are employed and want to upgrade your skills and build ml-driven products at your current company, we can help you make the case to your employer. You will learn valuable skills that will be very useful in your job. It won't cost your employer anything, but they should continue paying you while you participate in the programme. If you're not working full-time or want to change jobs, we can help you find a role with one of our partners.

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What you'll learn

  1. Data Engineering

    Relational, distributed and time series databases, data processing frameworks and pipelines, cloud computing and data visualisation.

    ELT/ETL, SQL & NoSQL, PostgreSQL, Hadoop, Apache Airflow, Apache Kafka, Kafka Stream, AWS.

  2. Machine Learning

    Introductory modelling, classification techniques and supervised models, followed by powerful ensemble methods, text mining and information retrieval techniques.

    Linear & Logistic Regression, K-Nearest Neighbours, Decision Trees, Random Forests, Gradient Boosting, TF-IDF, Empath, SVM, PCA, Numpy, Scipy, Scikit-learn, Matplotlib, Pandas.

  3. Deep Learning

    Multiple model architectures applied to categories such as natural language processing, classification tasks and recommendation systems.

    PyTorch, Back-propagation, Parameter Regularisation, Dataset Augmentation, Semi-Supervised Learning, Multitask Learning, Adaptive Learning Rate Optimisation, Performance Metrics, Hyperparameter Tuning, Autoencoders, MLP, CNN, RNN, LSTM and Transformers

  4. Mathematics

    There is plenty of maths at the heart of deep learning. Prior knowledge is helpful but not a requirement. We will cover aspects of Linear Algebra, Calculus, Probability & Statistics, and Numerical optimisation.

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In simple terms, you are eligible if you have lived in the UK or Europe continuously for the last 3 years, or you have refugee or asylum status.

There are a number of other ways you might be eligible for an apprenticeship. View the full eligibility criteria. If you have any questions about your eligibility, please email us at

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