This course is designed for anyone who is new to big data projects, and would like to get better understanding what machine learning and artificial intelligence mean in practice. It is not a technical course, it does not involve coding, but it will make you feel confident when working in teams with data scientists and programmers. It will bring you up to speed with the data science, ML and AI terminology.  

The course is also designed for people who are generally interested in modern technologies and their applications - we have included case studies covering oil&gas predictive maintenance, use of AI in healthcare, application of sensor and other digital technologies  in buildings and construction, the role of machine learning in transport and logistics and many more.

You will learn about big data, Internet of Things (IoT), data science, big data technologies, artificial intelligence (AI), machine learning (ML) algorithms, neural networks, and why this could be relevant to you even if you don't have technology or data science background. Please note that this is NOT TECHNICAL TRAINING and it does NOT teach Coding/Development or Statistics, but it is suitable for technical professionals.  I am proud to say that this course was purchased by a large oil&gas company in Asia to educate their field engineers about machine learning as part of their digitalisation strategy. 

The course includes the interviews with industry experts that cover  big data developments in Real Estate, Logistics & Transportation and Healthcare industries.  You will learn how machine learning is used to predict engine failures, how artificial intelligence is used in anti-ageing, cancer treatment and clinical diagnosis, you will find out what technology is used in managing smart buildings and smart cities including Hudson Yards in New York.  We have got fantastic guest speakers who are the experts in their areas:

- WAEL ELRIFAI - Global VP of Solution Engineering - Big Data, IoT & AI at Hitachi Vantara with over 15 years of experience in the field of machine learning and IoT. Wael is also a Co-Authour of the book "The Future of IoT".

- ED GODBER - Healthcare Strategist with over 20 years of experience in Healthcare, Pharmaceuticals and start-ups specialising in Artificial Intelligence.

- YULIA PAK - Real Estate and Portfolio Strategy Consultant with over 12 years of experience in Commercial Real Estate advisory, currently working with clients who deploy IoT technologies to improve management of their real estate portfolio.

Watch the course trailer

What you will learn

  • Examples of Big Data and Data Science in Practice (Healthcare, Logistics & Transportation, Manufacturing, and Real Estate & Property Management industries)

  • Big Data Definition and Data Sources. Why we need to be data and technology savvy

  • Introduction to Data Science and Skillset required for working with Big Data

  • Technological Breakthroughs which Enable Big Data Solutions (Connectivity, Cloud, Open Source, Hadoop and NoSQL)

  • Big Data Technology Architecture and most popular technology tools used for each Architecture Layer

  • Beginner's Introduction to Data Analysis, Artificial Intelligence and Machine Learning

  • Simplified Overview of Machine Learning Algorithms and Neural Networks

Course curriculum

    1. Course Introduction

    2. Our Guest Speakers

    3. Why to Learn about Big Data

    4. Big Data Definition & Sources

    5. Big Data Definition

    6. Sources of data: Flying IoT - Drone Technology

    1. Section introduction

    2. Logistics & Transportation: Social Impact of Artificial Intelligence & IoT

    3. Logistics & Transportation: Predictive & Prescriptive Maintenance

    4. Logistics & Transportation: Prepositioning of Goods and Just in Time inventory

    5. Logistics & Transportation: Route Optimisation

    6. Logistics & Transportation: Warehouse Optimisation and order picking

    7. Logistics & Transportation: The Future of the industry

    8. Logistics and Transportation Quiz

    1. Predictive Maintenance in Manufacturing - Case Study SIBUR

    1. Real Estate: Introduction to big data in real estate

    2. Real Estate & Property Management: Technological Enablers

    3. Real Estate & Property Management: Technological Enablers

    4. Real Estate: Building Asset Management and Building Information Modelling

    5. Real Estate: Big Data and IoT in Building Maintenance and Management - examples

    6. Real Estate: Smart Buildings

    7. Real Estate: Smart Cities (examples - Los Angeles and Hudson Yards in New York)

    8. Real Estate: Smart Technologies Cost and Government Subsidies (example - Norway)

    9. Real Estate: Data Driven Future

    10. Real Estate and Property Management Quiz

    1. Healthcare: Data Challenges in Healthcare Industry

    2. Healthcare: Transforming Role of AI and Data Measurement Technologies

    3. Healthcare: Artificial Intelligence in Disease Preventionn

    4. Healthcare: Artificial Intelligence in Anti-Ageing

    5. Healthcare: AI in Clinical Decision Making and Cancer Treatment

    6. Healthcare: Clash of AI and Traditional Healthcare Science

    7. Healthcare: Final Remarks - Value of Artificial Intelligence to Consumers

    8. BIG DATA IN PRACTICE: SECTION WRAP-UP

    9. Healthcare Quiz

    1. Data Science Definition and Required Skillset

    2. Guest Speakers on importance of working in teams & understanding business objective

    3. Data Science Skillset: Section Wrap-Up

    4. Data Science Skills Quiz

About this course

  • £29.99
  • 82 lessons
  • 3.5 hours of video content

This course is for:

  • Non-technical leaders and managers

  • Anyone who is interested in big data, machine learning and artificial intelligence

  • Anyone who works with coders, data engineers and data scientists and wants to learn basics about big data technology and tools

  • People with technical background who want to gain insights in real life applications of data science skills

  • People without maths or computer science background, but who want to understand how Machine Learning algorithms work