Data Science for the Internet of Things (IoT)
Application for this course will open in week 23-27 July 2018.
This unique course aims to create a new breed of engineer - those with a background in AI and IoT coupled with the knowledge of machine learning, cloud and robotics.
The Data Science for IoT course is designed as a general Artificial Intelligence (AI) course with an emphasis on the Internet of Things (IoT. The course aims to equip you with the skills to solve problems, providing you with a toolkit (code) and templates. It's for developers who want to be data scientists with a focus on AI and IoT.
The course explores problem solving for IoT analytics via the following themes
- Concepts: principles/foundations
- Product development for IoT (with an emphasis on analytics)
- Data science, Data Engineering and DevOps
- Artificial intelligence
- TensorFlow and Keras
- Deploying and refreshing AI models at scale in a pipeline
- IoT Verticals and Platforms
- Programming in Python foundations
- Statistics foundations
- Time series
- Deep learning
- Real time including LSTMs and streaming
- NoSQL databases for IoT
- Industrial IoT, Robotics and drones
- Edge analytics
- Complex event processing
- Blockchain and IoT
- Innovation in IoT
- A problem solving methodology – putting it all together
About the course and its aims:
- The course analyses problem solving for IoT analytics.
- The unique considerations for IoT data (e.g. time series data) are investigated.
- The course covers programming so participants will need to be familiar with some programming languages - but we do not expect familiarity in a specific language. The primary programming language of the course is Python (specifically TensorFlow and Keras).
- Development is based on coding sprints
- We use Spark for big data.
- The course needs an understanding of maths. We cover maths and statistics foundations as needed.
- Where possible, we use IoT datasets. We cover handling large-scale IoT datasets.
- We focus on skills based/commercial products. This is not an academic course.
- The course also includes an industry programme. The industry programme will be based on use cases incorporating IoT analytics methodology.
- We aim to equip you with skills such as TensorFlow, Keras and AI in general, which can be used outside of IoT applications.
The course takes a problem solving approach and uses specific case studies from industry. Participants are expected to have a mind-set of exploration and to study and learn beyond the class material itself (depending on their existing familiarity with the subject matter).
The course is based on a perspective of both AI and machine learning. AI is driven by deep learning algorithms. Deep learning is a wider case of machine learning based on automatic feature detection. IoT primarily involves data in time series formats (using AI algorithms like recurrent neural networks and long short-term memory (LSTMs)) and image-based data (using convolutional neural networks).
A limited number of participants ensures that all those taking this course gain the maximum possible value.
Previous students have used the course to start a new career, for career progression or to have their skills upgraded by their employer.
All participants finishing the Data Science for IoT course will receive a University of Oxford certificate showing that they have completed the course (see sample and details of requirements further down this page).
You will be fully supported by the tutor who will be available during the week to answer questions. The tutor list below may be subject to change.
The tutor will also offer a number of one-to-one 'surgery sessions' during the course.
All course participants will receive e-book versions of the relevant textbooks as part of the course fee (titles below subject to change):
The time commitment for this course is up to 4 - 5 hours face-to-face in Oxford on Saturdays (usually starting at 10:30) and 1 - 2 hours online each week on Tuesdays (usually starting at 19:00). We recommend you allow an additional 10 - 12 hours study time per week. There is a minimum attendance requirement of 75%.
Week Zero: Onboarding platform, introductions etc.
Week One: Foundations of Data Science for IoT
- Explore the application of predictive learning algorithms to IoT datasets in detail.
- Discuss the modalities where we could apply IoT analytics (Streaming, Edge etc.).
- Understand data science for IoT from a problem solving perspective.
- Understand IoT platforms and their strengths and drawbacks
- Explore where analytics fits into the overall Product development for an IoT based application
- IoT verticals
Week Two: Programming Foundations (part one) - The Python Ecosystem
In this session, we explore Python from a data science perspective using the book Python Machine Learning by Sebastian Raschka
Week Three: Programming Foundations (part two) - Understanding Tensorflow and Keras
Building on Week Two, we explore TensorFlow and Keras in detail using the books
Week Four: End to End IoT Deployment
This session covers an end to end IoT deployment covering sensors, analytics and visualization for devices using Microsoft Azure.
Week Five: Deploying Machine Learning and AI Models in Production
In this session, we explore the deployment of machine learning and AI models in production using two models: TensorFlow, Keras with Kubernetes and h2o.ai
Week Six: Time Series Analysis
Most IoT data is in time series format. In this session, we explore time series analysis including recurrent neural networks, LSTMs and multivariate time series.
Week Seven: Understanding and Managing Data and Models
Understanding and pre-processing data is a key part of data science. For IoT, we need two types of data, namely time series and image-based data. This session is based on understanding the transformations and models needed for IoT data with an emphasis on time series data and image based data.
Week Eight: Big Data and IoT - Spark Streaming and NoSQL Databases
In this session, we explore the impact of big data on data science for IoT. This includes perspectives like streaming (Spark) and NoSQL databases.
Book used for this section: Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis by Mohammed Guller.
Week Nine: Robotics, Drones etc. with Nvidia using AI and Deep Learning
With cameras as sensors, AI and deep learning technologies play a key role in a number of emerging areas. In this session, we use Nvidia platforms to understand the application of deep learning algorithms to a range of emerging technologies including drones, robotics etc. We primarily address video and image recognition based problems.
Week Ten: Industrial IoT
This session discusses various aspects of Industrial IoT including deployment of complex event processing, Industrial Internet of Things (IIoT) Platforms, platforms such as Predix, physics based modelling etc.
Week Eleven: Innovation / Latest Developments for Data Science for IoT
This session covers a range of innovations and latest developments with respect to data science for IoT including GPU databases, Voice interfaces for sensors, Blockchain, AI at chipset level, Tensorflow for embedded devices etc.
Week Twelve: Industry Use Cases
Industry use cases and meeting with invited experts - spanning all the sections above, a discussion and collaboration with invited industry experts from Ocado, Barclays, Google, Microsoft, GSMA, Logtrust and others.
Note that tutors and content may be subject to revision during the course and the course development process.
Participants who satisfy the course requirements will receive a Certificate of Attendance. The sample shown is an illustration only and the wording will reflect the course and dates attended.
To receive a certificate at the end of the course you will need to:
- Achieve a minimum attendance at the Oxford classroom sessions of 75%.
- Answer all the weekly learning quizzes (these are short quizzes designed to ensure you have understood the material in each unit).
- Complete the short exercises that you are given.
Standard course fee: £4995.00
Fees include all course materials and tuition. The price does not include accommodation.
All courses are VAT exempt.
Payment can be made in instalments, if your first instalment is dated 1 September 2018 or sooner:
Instalment 1: £2,500.00, due before 1 September 2018
Instalment 2: £2,500.00
Total fee if paid in two instalments: £5,100.00
Total fee if paid in one instalment: £4,995.00
Lead Tutor and Course Director
Ajit's work spans research, entrepreneurship and academia relating to artificial intelligence (AI), the internet of things (IoT), predictive analytics and mobility.
Ajit currently works as a Data Scientist currently in the Bioinformatics space. The technical emphasis of his work includes Time series, Edge Computing and Deep Learning for sequences.
Outside of Oxford University, he has been involved in teaching /academic programs at London School of Economics, Harvard Kennedy School, University of Madrid.
Ajit publishes extensively on KDnuggets and Data Science Central and his book, Data Science for Internet of Things, is included as a course book at Stanford University.
He was recently included in top 16 influencers (Data Science Central), Top 100 blogs (KDnuggets), Top 50 (IoT central), No 19 among top 50 twitter IoT influencers (IoT Institute).
Ajit has been involved with various mobile, telecoms and IoT projects since 1999 including strategic analysis, development, research, consultancy and project management.
In 2009, he was nominated to the World Economic Forum’s ‘Future of the Internet’ council. In 2016 he was involved in a WEF council for systemic risk (IoT, drones etc.). He has worked with cities like Amsterdam and Liverpool on Smart City projects in mayoral level advisory roles. Ajit has been involved in IoT-based roles for the webinos project (Fp7 project). In May 2005 he founded the OpenGardens blog, which is widely respected in the industry. He has spoken at Mobile World Congress (4 times), CTIA, CEBIT, Web 2.0 expo, The European Parliament, Stanford University, MIT Sloan, Fraunhofer FOKUS; University of St Gallen. He has also been involved in transatlantic technology policy discussions.
Ajit is also passionate about teaching data science to young people through space exploration working with Ardusat.
Director of Studies
Dr Cezar Ionescu is Associate Professor of Data Science with the Oxford University Department for Continuing Education. His main interests include functional programming, correctness of scientific computing and machine learning algorithms, and the role of computing science in education.
Guest Speaker and Course Developer
Director & Technical Consultant, Catalyst Computing Services
Peter Marriott is an industry practitioner with over 25 years database and software development experience on production systems. The main focus of his career has been working with data, working on business systems to make the data useful and available in a performant cost-effective way.
13 years ago he founded the consultancy Catalyst Computing Services, working with a wide range of clients in a variety of market sectors. Their first IoT project was in 2006. Peter has been involved working throughout the whole project development cycle of IoT: from prototyping proof of concepts; designing systems architecture; development; deployment and training of support staff.
Peter runs training courses in cloud computing and database technologies for clients, gives career talks for undergraduates and speaks at various IT user groups.
Guest Speaker and Course Developer
Director, Insight and Customer Strategy, Oracle
JJ Bernard has an MSc in Engineering from the Ecole Centrale de Marseille and an MBA from the University of Cambridge. He is also a certified Lean Six Sigma Black Belt.
He currently works at Oracle as a strategy consultant, advising client on their technology investment with regards to their business strategy.
Previously, he has worked as a project manager for Orphoz, a subsidiary of McKinsey & Company, focusing on defining and executing transformation projects. He has worked in diverse environments such as manufacturing, FMCG, public sector, steelmaking, mining, healthcare and automative.
He has also worked for Accenture, both on business and IT transformation projects, for the financial services industry and the public sector.
Chief Technology Officer, Ocado
Paul Clarke is Chief Technology Officer at Ocado, the world's largest online-only grocery retailer.
Paul joined Ocado in 2006. After establishing new teams for Simulation and Mobile development, Paul then co-wrote the first of Ocado’s award winning mobile apps. In his current role, Paul heads up Ocado Technology, whose 950+ software engineers and other IT specialists are responsible for building all the software and IT infrastructure that powers Ocado, and now Morrisons’ online grocery business too.
Paul read Physics at St John's College, Oxford before then entering the computer industry. He has worked in software engineering, consultancy, interim management and a number of software start-ups.
In what little spare time he has alongside his work and family, Paul loves to invent and build stuff, design PCBs, write software and generally tinker.
Co-founder of Blesh
Devrim Sonmez is regarded as a high performing executive and entrepreneur with over 19 years of experience at intersection of digital and technology with various industries, over 10 years of Executive Board experience and taking a strategic role in securing M&A deals worth over $170 million in technology.
In 2013, he became the CEO and co-founder of Blesh Inc. which is an award winning and innovative start up in IoT space developing IoT platforms and solutions through its own research and development. It is among the top Global 5 Mobile Proximity Solution providers and is considered the first global beacon solution provider of Google Physical Web technology since 2014 with exports more than 30 countries.
He is still the Cofounder and the Board Member of Blesh. Alongside these positions, Mr. Sonmez has sat on the board of several more companies and associations including IOT.ATL a program of US Metro Atlanta Chamber that intends to boost the region’s tech sector in the burgeoning industry of Internet of Things products and software, the highly prestigious TUBISAD (Turkish Informatics Industrialists Association) and English Ninjas (An innovative mobile startup for English practicing), where his influence plays an integral part in grow and success.
Devrim holds a Mathematics Bachelor of Science from the leading Turkish university in Ankara, the Middle Eastern Technical University graduating in 1998 and a Master of Business Administration from the Koc University in Istanbul, graduating in 2005.
Senior Software Engineer, Microsoft
Since joining Microsoft in 1994, Paul Foster has worked across a wide range of sectors and customers, providing a mix of technical and strategic guidance around the creative use of technology in relation to their business needs.
Paul is currently a principal software engineer at Microsoft. As an established public speaker across Europe and having spent a considerable amount of time working on the cutting edge of technology providing leadership and inspiration on topics like Smart Devices, Cloud Computing, Education and App Development.
Paul is currently focusing on the building of next generation sensor webs which automate the gathering of data from disparate sources, and how to enable the creative analysis of this data to start a new era of perception.
For a short time Paul was a member of a high-wire flying trapeze circus troupe, is a keen roboticist and an international marathon runner.
Vision Design Engineer, Programmable Solutions Group, Intel
Jahanzeb Ahmad joined Intel Programmable Solutions Group (PSG) formally known as Altera in 2013 and is currently working as vision design engineer. His current responsibilities include architecting and developing machine learning architectures and solutions for autonomous vehicles and surveillance.
Previously, Jahanzeb spent 2 years working as a consultant/contractor developing FPGA based video compression/decompression, conversion and capturing systems.
Prior to joining PSG, Jahanzeb did his PhD in computer vision and medical engineering from University of The West of England, Bristol, UK. Jahanzeb also holds a BEng in Computer Engineering and a Masters in Communications Engineering.
Imperial College London; Organiser, Google Developer Group (GDG) Cloud London
Surya is pursuing an MEng in EEE from Imperial College London, specialising in Machine Learning and Embedded Systems. He started his journey in data science at a biotechnology startup, where he worked on characterising hand tremors of Parkinson’s patients to tune the product’s control algorithm (which stabilises the tremors). He spent last summer working on implementing neural network based applications on Android.
He also leads workshops and events at the Cloud Google Developer Group in London, with a specific focus on Machine Learning frameworks, such as Tensorflow.
Surya can usually be found tinkering with embedded hardware and software in the Robotics Lab at Imperial College.
Founder, Seven Symbols
Barend Botha is a UK-based consultant working predominantly in the field of data visualisation.
He is particularly interested in the growing future potential and roles that data analytics and visualisation will play across IoT verticals in in combination with Artificial Intelligence and the resulting products and insights for business and consumers alike.
He draws upon past experience in research, design, development, management and marketing across various domains and disciplines.
Senior Software Engineer, Avast Software
Bojan Komazec has been working in the IT industry for over 13 years. He currently holds the position of Senior Software Engineer in Avast Software where he has been developing various security and privacy products.
Bojan's interests span from code craftsmanship and cyber security to Artificial Intelligence and Internet of Things. He is an active blogger and speaker at several IT Meetup groups where he enjoys sharing experience and knowledge.
Bojan studied Electrical Engineering and Telecommunications and in 2004 received master's degree from University of Novi Sad, Serbia.
Please complete the self-assessment pre-course questionnaire. The information requested is to allow us to get a fuller picture of your skills and background.
We do not expect you to have knowledge or experience in all of the areas on this questionnaire!
Upon approval from the academic review panel, we'll send you an application form by email.
Complete the application form, and send it to us by post or email. Please do not send credit card details by email.
We'll invoice you for the course fees.
Submit payment. Your place on the course will be confirmed only after we have received payment.
Terms and conditions
Terms and conditions for applicants and students on this course
Sources of funding
Information on financial support
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