Machine Learning Training in London – ML Algorithms, Deep Learning & MLOps

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SoftPro9 runs Machine Learning Engineering training as live online batches in UK time, for learners in the City, Canary Wharf, Shoreditch and across London.

  • Covers: Python, NumPy, pandas, scikit-learn, XGBoost, LightGBM, CatBoost, Optuna and more
  • Mode: Live online in UK time
  • New batches: Every Monday and Thursday; UK time slots 8 AM / 3:30 PM / 6 PM
  • Duration: 20–24 weeks at 10–12 hours a week, including a production capstone
  • Fee: The current fee is listed on the Machine Learning Engineering course page: /course/machine-learning-ml-training-course. Any cloud ML certification exam is optional and paid directly to the exam provider.
  • Batch size: Up to 15 learners
  • Practice: GPU-enabled cloud notebooks, MLflow tracking server and your own GitHub repositories

Last updated: 28 October 2026

Machine Learning course in London: basic to advanced

London's banks, insurers and fintechs use ML for risk, pricing and fraud, under strong regulatory expectations on explainability. The course is split into three levels. You can join at the level that matches your experience after a short assessment at counselling.

Basic

Maths and ML foundations

  • Python, NumPy and pandas for ML work
  • Linear algebra: vectors, matrices, dot products, eigenvectors
  • Calculus for ML: derivatives, gradients and gradient descent
  • Probability, distributions and Bayes' theorem
  • The ML workflow: train/validation/test splits, bias and variance
  • Linear and logistic regression built from scratch, then with scikit-learn
  • Evaluation metrics: RMSE, precision, recall, F1, ROC-AUC

London practice: UK GDPR and consent practice in web and data exercises.

Intermediate

Algorithms and model building

  • Decision trees, random forests and ensembles
  • Gradient boosting with XGBoost, LightGBM and CatBoost
  • Support vector machines and k-nearest neighbours
  • Clustering (k-means, DBSCAN, hierarchical) and PCA
  • Feature engineering, encoding, scaling and pipelines
  • Hyperparameter tuning with grid search and Optuna
  • Imbalanced data, cross-validation strategies and data leakage
  • Recommender systems: collaborative filtering and matrix factorisation

London practice: Accessibility to WCAG 2.2 AA, as UK public-sector sites require.

Advanced

Deep learning and MLOps

  • Neural networks and backpropagation with PyTorch
  • CNNs for images and sequence models for text and time series
  • Transfer learning and fine-tuning pretrained models
  • Time-series forecasting with ML and deep learning
  • Model explainability (SHAP) and fairness checks
  • MLOps: experiment tracking with MLflow, data versioning with DVC
  • Serving models with FastAPI and Docker; batch versus real-time inference
  • Monitoring drift and retraining; intro to Kubernetes, AWS SageMaker and Google Vertex AI

London practice: UK date formats, postcodes and the April–April tax year.

Who joins from London

  • Finance and insurance staff in the City and Canary Wharf
  • Career changers building a portfolio for tech roles
  • Developers adding data or modern front-end skills

Roles it typically leads to in London

  • Machine-learning engineer
  • ML / MLOps engineer
  • Data scientist (modelling-focused)
  • Applied ML engineer
  • Computer-vision or recommender-systems engineer

Freshers usually start in junior or support versions of these roles.

Machine Learning Engineering – full course details and fee →

Tools you will use

Every tool below is used hands-on in class or in a project, not just mentioned on a slide.

  • Python
  • NumPy
  • pandas
  • scikit-learn
  • XGBoost
  • LightGBM
  • CatBoost
  • Optuna
  • PyTorch
  • TensorFlow / Keras
  • SHAP
  • MLflow
  • DVC
  • FastAPI
  • Docker
  • Kubernetes (intro)
  • AWS SageMaker
  • Google Vertex AI
  • Git & GitHub
  • Jupyter

Projects you will build

  1. A credit-risk model with tuned gradient boosting, SHAP explanations and a fairness check

  2. A product recommender system evaluated against a popularity baseline

  3. An image classifier fine-tuned from a pretrained CNN

  4. A capstone model served through a FastAPI endpoint in Docker, with MLflow tracking and drift monitoring

  5. London project: A motor-insurance pricing model with explainability for regulators, using data and conventions from London.

Upcoming London Machine Learning batches

New batches start every Monday and Thursday, with no more than 15 learners in each. Weekday class slots in UK time: 8 AM / 3:30 PM / 6 PM. Weekend slots: 10 AM / 5 PM. Times shown are for winter; they move one hour when clocks change.

The early-morning and evening UK-time slots fit around a standard working day.

Start dateCourseModeBatch size
Thu, 29 Oct 2026Machine Learning (all levels)Live onlineUp to 15
Mon, 2 Nov 2026Machine Learning (all levels)Live onlineUp to 15
Thu, 5 Nov 2026Machine Learning (all levels)Live onlineUp to 15
Mon, 9 Nov 2026Machine Learning (all levels)Live onlineUp to 15

Message us with the start date and slot you want, and we will confirm your seat.

Reserve on WhatsApp

Machine learning in brief

Machine learning is the part of AI where software learns patterns from data instead of following hand-written rules. A trained model can score a loan application, recommend a product, flag a faulty part or forecast demand, and it improves as it sees more data.

This course goes deeper into the engineering side than a general data science course: how algorithms work under the hood, how to tune and validate them properly, and how to ship, monitor and retrain models in production with MLOps tools such as MLflow, DVC, Docker and cloud ML platforms.

Why machine learning skills matter in London

London is Europe's largest financial centre and one of its biggest technology hubs: banks and insurers in the City and Canary Wharf, fintech and startups around Shoreditch and King's Cross, and public-sector digital teams. Employers value clean, tested code, accessibility and a clear explanation of your work.

Who hires in London

  • Banking, insurance and fintech

    The City and Canary Wharf host global banks, insurers and many fintechs.

  • Technology and startups

    Shoreditch, King's Cross and the wider tech scene, including AI companies.

  • Public sector digital

    Government digital services and the NHS, which follow strict accessibility and design standards.

  • Retail, media and consulting

    Retailers, broadcasters and consultancies with large data and web teams.

UK context you will work with

Generic courses use generic datasets, and interviewers notice. Our exercises include:

  • GBP pricing and 20% VAT in invoice data
  • UK GDPR and consent practice in web and data exercises
  • Accessibility to WCAG 2.2 AA, as UK public-sector sites require
  • UK date formats, postcodes and the April–April tax year
  • Clock changes (GMT/BST) in time-series data

How to choose the right Machine Learning track

Your backgroundStart withWhy
Software developerFull courseYour engineering habits are what MLOps needs
Data analyst with PythonAlgorithms, then MLOpsMove from reporting to models that run in production
Engineering / maths graduateFull courseThe maths module will be a quick refresher
New to programmingPython firstML assumes you are comfortable writing Python
Mainly interested in ChatGPT-style appsArtificial Intelligence courseThat course focuses on LLMs, RAG and agents

Common pairings: Machine Learning + Python (if you are new to coding), Machine Learning + Artificial Intelligence (for generative AI roles), and Machine Learning + DevOps (for MLOps-heavy roles). Learn one course well before adding a second.

From course to first role: a realistic path

  1. Master the maths and ml foundations before moving on.

  2. Build and publish your projects, including the London capstone.

  3. Apply for entry roles such as machine-learning engineer or ml / mlops engineer with employers like the banking, insurance and fintech above.

Honest note: freshers usually start in junior or trainee roles, and salaries in London vary too widely for a headline figure. Ask us which openings we are seeing.

Machine Learning certification: what we cover and what we issue

There is no single official machine-learning certification. Cloud vendors run optional exams such as AWS Certified Machine Learning Engineer – Associate, Google Cloud Professional Machine Learning Engineer and Microsoft Azure Data Scientist Associate (DP-100); they are paid directly to the vendor and are not part of our fee. SoftPro9 issues a course completion certificate. Employers mainly judge ML candidates on deployed projects and how well they explain their modelling choices.

What to check before choosing a Machine Learning institute in London

  • A 2026 syllabus: look for Docker, Kubernetes (intro), AWS SageMaker, Google Vertex AI, not only the basics.

  • Projects on your own accounts, a trainer you can meet first, and a published fee with nothing hidden.

  • No "global certification" or "100% placement" claims: vendors run their own exams, and nobody can promise a job.

How our Machine Learning classes work

  • Taught from Bangalore

    Classes are taught live by the same trainers who teach our Bangalore classroom, streamed to London in UK time.

  • Live, with recordings and reviews

    Live sessions in UK time, recordings for revision, and project reviews from the trainer. GPU-enabled cloud notebooks, MLflow tracking server and your own GitHub repositories.

  • Interview preparation

    Mock interviews, resume reviews and referrals to London and remote openings we hear about. We do not guarantee a job.

Machine Learning training across London: which option suits your area

AreaWhereMost learners choose
The City, Canary WharfCentral / eastLive online, evening slots
Shoreditch, King's Cross, CamdenCentral / northLive online
Croydon, Wimbledon, RichmondSouth / westLive online, weekend batches
Stratford, Ilford, Harrow, WembleyOuter LondonLive online

London batches are live online in UK time (times shift with GMT/BST); there is no classroom in London.

Where your classes come from

London batches are live online. They are run from our Bangalore centre, which you are welcome to visit if you are ever in the city.

SoftPro9 IT Services – Bangalore
22/1, Opp Infosys, BHBCS Layout, BTM Layout 2nd Stage, BTM Layout, Bengaluru, Karnataka – 560076

Phone: +91 95354 51414

Getting here

We are in BTM Layout 2nd Stage, opposite the Infosys office. The nearest metro is Jayadeva Hospital station, about a 10-minute walk away, and BMTC buses on the Outer Ring Road and Bannerghatta Road stop nearby.

Opening hours

Monday–Friday 9:30 AM–7:30 PM · Saturday 9:30 AM–3:30 PM · Sunday closed

Get directions

Machine Learning training in London: frequently asked questions

How much does Machine Learning training cost in London?

The current training fee is listed on the Machine Learning Engineering course page: /course/machine-learning-ml-training-course. It covers live classes, the practice environment, projects and interview preparation. Any cloud ML certification exam is optional, not included, and paid directly to the exam provider.

How is this different from the Data Science course?

Data Science covers the whole workflow from analysis to modelling and communication. Machine Learning goes deeper into algorithms, tuning and putting models into production with MLOps.

How much maths do I need?

School-level maths is enough to start. We teach the linear algebra, calculus and probability that ML relies on, with code and intuition rather than proofs.

Do you cover MLOps?

Yes. You track experiments with MLflow, version data with DVC, serve models with FastAPI and Docker, and monitor drift.

Do I need a GPU?

No. Deep-learning exercises run in GPU-enabled cloud notebooks we provide.

Is there a classroom in London?

No. London learners join live online batches in UK time, with recordings and a 15-learner cap.

Is the course regulated or eligible for UK student finance?

No. It is a private professional course and not eligible for UK student finance.

When does the next batch start?

New Machine Learning batches start every Monday and Thursday. See the batch table on this page for the next dates and UK time class slots.

Do you guarantee placement?

No. We provide interview preparation, resume help and referrals to openings we hear about in London, but no institute can honestly guarantee a job.

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Talk to us about your Machine Learning course

Tell us your degree, your current job (if any) and where in London you are. We will suggest a track and a batch that fits.

Chat on WhatsAppCall +91 95354 51414