Mind Project

Data Science Training and Big Data Predictive Analytics

Big Data Analytics with R – 2-Day Tutor-Led Course – July 2022

Big Data Analytics with R

Big Data Analytics with R – 2-Day Tutor-Led Course – July 2022

£330.00 – £450.00

Course dates: 4th-5th of July 2022, 10:00-17:00 London (UK) time

Course type: 2-day tutor-led online course with certification

Recommended time commitment: 24 hours including self-study
Deadline for registrations: Friday, 1st of July 2022 @ 17:00 London (UK) time

Book your place on this course by 6th of June 2022 to be eligible for the Early Bird discount.

SKU: N/A Category: Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Description

This hands-on two-day tutor-led course covers one of the most exciting and current topics within the R community. Although traditionally R has not been used for Big Data analytics due to various limitations, recent R packages have provided much-needed connectivity for out-of-memory processing with popular Big Data tools such as Hadoop, Spark, SQL and NoSQL databases etc.

During this training course, you will learn essential know-how on applications of R language to manage, manipulate and analyse Big Data, datasets stored in distributed file systems or large databases, and to write fast, parallel R code to allow scalability of algorithms and data processing. The course also serves as a good introduction to Cloud Computing (Amazon Web Services and Microsoft Azure) and MLOps as you will be presented with the best practices of the Big Data system design which utilises the growing ecosystem of tools that support Big Data analytics including software and engines applicable to large scale statistical and machine learning (h2o, Spark, keras, and tensorflow).

This course is based on the “Big Data Analytics with R” book (with recent edits) authored by the course tutor. You will receive full access to the ebook version of this book before the course. Additionally, all activities (tutorials and exercises) of the course will be performed on the Mind Project Big Data virtual machines and computing clusters which consist of both CPU and GPU-accelerated multi-node Hadoop DFS with Spark engines and Hive databases, separate databases (both SQL and NoSQL including scalable and distributed MongoDB, HBase and CassandraDB) as well as all necessary R packages (e.g. Spark, h2o, keras, tensorflow, data.table, tidyverse etc.) pre-installed for your convenience to allow seamless connectivity of R with various Big Data tools and processing/analytical engines.

 

Programme outline

This is a 2-day instructor-led online training course with a week-long follow up period. The course will run from 10:00 in the morning to ~17:00 each day and will include a 50-minute break for lunch between morning and afternoon sessions and two 15-minute coffee/tea breaks. Following the course, you will be able to submit your solutions to the homework exercises and you will receive feedback from the tutor. 

This training course is tutor-led – all online tutorials are presented live by our expert instructor, you can ask questions, discuss the topic and interact with other learners. You can also email the tutor after the course if you have any questions related to the material presented during the course. 

The course will be recorded – you will have access to the video recordings of the course webinars and additional resources such as datasets, R code, academic papers related to the topics of the workshop, and supplementary exercises via Mind Project Learning Platform. 

Course dates: Monday-Tuesday, 4th-5th of July 2022, 10:00-17:00 London (UK) time

Deadline for registrations: Friday, 1st of July 2022 @ 17:00 London (UK) time

 

The programme for this course covers the following concepts and topics:

    • Use third-party R packages, which support parallel computing in order to increase the speed and processing capabilities of R with both CPUs and GPUs,

    • Work on large data sets in the Cloud (Microsoft Azure and Amazon EC2) through R deployed on the server,

    • Implement MapReduce framework through Hadoop straight from R console,

    • Manage Hadoop Distributed File System, HBase and Hive databases through R,

    • Connect to and extract, aggregate and manage the data in major relational SQL-based database management systems (RDBMSs) using a variety of R packages,

    • Apply NoSQL queries to access, transform and manipulate large data sets in MongoDB using R packages,

    • Improve the data flow and speed of data processing as well as implementation of AI models for large data sets through R’s connectivity with Spark and h2o packages,

    • Learn how to design Big Data systems to support scalable and distributed machine learning and AI (with Spark, h2o, keras and tensorflow packages),

    • Implement selected Big Data tools in the Big Data Product Cycle with R.

 

Course pre-requisites and further instructions

  • You will need at least one commonly used web browser installed on your PC (e.g. Chrome, Safari, Firefox, Edge etc.) to access our computing clusters and the Mind Project Learning Platform (with additional resources). There is no need for you to install any specific R packages as our clusters and virtual machines will be set-up for your convenience.

  • We recommend that the attendees have practical experience in data processing or quantitative research – gathered from either professional work or university education/research. We suggest that the course is preceded with our “Applied Data Science with R” open-to-public training course.

  • Your PC needs to be connected to a stable WiFi/Internet network (either home or office-based) and have Zoom video-conferencing application installed.

  • The primary spoken and written language of the course is English.

  • By enrolling on one of our online training courses you agree to the Training Terms and Conditions. Please read the Training Terms and Conditions before purchasing this course. Please note we reserve the right to cancel the course in case the number of registered attendees on the course is less than 5 individuals one week before its scheduled start date.

 

Your course instructor

Simon Walkowiak

Your instructor for this course will be Simon Walkowiak. Simon is a director at Mind Project Limited and a Ph.D. researcher in Artificial Intelligence at the Bartlett Centre for Advanced Spatial Analysis (University College London) and the Alan Turing Institute in London. Simon holds BSc (First Class Honours) in Psychology with Neuroscience and MSc (Distinction) in Big Data Science. He conducts and manages research projects on implementation and computational optimisation of novel AI approaches applicable to large-scale datasets to predict human behaviour and spatial cognition. Simon is the author of “Big Data Analytics with R” (2016) – a widely used textbook on high-performance computing with R language and its compatibility with ecosystem of Big Data tools e.g. SQL/NoSQL databases, Spark, Hadoop etc. Apart from research and data management consultancy, during the past several years, Simon has taught at more than 150 in-house or open-to-public statistical training courses (in R, Python, SQL and Scala for Spark languages) in the UK, Europe, Asia and USA. His major clients include organisations from finance and banking (HSBC, RBS, GE Capital, European Central Bank, Credit Suisse, ING etc.), research and academia (GSMA, CERN, University of Cambridge, UK Data Archive, Agri-Food Biosciences Institute, Newcastle University etc.), health (NHS), insurance (Liberty IT), transport (Steer Group) and government (Home Office, Ministry of Justice, Government Actuary’s Department etc.).

 

Discounts and multiple bookings

We offer 2 types of enrolment options:

  • Regular Fee – full-priced enrolment for learners representing commercial organisations or self-funded individuals who do not meet our eligibility criteria for discounted rates (please see below),
  • Discounted Fee – applicable to undergraduate and postgraduate students as well as representatives of registered charitable organisations and non-governmental organisations (NGOs) – this category also includes employees of the National Health Service (NHS).

Students and individuals eligible for the Discounted Fee should submit a copy of their student or organisation ID card (with their name and card expiry date visible) when making the purchase of their place on the course for the discount eligibility verification purposes. Alternatively, the discount eligibility can be verified by submitting either i.) a copy of a letter from the university registrar or student’s department confirming your status, or ii.) a copy of a letter from your employer (on a company letter-headed paper with a charity/NGO registration number) which confirms your current position within the organisation.

Apart from the discounted fees for students or employees of charitable organisations and NGOs, we are able to offer further discounts on the overall cost of your training if you wish to attend multiple related courses or enrol several delegates on this specific course. Please note that this offer is only available through our website.

  • If you book 3 or 4 tickets on any of our tutor-led open-to-public online training courses, you will receive 5% discount on the total price of your booking.
  • If you book 5 or more tickets on any of our tutor-led open-to-public online training courses, you will receive 10% discount on the total price of your booking.

All discounts are calculated automatically when tickets are added to the Cart. For bookings of 6 and more delegates on one course, we recommend that you contact us directly – we may be able to arrange a separate course just for your delegates at a discounted rate.

 

Arrange this course at your organisation

If your delegates cannot attend this public course, or you are interested in arranging this training course explicitly for your delegates (or at your premises) or simply you need a bespoke, made-to-measure training solution, please request a quote for the in-house version of this course based on your specific needs and desired outcomes of the training.

You may email us directly at info(at)mindproject.io and include the following information in your enquiry:

  • contact details to a person who should receive the quote,

  • number of delegates you would like to train,

  • approximate number of online sessions (or half-days / full days for on-site in-house course) you would like to arrange the course for (including additional support/project guidance if needed),

  • location of the training venue if not online,

  • any details on course customisation or specific topics you would like the course to address – most importantly, please indicate desired outcomes of the course if different then presented above,

  • any other questions you may have.

If you don’t know the answers to questions above or you are at early stages of course planning, we would be happy to arrange an informal chat and help you choose the most suitable and budget-efficient option.

What did previous delegates say about our courses?

“A very clear and practical overview of R and how it can be used in real world data sets. Learning from an expert!” - G's Group Holdings - Applied Data Science with R
“Excellent course for beginners and not-so-beginners in data analysis with Python. Simon brings real-world experience to the table and is a patient, knowledgeable and personable instructor.” - Roxana Lupu, Medallia - Applied Data Science with Python
“Thank you for sharing great knowledge with us which will be used for and will contribute a lot towards our business.” - Cabot Financial Ltd - Machine Learning with R
“Highly recommended, best place to start for machine learning with R!” - Max Fennelly, Pearson Ham - Machine Learning with R
"Great introduction to Hadoop from a clearly knowledgable demonstrator." - Feargal Egan, G-Research - Introduction to Hadoop with Java
“Simon is very knowledgeable and provided lots of solutions to consider in dealing with Big Data.” - Aidan Mews, Ministry of Justice - Big Data Methods with R
“The course has given me a greater understanding of Python and its capabilities.” - Mike Watts, Adactus Housing - Applied Data Science with Python
“This course was a great way to get an introduction to R and how it can be used to perform statistical analysis and run data visualisations.” - Daria Kuznetsova, Director of Strategy and Research at Teach First - Applied Data Science with R
“A really good, hands-on introduction that left me aware of and confident to use Hadoop stack. The practical writing of MapReduce and querying Hive was extremely useful.” - Chris Mainey, University College London & University Hospital Birmingham - Introduction to Hadoop with Java
“This course teaches you everything you need to know about the basic operations of R and useful exploratory data analysis tools. The content is both challenging and engaging, and the trainer is extremely supportive.” - Thomas Weeks, NHS Improvement - Applied Data Science with R
“The Machine Learning with R course by Mind Project provides a fantastic overview of supervised and unsupervised ML models and their applications. The course offers details on important topics such as advanced model evaluation metrics which are not emphasised on other ML courses.” - James Patten, Deloitte UK - Machine Learning with R
“I don't think I will ever open Excel again. The course has confirmed my perception of the applicability of R in the NHS.” - Paul Stroner, Deputy Director of Information and Analytics, NHS - Applied Data Science with R
“Really enjoyed the course! Simon had a great way of taking us from simple R topics to more complex Hadoop related concepts, which opened the window into Big Data methods.” - Sofia Diamanti, Deloitte UK - Big Data Methods with R
“This was a great course – very practical and taught in a relaxed style.” - Sophie Reid, Design Council - Applied Data Science with R
“The best organised data science course I have found so far.” - David Metcalfe, Doctoral Candidate, University of Oxford - Applied Data Science with Python
“Enjoyed the course. The tutor is in command of his subject and patient with his students.” - Dean Allsopp, DA Consulting - Machine Learning with R
“Simon is a great teacher – his workshops flow well and move at a good pace. I’ve really enjoyed both courses with Mind Project and I would definitely recommend them.” - Ellen Talbot, University of Liverpool - Machine Learning with R and Big Data Methods with R
“Excellent course for the intro to R, I highly recommend it.” - Dr Edward Barker, Institute of Psychiatry, King's College London - Applied Data Science with R
“The course provides a beginner enough knowledge to start analysis using R. I appreciated the instructor’s knowledge and the willingness to give as much explanation as possible.” - Prof. Sunil Sahadev, Salford Business School - Applied Data Science with R
“Informative and very useful, interactive course.” - Kuldeep Sohal, Bradford Institute for Health Research - Applied Data Science with R
“Course excellently laid out. Very rich content. It will provide material and food for thought for years!” - Ernesto Addiego-Guevara, Imperial College London - Applied Data Science with Python
“Simon was exceptional in conducting this course. The course covered a nice mixture of theory and practicals related to R, databases and Hadoop. It has really helped me to understand a lot of concepts and has motivated me to work on Hadoop.” - Sushant Chatufale, University of Portsmouth - Big Data Methods with R
“This is a great course, which I would recommend to anyone with an interest in data science no matter your ability.” - Clair Cooper, Durham University - Applied Data Science with R
“Great course, it covers a lot of material. Good balance between maths, theory, R and stats.” - Gordon Izatt - Machine Learning with R
“Expert tuition in Python and Machine Learning. I am now inspired and equipped to apply what I've learnt.” - John Taylor, TR Control Solutions Ltd - Machine Learning with Python
“This is a unique face-to-face course on data analysis using Python. Very rich learning experience in 3 days.” - Hamad Al Jassmi, Assistant Professor at UAE University - Applied Data Science with Python
“A great starter course. Exercises were provided so that we could practice and we could easily communicate with the course teacher.” - Iqqra Aziz, Get The Data - Applied Data Science with R
“Excellent and thorough intro to R, exceeded my expectations.” - Shahrooz Aliabadi, Lapinco Ltd - Applied Data Science with R
“Very interesting course. Really useful tutorials that progressed understanding of machine learning concepts.” - Talia Beech, Canadian Department of National Defence - Machine Learning with R
“The course provided me with a strong knowledge base to build upon.” - Tobias Koelsch, REWE Group - Machine Learning with Python
“Very informative, made me think of the potential Python holds in many fields. The trainer was excellent, he made everyone comfortable to contribute.” - Naeema Al Darmaki, UAE University - Applied Data Science with Python
“Excellent course. Very well structured and very professional. Simon catered for all abilities. Everyone gained a lot of information. Value for money.” - Dr. Noreen Quinn, Lecturer in Statistics, Cork Institute of Technology - Machine Learning with R
“Excellent course, a lot to cover and take back. Perfectly suited to analysts improving their skills in Python.” - Ben Amos, Argos - Applied Data Science with Python
"The course is very informative and Simon has been a great tutor. The ML steps he taught us is quite clear from setting up the python environment, running the scripts and analysis. He taught us new techniques in ML and how to do it properly." - Farraen Mohd Azmin Senior Project Engineer: Machine Learning Specialist - Machine Learning with Python
"Extremely useful introduction course to ML. It's really great to have the basics so clearly laid out, will definitely make use of the learnings and material in the future!" - Siem van Limpt, Senior Consultant, Element Energy - Machine Learning with Python
"The course provided an incredible overview of regression, clustering and classification methods. The amount of material we covered in three days was substantial, but Simon kept it clear, and the homeworks were a really helpful opportunity to bed in learning" - Harry Lloyd, Marine Data Scientist - Machine Learning with Python

Big Data Analytics with R – 2-Day Tutor-Led Course – July 2022

Related products