Applied Data Science Online Learning

Become a Data Scientist in 9 months, taught online with immediate support

01 FEBRUARY 2019 APPLY NOW

ONLINE TRAINING

WANT TO LEARN IN PERSON ?
FIND OUT ABOUT OUR LONDON BOOTCAMP

What is ADS Online ?

The Online Bootcamp combines our proven, industry-driven curriculum with personalised, self-paced learning. We equip you with the skills and practical experience needed to contribute to data science teams and produce production ready code.

During the course you will:

Assess 10 video training modules with live-coding, learning activities and projects
Enjoy peer-learning and interacting with academic and industry expects
Get instant, personalised project feedback using K.A.T.E.®
Build a professional portfolio completing projects on real-world data
Gain experience working on an end-to-end industry project
Connect with a global community of students, alumni and project partners
Earn industry recognised certification
Online

What you will learn

Over nine months, you’ll learn how to extract, clean, analyse and transform data into actionable insights with the most industry-relevant Applied Data Science Bootcamp, built with industry Project Partners. You’ll advance your career by building an enviable portfolio to evidence the tools, techniques and libraries you’ve applied, enabling you to secure employment in a field projected to soar in demand by 28% by 2020.

  • This preparatory module covers all the essential programming skills, mathematical and statistical understanding,

    and knowledge of computer science principles you need to work in Data Science.
  • This module is designed to equip you with the skills to transform a real-world “dirty” dataset into a set of observations that can be analysed and then communicated to non-technical domain experts, executives and stakeholders.

  • This module is designed to ensure you understand the fundamental methods and industry best practices when developing machine learning models by applying a robust methodology. Emphasis will be placed on the evaluation and optimisation of models for different task demands and contexts.

  • This module is designed to help you gain the skills to develop and communicate models with simple, subtle or complex relationships between variables. You will also receive hands-on training in time series analysis.

  • This module is designed to ensure you understand the fundamental principles behind ensemble models and are able to evaluate them rigorously. You will also gain an in-depth understanding of the theory behind Support Vector Machines (SVMs), and develop the skills you need to build and evaluate SVM models.

  • The first part of this module is designed to help you develop the knowledge and skills to run experiments using resources available on state-of-the-art cloud environments. The second part of this module will teach you how to work with modern databases to store and query structured and unstructured data.

  • This module is designed to help you develop the knowledge and skills to design or make decisions on the computational architecture or ecosystem used for processing, storing retrieving, and analysing data

  • This module is designed to ensure you have a strong understanding of how neural networks are constructed and how they operate. You will learn about different neural network architectures, ranging from simple single-layer architectures to complex deep learning architectures with many layers and more elaborate connection structures.

  • This module is designed to provide you with hands-on training in text processing, semantic analysis and sophisticated Machine Learning approaches.

  • This final training module is split into three core sections, building Recommender Systems, followed by model evaluation and interpretability, concluding with interview preparation and project allocations. Your final capstone project will be announced at the end of the session.

  • After completing the ten modules, you will work independently on an end-to-end project from our supporters and industry partners. We will match you with an exciting data science problem and help you make professional contacts in the field.

    Final projects come from a range of sectors. Some examples include:

    • Deep Learning: automatic image classification
    • Time Series: visualising a portfolio of stocks
    • NLP: topic modeling for crowdfunding campaigns
    • Working on your own work related project is also supported

PREREQUISITES

  • Intermediate Python programming and use of the command line
  • Basic probability and linear algebra
  • Familiarity with Git

STUDENT JOURNEY

You’ll complete the most comprehensive data science curriculum, designed for professionals looking to upskill while keeping their job.

Schedule a call with our Head of Admissions to learn about the course!

How we are Different

Benefit from a self-paced, blended learning approach including live-coded online videos, interactive exercises and project-based assignments.

Gain hands-on experience working on a range of projects and put together a Data Science portfolio to demonstrate your skills.

Get immediate, personalised feedback on your project submissions using K.A.T.E.®, your learning and assessment platform

We simulate a real work environment using version control tools and coding best practices and Machine Learning methodologies to prepare you for industry

Enjoy a collaborative, peer learning environment where you will connect with individuals from all industries and gain insight into different problem-solving approaches

Online
Online

Pricing

All prices include VAT.

Get in touch

CONTACT OUR ADMISSIONS TEAM

We will email you within the next 24 hours to arrange a quick call to help with any questions about the programme and recommend pre-course materials.

We look forward to speaking with you.

Olivia Hughes

Olivia Hughes

Head of Admissions