Intro to Big Data, Data Science and Artificial Intelligence

Big Data Technology & Tools for Non-Technical Leaders. Industry expert insights on IoT, AI and Machine Learning for all.

4.59 (782 reviews)
Udemy
platform
English
language
Data Science
category
instructor
1,732
students
3.5 hours
content
Jan 2024
last update
$27.99
regular price

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

Description

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.

Hope you will enjoy the course and let me know  in the comments of each section how I can improve the course!  Please follow me on social media (Shortlisted Productions) - you can find the links on my profile page - just click on my name at the bottom of the page just before the reviews.  And please check out my other courses on Climate Change.

Content

Course overview and Introduction to big data

Course Introduction
Guest Speakers
BEFORE YOU START
Why learn about big data?
Big data definition and Sources of data
Big Data Definition

Big Data in Practice - LOGISTICS & TRANSPORTATION

Section introduction
Logistics & Transportation: Social Impact of Artificial Intelligence & IoT
Logistics & Transportation: Predictive & Prescriptive Maintenance
Logistics & Transportation: Prepositioning of Goods and Just in Time inventory
Logistics & Transportation: Route Optimisation
Logistics & Transportation: Warehouse Optimisation and order picking
Logistics & Transportation: The Future of the industry
Logistics and Transportation Quiz

Big Data in Practice - PREDICTIVE MAINTENANCE IN MANUFACTURING

Predictive Maintenance in Manufacturing - Case Study SIBUR

Big Data in Practice: REAL ESTATE & PROPERTY MANAGEMENT

Real Estate: Introduction to big data in real estate
Real Estate: Business Drivers for Using Big Data
Real Estate & Property Management: Technological Enablers
Real Estate: Building Asset Management and Building Information Modelling
Real Estate: Big Data and IoT in Building Maintenance and Management - examples
Real Estate: Smart Buildings
Additional Resources to Lecture on Smart Buildings
Real Estate: Smart Cities (examples - Los Angeles and Hudson Yards in New York)
Additional resources on Smart Cities
Real Estate: Smart Technologies Cost and Government Subsidies (example - Norway)
Real Estate: Data Driven Future
Real Estate and Property Management

Big Data in Practice: HEALTHCARE

Healthcare: Data Challenges in Healthcare Industry
Healthcare: Transforming Role of AI and Data Measurement Technologies
Healthcare: Artificial Intelligence in Disease Prevention
Healthcare: Artificial Intelligence in Anti-Ageing
Healthcare: AI in Clinical Decision Making and Cancer Treatment
Healthcare: Clash of AI and Traditional Healthcare Science
Healthcare: Final Remarks - Value of Artificial Intellegence to Consumers
BIG DATA IN PRACTICE: SECTION WRAP-UP
Healthcare

Data Science and Required Skillset

Data Science Definition and Required Skillset
Guest Speakers importance of working in teams & understanding business objective
Data Science Skillset: Section Wrap-Up
Handouts
Data Science Skills

Introduction to Big Data Technologies

Key Technological Advances and Enablers
Wide Adoption of Cloud Computing
Data Management Technological Breakthroughs (e.g. NoSQL, Hadoop)
Open Source and Open APIs
Big Data Enablers
Additional Resources and Handouts
Big Data Technology Architecture (including examples of popular technologies)
Big data technology architecture
Additional Resources and Handouts

Introduction to data analysis, Artificial Intelligence and Machine Learning

Why to be data and tech savvy
Big Data Analytics and Artificial Intelligence Definitions
Machine Learning Workflow and Training a Model
Model Accuracy and Ability to Generalise
Machine Learning Components: DATA
Machine Learning Components: FEATURES
Machine Learning Components: ALGORITHMS
Additional Resources and Handouts
Introduction to AI quiz

Simplified Overview of Machine Learning Algorithms

Classical Machine Learning: Supervised and Unsupervised Learning
SUPERVISED LEARNING: Classification
Classification: Naive Bayes
Classification: Decision Trees
Classification: Support Vector Machines (SVM)
Classification: Logistic Regression
Classification: K Nearest Neighbour
Classification: Anomaly Detection
SUPERVISED LEARNING: Regression
Classical Machine Learning: Unsupervised Learning
UNSUPERVISED LEARNING: Clustering
Clustering: K-Means
Clustering: Mean-Shift
Clustering: DBSCAN
Clustering: Anomaly Detection
UNSUPERVISED LEARNING: Dimensionality Reduction
UNSUPERVISED LEARNING: Association Rule
CLASSICAL MACHINE LEARNING - Section Wrap Up
REINFORCEMENT LEARNING
ENSEMBLES
Machine Learning Quiz

Introduction to Deep Learning and Neural Networks

DEEP LEARNING AND NEURAL NETWORKS
NEURAL NETWORKS: Convolutional Neural Network
NEURAL NETWORKS: Recurrent Neural Network
NEURAL NETWORKS: Generative Adversarial Network (GAN)
Additional Resources
Neural Networks Quiz

Machine Learning Sections Wrap-up

Choosing AI algorithms
Additional Resources and Handouts
Course Wrap up
Your feedback and more resources

Screenshots

Intro to Big Data, Data Science and Artificial Intelligence - Screenshot_01Intro to Big Data, Data Science and Artificial Intelligence - Screenshot_02Intro to Big Data, Data Science and Artificial Intelligence - Screenshot_03Intro to Big Data, Data Science and Artificial Intelligence - Screenshot_04

Reviews

Jose
July 19, 2023
SIENDO UN CURSO INTRODUCTORIO EN AREAS CON ENORME VOLUMEN DE INFORMACION Y TERMINOLOGIAS ESPECIFICAS, CREO QUE ES CONVENIENTE SOPORTAR LA DESCRIPCION DE CASOS PRACTICOS CON MAYOR MATERIAL DE APOYO GRAFICO ( EN EL CASO DE REAL ESTATE SE COMPLEMENTA CON MATERIAL DE APOYO AL FINAL). ES SUMAMANENTE VALIOSO INCLUIRLO DURANTE EL DESARROLLO DE LOS TEMAS CENTRALES. 2. POR EJEMPLO: EL CASO PRACTICO DE LOGISTICA Y TRANSPORTE, A MI PARECER ES QUE HASTA HORA TENDRIA UN 5 ESTRELLAS EN SU PRESENTACION Y COMPLEMENTACION DIDACTICA. 3. LA INCLUSION DE LOS SUBTITULOS TIENE UN VALOR INESTIMABLE. NO OBSTANTE, RECOMIENDO LA REVISION DE SOLO DE LA TRADUCCION EN ALGUNAS SECCIONES DEL CURSO (POR EJEMPLO AI EN LA SECCION DE HEALTHCARE ES PUESDTA MUCHAS VECES COMO I Y OTROS CASOS). ASIMISMO, CONSIDERO BENEFICIOSO PARA UN MEJOR SEGUIMIENTO DEL CURSO (DADA LA INCLUSION DE MUCHOS TERMINOS TECNICOS Y LOS ACENTOS VARIADOS DE LOS INTERLOCUTORES), DE UNA MEJOR PRESENTACION DE LOS SUBTITULOS, MEJORANDO LA ESTRUCTURACION DE LAS ORACIONES Y EL USO DE SIGNOS DE PUNTUACION.
Jakub
January 29, 2023
Great introduction to the world of Big Data and Artificial Intelligence. Tomorrow is today, so better check out how it looks like ;-).
Nienke
December 31, 2022
Great content for beginners like myself and lots of examples of how certain things work in practice, provided by excellent guest speakers. I would have preferred the section Overview of Machine Learning Algorithms to be structured/ explained differently - now it is too much info crammed into too short snippets.
Esther
April 1, 2022
It really gives you and very good introduction of each topic that is developed in the course. I recommend it if you would like to have an idea and know nothing about them.
Eric
February 8, 2022
This course was an excellent introduction to big data and provided a comprehensive overview to all the important pieces of the big data puzzle. Would highly recommend for anyone seeking to gain foundational knowledge on big data, data science, and artificial intelligence.
Esther
July 25, 2021
I liked this course. I think they explain each topic so easy and let you know a lot of examples to achieve a deep understanding.
Ashwati
May 31, 2021
The concepts of Big data, AI and Machine learning was very precisely explained. As a person who had no prior knowledge in these subjects, it was very much informative. There is no much technical support in this training as such but for an overview the training serves its purpose.
Amri
July 22, 2020
This course is a very good introduction to Big Data, Data Science and not least Machine Learning in order to understand how AI works. It exposes users on what to consider and look out for in managing Big Data and implementing Machine Learning.
Zulkifli
July 20, 2020
Good to know progress in health system with regards to digital. Have basic ideas of AI and what we need to know to improve business using ML.
Edmar
July 17, 2020
Very informative, overall good speakers and topics, extra resources and videos and bite size presentations.
Anis
July 16, 2020
This course is very beneficial in current working environment and lifestyle as having good data management and process will sure help optimize the time spend in completing a task.
Noor
July 14, 2020
for a starter like myself, this course provides insights of how big data, data science and AI relates to each other and how it works conceptually.
Arif
July 13, 2020
Provide good basic to intermediate information. I wish for more graphical / montage to go along with oral presentations to really illustrate applications.
Abd
July 7, 2020
some of the material are easy to follow while other are tough to understand the first time. maybe the subject is just that complex to be explain in layman's term. anyhow, tqvm
Fadzrul
June 30, 2020
Course is informative, maybe a bit too informative for non- Data Scientists. Will benefit from using a lot more visual aid to complement the chatty delivery.

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2427676
udemy ID
6/24/2019
course created date
12/26/2020
course indexed date
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